Mathias Hudoba de Badyn

• Retselis, Anastasios-Faidon; Knutsen, Elise Wright; Holdcroft, Sam; Viet, Shayla; Wahlén, Rebecka & Virdis, Mario [Vis alle 19 forfattere av denne artikkelen] (2026). CENSSAT-1: A space weather mission and an educational platform. I Detrell, Gisela; Alarcia, Ramón María García; Messina, Vincenzo & Kinnaird, Alexander (Red.), Proceedings of the 5th Symposium on Space Educational Activities (SSEA). Technical University of Munich. s. 852–857. doi: 10.14459/2026MD1857465. Fulltekst i vitenarkiv Vis sammendrag

  The Symposium on Space Educational Activities (SSEA), organised by the European Space Agency’s Education Office, provides a forum for university students, professionals working in education, and other professionals in industry or agencies to present and discuss their experiences organising, running and/or participating in Educational Activities related to Space. After successful past events in Padova (2015), Budapest (2018), Leicester (2019), and Barcelona (2022), the 5th SSEA was held in April 2026 (the 8th, 9th, and 10th) in the TUM Aerospace Campus in Willy-Messerschmitt-Strasse 5, Taufkirchen, Germany. The local organisation team was led by the Technical University of Munich (TUM), involving Professors, PostDocs, PhD Candidates, and Master’s and Bachelor’s students, in close collaboration with the Bavarian aerospace ecosystem partners.

• Zieglmeier, Sebastian Georg; Badyn, Mathias Hudoba de; Warakagoda, Narada Dilp; Krogstad, Thomas Røbekk & Engelstad, Paal E. (2025). Semi-Data-Driven Model Predictive Control: A Physics-Informed Data-Driven Control Approach. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. s. 2110–2117. doi: 10.1109/cdc57313.2025.11312410. Fulltekst i vitenarkiv Vis sammendrag

  Data-enabled predictive control (DeePC) has emerged as a powerful technique to control complex systems without the need for extensive modeling efforts. However, relying solely on offline collected data trajectories to represent the system dynamics introduces certain drawbacks. Therefore, we present a novel semi-data-driven model predictive control (SD-MPC) framework that combines (limited) model information with DeePC to address a range of these drawbacks, including sensitivity to noisy data and a lack of robustness. In this work, we focus on the performance of DeePC in operating regimes not captured by the offline collected data trajectories and demonstrate how incorporating an underlying parametric model can counteract this issue. SD-MPC exhibits equivalent closed-loop performance as DeePC for deterministic linear time-invariant systems. Simulations demonstrate the general control performance of the proposed SD-MPC for both a linear time-invariant system and a nonlinear system modeled as a linear parameter-varying system. These results provide numerical evidence of the enhanced robustness of SD-MPC over classical DeePC.

• Badyn, Mathias Hudoba de & Summers, Tyler (2025). Optimizing Weighted Hodge Laplacian Flows on Simplicial Complexes. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. doi: 10.1109/CDC57313.2025.11312795. Fulltekst i vitenarkiv Vis sammendrag

  Simplicial complexes are generalizations of graphs that describe higher-order network interactions among nodes in the graph. Network dynamics described by graph Laplacian flows have been widely studied in network science and control theory, and these can be generalized to simplicial complexes using Hodge Laplacians. We study weighted Hodge Laplacian flows on simplicial complexes. In particular, we develop a framework for weighted consensus dynamics based on weighted Hodge Laplacian flows and show some decomposition results for weighted Hodge Laplacians. We then show that two key spectral functions of the weighted Hodge Laplacians, the trace of the pseudoinverse and the smallest non-zero eigenvalue, are jointly convex in upper and lower simplex weights and can be formulated as semidefinite programs. Thus, globally optimal weights can be efficiently determined to optimize flows in terms of these functions. Numerical experiments demonstrate that optimal weights can substantially improve these metrics compared to uniform weights.

• Badyn, Mathias Hudoba de; Binz, Jonas; Iannelli, Andrea & Smith, Roy S. (2025). Distributed Dual-Quaternion Extended Kalman Filtering for Spacecraft Pose Estimation. Journal of Guidance Control and Dynamics. ISSN 0731-5090. 48(5), s. 1071–1087. doi: 10.2514/1.G007825. Fulltekst i vitenarkiv Vis sammendrag

  In this paper, a distributed dual-quaternion multiplicative extended Kalman filter for the estimation of poses and velocities of individual satellites in a fleet of spacecraft is analyzed. The proposed algorithm uses both absolute and relative pose measurements between neighboring satellites in a network, allowing each individual satellite to estimate its own pose and that of its neighbors. By utilizing the distributed Kalman consensus filter, a novel sensor and state-estimate fusion procedure is proposed that allows each satellite to improve its own state estimate by sharing data with its neighbors over a communication link. A leader–follower approach, whereby only a subset of the satellites has access to an absolute pose measurement, is also examined. In this case, followers rely solely on the information provided by their neighbors, as well as relative pose measurements to those neighbors. The algorithm is tested extensively via numerical simulations, and it is shown that the approach provides a substantial improvement in performance over the scenario in which the satellites do not cooperate. A case study of satellites swarming an asteroid is presented, and the performance in the leader–follower scenario is also analyzed.

• Virdis, Mario; Knutsen, Elise Wright; Kohfeldt, Anja; Jebali, Ramsey Al; Teodoro, Luis Filipe Alves & Skauli, Torbjørn [Vis alle 12 forfattere av denne artikkelen] (2024). University of Oslo CENSSAT-1 mission concept. Proceedings of the International Astronautical Congress. ISSN 0074-1795. Fulltekst i vitenarkiv
• Belgioioso, Giuseppe; Liao-McPherson, Dominic; Badyn, Mathias Hudoba de; Bolognani, Saverio; Smith, Roy S. & Lygeros, John [Vis alle 7 forfattere av denne artikkelen] (2024). Online Feedback Equilibrium Seeking. IEEE Transactions on Automatic Control. ISSN 0018-9286. 70(1), s. 203–218. doi: 10.1109/TAC.2024.3424345. Fulltekst i vitenarkiv Vis sammendrag

  This paper proposes a unifying design framework for dynamic feedback controllers that track solution trajectories of time-varying generalized equations, such as local minimizers of nonlinear programs or competitive equilibria (e.g., Nash) of non-cooperative games. Inspired by the feedback optimization paradigm, the core idea of the proposed approach is to re-purpose classic iterative algorithms for solving generalized equations (e.g., Josephy–Newton, forward-backward splitting) as dynamic feedback controllers by integrating online measurements of the continuous-time nonlinear plant. Sufficient conditions for closed-loop stability and robustness of the algorithm-plant cyber-physical interconnection are derived in a sampled-data setting by combining and tailoring results from (monotone) operator, fixed-point, and nonlinear systems theory. Numerical simulations on smart building automation and competitive supply-chain management are presented to support the theoretical findings.

• Behrunani, Varsha; Zagorowska, Marta; Badyn, Mathias Hudoba de; Ricca, Francesco; Heer, Philipp & Lygeros, John (2023). Degradation-aware data-enabled predictive control of energy hubs. Journal of Physics: Conference Series (JPCS). ISSN 1742-6588. 2600(7). doi: 10.1088/1742-6596/2600/7/072006. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Mitigating the energy use in buildings, together with satisfaction of comfort requirements are the main objectives of efficient building control systems. Augmenting building energy systems with batteries can improve the energy use of a building, while posing the challenge of considering battery degradation during control operation. We demonstrate the performance of a data-enabled predictive control (DeePC) approach applied to a single multi-zone building and an energy hub comprising an electric heat pump and a battery. In a comparison with a standard rule-based controller, results demonstrate that the performance of DeePC is superior in terms of satisfaction of comfort constraints without increasing grid power consumption. Moreover, DeePC achieved two-fold decrease in battery degradation over one year, as compared to a rule-based controller.

• Belgioioso, Giuseppe; Liao-McPherson, Dominic; Badyn, Mathias Hudoba de; Pelzmann, Nicolas; Lygeros, John & Dörfler, Florian (2023). Stability and Robustness of Distributed Suboptimal Model Predictive Control. IFAC-PapersOnLine. ISSN 2405-8971. 56(2), s. 5115–5120. doi: 10.1016/j.ifacol.2023.10.1295. Fulltekst i vitenarkiv Vis sammendrag

  In distributed model predictive control (MPC), the control input at each sampling time is computed by solving a large-scale optimal control problem (OCP) over a finite horizon using distributed algorithms. Typically, such algorithms require several (virtually, infinite) communication rounds between the subsystems to converge, which is a major drawback both computationally and from an energetic perspective (for wireless systems). Motivated by these challenges, we propose a suboptimal distributed MPC scheme in which the total communication burden is distributed also in time, by maintaining a running solution estimate for the large-scale OCP and updating it at each sampling time. We demonstrate that, under some regularity conditions, the resulting time-distributed suboptimal MPC control law recovers the qualitative robust stability properties of optimal MPC, if the communication budget at each sampling time is large enough.

• Terpin, Antonio; Fricker, Sylvain; Perez, Michel; Badyn, Mathias Hudoba de & Dorfler, Florian (2022). Distributed Feedback Optimisation for Robotic Coordination. American Control Conference (ACC). ISSN 0743-1619. s. 3710–3715. doi: 10.23919/acc53348.2022.9867738. Fulltekst i vitenarkiv Vis sammendrag

  Feedback optimisation is an emerging technique aimed at steering a system to an optimal steady state for a given objective function. We show that it is possible to employ this control strategy in a distributed manner. Moreover, we prove asymptotic convergence to the set of optimal configurations. To this scope, we show that exponential stability is needed only for the portion of the state that affects the objective function. This is showcased by driving a swarm of agents towards a target location while maintaining a target formation. Finally, we provide a sufficient condition on the topological structure of the specified formation to guarantee convergence of the swarm in formation around the target location.

• Summers, Tyler; Ganapathy, Karthik; Shames, Iman & Badyn, Mathias Hudoba de (2022). Self-Tuning Network Control Architectures. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. s. 5876–5881. doi: 10.1109/cdc51059.2022.9992780. Fulltekst i vitenarkiv Vis sammendrag

  We formulate a general mathematical framework for self-tuning network control architecture design. This problem involves jointly adapting the locations of active sensors and actuators in the network and the feedback control policy to all available information about the time-varying network state and dynamics to optimize a performance criterion. We propose a general solution structure analogous to the classical self-tuning regulator from adaptive control. We show that a special case with full-state feedback can be solved in principle with dynamic programming, and in the linear quadratic setting the optimal cost functions and policies are piecewise quadratic and piecewise linear, respectively. For large networks where exhaustive architecture search is prohibitive, we describe a greedy heuristic for joint architecture-policy design. We demonstrate in numerical experiments that self-tuning architectures can provide dramatically improved performance over fixed architectures. Our general formulation provides an extremely rich and challenging problem space with opportunities to apply a wide variety of approximation methods from stochastic control, system identification, reinforcement learning, and static architecture design.

• Bünning, Felix; Huber, Benjamin; Schalbetter, Adrian; Aboudonia, Ahmed; Badyn, Mathias Hudoba de & Heer, Philipp [Vis alle 8 forfattere av denne artikkelen] (2022). Physics-informed linear regression is competitive with two Machine Learning methods in residential building MPC. Applied Energy. ISSN 0306-2619. 310. doi: 10.1016/j.apenergy.2021.118491. Fulltekst i vitenarkiv Vis sammendrag

  Because physics-based building models are difficult to obtain as each building is individual, there is an increasing interest in generating models suitable for building MPC directly from measurement data. Machine learning methods have been widely applied to this problem and validated mostly in simulation; there are, however, few studies on a direct comparison of different models or validation in real buildings to be found in the literature. Methods that are indeed validated in application often lead to computationally complex non-convex optimization problems. Here we compare physics-informed Autoregressive–Moving-Average with Exogenous Inputs (ARMAX) models to Machine Learning models based on Random Forests and Input Convex Neural Networks and the resulting convex MPC schemes in experiments on a practical building application with the goal of minimizing energy consumption while maintaining occupant comfort, and in a numerical case study. The building has a water-based emission system and is located in temperate climate. We demonstrate that Predictive Control leads to savings between 26% and 49% of heating and cooling energy, compared to the building’s baseline hysteresis controller. Moreover, we show that all model types lead to satisfactory control performance in terms of constraint satisfaction and energy reduction. However, we also see that the physics-informed ARMAX models have a lower computational burden, and a superior sample efficiency compared to the Machine Learning based models. Moreover, even if abundant training data is available, the ARMAX models have a significantly lower prediction error than the Machine Learning models, which indicates that the encoded physics-based prior of the former cannot independently be found by the latter.

• Lefebure, Nicolas; Khosravi, Mohammad; Badyn, Mathias Hudoba de; Bünning, Felix; Lygeros, John & Jones, Colin [Vis alle 7 forfattere av denne artikkelen] (2022). Distributed model predictive control of buildings and energy hubs. Energy and Buildings. ISSN 0378-7788. 259. doi: 10.1016/j.enbuild.2021.111806. Fulltekst i vitenarkiv Vis sammendrag

  Model predictive control (MPC) strategies can be applied to the coordination of energy hubs to reduce their energy consumption. Despite the effectiveness of these techniques, their potential for energy savings are potentially underutilized due to the fact that energy demands are often assumed to be fixed quantities rather than controlled dynamic variables. The joint optimization of energy hubs and buildings’ energy management systems can result in higher energy savings. This paper investigates how different MPC strategies perform on energy management systems in buildings and energy hubs. We first discuss two MPC approaches; centralized and decentralized. While the centralized control strategy offers optimal performance, its implementation is computationally prohibitive and raises privacy concerns. On the other hand, the decentralized control approach, which offers ease of implementation, displays significantly lower performance. We propose a third strategy, distributed control based on dual decomposition, which has the advantages of both approaches. Numerical case studies and comparisons demonstrate that the performance of distributed control is close to the performance of the centralized case, while maintaining a significantly lower computational burden, especially in large-scale scenarios with many agents. Finally, we validate and verify the reliability of the proposed method through an experiment on a full-scale energy hub system in the NEST demonstrator in Dübendorf, Switzerland.

• Badyn, Mathias Hudoba de; Miehling, Erik; Janak, Dylan; Açıkmeşe, Behçet; Mesbahi, Mehran & Başar, Tamer [Vis alle 8 forfattere av denne artikkelen] (2021). Discrete-Time Linear-Quadratic Regulation via Optimal Transport. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. s. 3060–3065. doi: 10.1109/cdc45484.2021.9682825. Fulltekst i vitenarkiv Vis sammendrag

  In this paper, we consider a discrete-time stochastic control problem with uncertain initial and target states. We first discuss the connection between optimal transport and stochastic control problems of this form. Next, we formulate a linear-quadratic regulator problem where the initial and terminal states are distributed according to specified probability densities. A closed-form solution for the optimal transport map in the case of linear-time varying systems is derived, along with an algorithm for computing the optimal map. Two numerical examples pertaining to swarm deployment demonstrate the practical applicability of the model, and performance of the numerical method.

• Gkouletsos, Dimitris; Iannelli, Andrea; Badyn, Mathias Hudoba de & Lygeros, John (2021). Decentralized Trajectory Optimization for Multi-Agent Ergodic Exploration. IEEE Robotics and Automation Letters. ISSN 2377-3766. 6(4), s. 6336–6336. doi: 10.1109/lra.2021.3094242. Fulltekst i vitenarkiv Vis sammendrag

  Autonomous exploration is an application of growing importance in robotics. A promising strategy is ergodic trajectory planning, whereby an agent spends in each area a fraction of time which is proportional to its probability information density function. In this letter, a decentralized ergodic multi-agent trajectory planning algorithm featuring limited communication constraints is proposed. The agents’ trajectories are designed by optimizing a weighted cost encompassing ergodicity, control energy and close-distance operation objectives. To solve the underlying optimal control problem, a second-order descent iterative method coupled with a projection operator in the form of an optimal feedback controller is used. Exhaustive numerical analyses show that the multi-agent solution allows a much more efficient exploration in terms of completion task time and control energy distribution by leveraging collaboration among agents.

• Farhat, Omar; Jaoude, Dany Abou & Badyn, Mathias Hudoba de (2021). H∞ network optimization for edge consensus. European Journal of Control. ISSN 0947-3580. 62, s. 2–13. doi: 10.1016/j.ejcon.2021.06.032. Fulltekst i vitenarkiv Vis sammendrag

  This paper examines the performance problem of the edge agreement protocol for networks of agents operating on independent time scales, connected by weighted edges, and corrupted by exogenous disturbances. H∞-norm expressions and bounds are computed that are then used to derive new insights on network performance in terms of the effect of time scales and edge weights on disturbance rejection. We use our bounds to formulate a convex optimization problem for time scale and edge weight selection. Numerical examples are given to illustrate the applicability of the derived H∞-norm bound expressions, and the optimization paradigm is illustrated via a formation control example involving non-homogeneous agents.

• Bünning, Felix; Schalbetter, Adrian; Aboudonia, Ahmed; Badyn, Mathias Hudoba de; Heer, Philipp & Lygeros, John (2021). Input Convex Neural Networks for Building MPC. Proceedings of Machine Learning Research (PMLR). 144, s. 251–262. Fulltekst i vitenarkiv Vis sammendrag

  Model Predictive Control in buildings can significantly reduce their energy consumption. The cost and effort necessary for creating and maintaining first principle models for buildings make data- driven modelling an attractive alternative in this domain. In MPC the models form the basis for an optimization problem whose solution provides the control signals to be applied to the system. The fact that this optimization problem has to be solved repeatedly in real-time implies restrictions on the learning architectures that can be used. Here, we adapt Input Convex Neural Networks that are generally only convex for one-step predictions, for use in building MPC. We introduce additional constraints to their structure and weights to achieve a convex input-output relationship for multi- step ahead predictions. We assess the consequences of the additional constraints for the model accuracy and test the models in a real-life MPC experiment in an apartment in Switzerland. In two five-day cooling experiments, MPC with Input Convex Neural Networks is able to keep room temperatures within comfort constraints while minimizing cooling energy consumption.

• Belgioioso, Giuseppe; Liao-McPherson, Dominic; Badyn, Mathias Hudoba de; Bolognani, Saverio; Lygeros, John & Dörfler, Florian (2021). Sampled-Data Online Feedback Equilibrium Seeking: Stability and Tracking. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. s. 2702–2708. doi: 10.1109/cdc45484.2021.9683614. Fulltekst i vitenarkiv Vis sammendrag

  This paper proposes a general framework for constructing feedback controllers that drive complex dynamical systems to "efficient" steady-state (or slowly varying) operating points. Efficiency is encoded using generalized equations which can model a broad spectrum of useful objectives, such as optimality or equilibria (e.g. Nash, Wardrop, etc.) in noncooperative games. The core idea of the proposed approach is to directly implement iterative solution (or equilibrium seeking) algorithms in closed loop with physical systems. Sufficient conditions for closed-loop stability and robustness are derived; these also serve as the first closed-loop stability results for sampled-data feedback-based optimization. Numerical simulations of smart building automation and game-theoretic robotic swarm coordination support the theoretical results.

• Badyn, Mathias Hudoba de; Foight, Dillon R.; Calderone, Daniel; Mesbahi, Mehran & Smith, Roy S. (2021). Graph-Theoretic Optimization for Edge Consensus. IFAC-PapersOnLine. ISSN 2405-8971. 54(9), s. 538–538. doi: 10.1016/j.ifacol.2021.06.113. Fulltekst i vitenarkiv Vis sammendrag

  We consider network structures that optimize the H2-norm of weighted, time scaled consensus networks, under a minimal representation of such consensus networks described by the edge Laplacian. We show that a greedy algorithm can be used to find the minimum-H2 norm spanning tree, as well as how to choose edges to optimize the H2 norm when edges are added back to a spanning tree. In the case of edge consensus with a measurement model considering all edges in the graph, we show that adding edges between slow nodes in the graph provides the smallest increase in the H2 norm.

• Badyn, Mathias Hudoba de & Mesbahi, Mehran (2021). H2 Performance of Series-Parallel Networks: A Compositional Perspective. IEEE Transactions on Automatic Control. ISSN 0018-9286. 66(1), s. 361–361. doi: 10.1109/tac.2020.2979758. Fulltekst i vitenarkiv Vis sammendrag

  We examine the H2 norm of matrix-weighted leader–follower consensus on series–parallel networks. By using an extension of electrical network theory on matrix-valued resistances, voltages, and currents, we show that the computation of the H2 norm can be performed efficiently by decomposing the network into atomic elements and composition rules. Finally, we examine the problem of efficiently adapting the matrix-valued edge weights to optimize the H2 norm of the network.

• Foight, Dillon R.; Badyn, Mathias Hudoba de & Mesbahi, Mehran (2020). Performance and Design of Consensus on Matrix-Weighted and Time-Scaled Graphs. IEEE Transactions on Control of Network Systems. 7(4), s. 1822–1822. doi: 10.1109/tcns.2020.3001835. Fulltekst i vitenarkiv Vis sammendrag

  In this article, we consider the H2-norm of networked systems with multi-time-scale consensus dynamics and vector-valued agent states. This allows us to explore how measurement and process noise affect consensus on matrix-weighted graphs by examining edge-state consensus. In particular, we highlight an interesting case where the influences of the weighting and scaling on the H2-norm can be separated in the design problem. We then consider optimization algorithms for updating the time-scale parameters and matrix weights in order to minimize network response to injected noise. Finally, we present an application to formation control for multivehicle systems.

• Foight, Dillon R.; Badyn, Mathias Hudoba de & Mesbahi, Mehran (2019). Time Scale Design for Network Resilience. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. s. 2096–2101. doi: 10.1109/cdc40024.2019.9029472. Fulltekst i vitenarkiv Vis sammendrag

  In this paper we consider the H2-norm of networked systems with multi-time scale consensus dynamics. We develop a general framework for such systems that allows for edge weighting, independent agent-based time scales, as well as measurement and process noise. From this general system description, we highlight an interesting case where the influences of the weighting and scaling can be separated in the design problem. We then consider the design of the time scale parameters for minimizing the H2-norm for the purpose of network resilience.

• Badyn, Mathias Hudoba de & Mesbahi, Mehran (2019). Efficient Computation of H2 Performance on Series-Parallel Networks. American Control Conference (ACC). ISSN 0743-1619. s. 3364–3369. doi: 10.23919/acc.2019.8814989. Fulltekst i vitenarkiv Vis sammendrag

  Series-parallel networks are a class of graphs on which many NP-hard problems have tractable solutions. In this paper, we examine performance measures on leader-follower consensus on series-parallel networks. We show that a distributed computation of the H2 norm can be done efficiently on this system by exploiting a decomposition of the network into atomic elements and composition rules. Lastly, we examine the problem of adaptively re-weighting the network to optimize the H2 norm, and show that it can be done with similar complexity.

• Matheny, Matthew H.; Emenheiser, Jeffrey; Fon, Warren; Chapman, Airlie; Salova, Anastasiya & Rohden, Martin [Vis alle 15 forfattere av denne artikkelen] (2019). Exotic states in a simple network of nanoelectromechanical oscillators. Science. ISSN 0036-8075. 363(6431). doi: 10.1126/science.aav7932. Fulltekst i vitenarkiv Vis sammendrag

  Synchronization of oscillators, a phenomenon found in a wide variety of natural and engineered systems, is typically understood through a reduction to a first-order phase model with simplified dynamics. Here, by exploiting the precision and flexibility of nanoelectromechanical systems, we examined the dynamics of a ring of quasi-sinusoidal oscillators at and beyond first order. Beyond first order, we found exotic states of synchronization with highly complex dynamics, including weak chimeras, decoupled states, traveling waves, and inhomogeneous synchronized states. Through theory and experiment, we show that these exotic states rely on complex interactions emerging out of networks with simple linear nearest-neighbor coupling. This work provides insight into the dynamical richness of complex systems with weak nonlinearities and local interactions.

• Badyn, Mathias Hudoba de; Eren, Utku; Açikmeşe, Behçet & Mesbahi, Mehran (2018). Optimal Mass Transport and Kernel Density Estimation for State-Dependent Networked Dynamic Systems. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. s. 1225–1230. doi: 10.1109/cdc.2018.8619808. Fulltekst i vitenarkiv Vis sammendrag

  State-dependent networked dynamic systems are ones where the interconnections between agents change as a function of the states of the agents. Such systems are highly nonlinear, and a cohesive strategy for their control is lacking in the literature. In this paper, we present two techniques pertaining to the density control of such systems. Agent states are initially distributed according to some density, and a feedback law is designed to move the agents to a target density profile. We use optimal mass transport to design a feedforward control law propelling the agents towards this target density. Kernel density estimation, with constraints imposed by the state-dependent dynamics, is then used to allow each agent to estimate the local density of the agents.

• Reynolds, Taylor; Kaycee, Krish; Barzgaran, Bijan; Badyn, Mathias Hudoba de; Rice, Sean & Hansen, Emma [Vis alle 9 forfattere av denne artikkelen] (2018). Development of a Generic Guidance Navigation & Control System for Small Satellites: Application to HuskySat-1. 2018 AIAA SPACE and Astronautics Forum and Exposition. doi: 10.2514/6.2018-5403. Fulltekst i vitenarkiv Vis sammendrag

  his paper presents the development of a generic Guidance, Navigation & Control (GNC) system for small satellites at the University of Washington that serves as a testbed for algorithm development and supports small satellite mission design. Our ultimate aim is to advance the capabilities of autonomous satellite operations by demonstrating advanced on-board control and estimation techniques, though the work is equally applicable to earth-imaging, pointing and technology demonstration missions. The work discusses the development of flight software and requisite sensor, actuator and environmental models needed to validate flight software functionality. The first mission application is the HuskySat-1 mission, undertaken by a student-led group at the University of Washington. Primarily a technology demonstration, HuskySat-1 is a 3U CubeSat equipped with a pulsed plasma thruster and a high-frequency communication antenna, equipped with a 3-axis active attitude control subsystem. We demonstrate through software and hardware-based testing that our system supports both scientific payloads. We outline our approach to algorithm development, verification and validation, and briefly hardware-in-the-loop testing.

• Badyn, Mathias Hudoba de; Alemzadeh, Siavash & Mesbahi, Mehran (2017). Controllability and data-driven identification of bipartite consensus on nonlinear signed networks. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. s. 3557–3562. doi: 10.1109/cdc.2017.8264181. Fulltekst i vitenarkiv Vis sammendrag

  Nonlinear networked systems are of interest in several areas of research, such as multi-agent systems and social networks. In this paper, we examine the controllability of several classes of nonlinear networked dynamics on which the underlying graph admits negative weights. Such signed networks exhibit bipartite clustering when the underlying graph is structurally balanced. We show that structural balance is the key ingredient inducing uncontrollability when combined with a leader-node symmetry and a certain type of dynamical symmetry. We then examine the problem of extracting the bipartite structure of such graphs from data using Extended Dynamic Mode Decomposition to approximate the corresponding Koopman operator.

• Lee, Unsik; Reynolds, Taylor; Barzgaran, Bijan; Badyn, Mathias Hudoba de; Chrisope, Jeff & Adler, Aaron [Vis alle 8 forfattere av denne artikkelen] (2017). Development of Attitude Determination and Control Subsystem for 3U CubeSat with Electric Propulsion. AIAA SPACE and Astronautics Forum and Exposition. doi: 10.2514/6.2017-5320. Fulltekst i vitenarkiv Vis sammendrag

  This paper presents the development of an attitude determination and control subsystem (ADCS) for a technology demonstration mission launched by the University of Washington. HuskySat-1 is a 3U CubeSat equipped with a pulsed plasma thruster (PPT) and a high-gain communication antenna employing a full 3-axis active attitude control subsystem. The PPT aims to operate for an extended period of time to provide enough ∆V to maintain altitude for more than 3 months of operation in low earth orbit (LEO). At the same time, a novel high frequency K-band reflectarray antenna will complete multiple downlinks of up to 1Mb/s while flying over the ground station. The ADCS requirements are to estimate the current orientation and position of the spacecraft and provide reliable reorientation control across all attitude modes. Specifically, ADCS shall maintain pointing accuracy of 2° during ground station flyovers, and 4° accuracy during velocity-pointing maneuvers for PPT operation. For reorientation control, the ADCS employs two control algorithms. One implements a large angle reorientation of a solar panel bore-sight vector in a geodesic manner, while the other carries out a reorientation in the presence of an attitude forbidden zone due to PPT exhaust plumes. To validate the controller, simulations are performed in a closely modeled space environment and the results are compared with conventional algorithms.

• Alemzadeh, Siavash; Badyn, Mathias Hudoba de & Mesbahi, Mehran (2017). Controllability and stabilizability analysis of signed consensus networks. IEEE Conference on Control Technology and Applications (CCTA). ISSN 2768-0762. s. 55–60. doi: 10.1109/ccta.2017.8062440. Fulltekst i vitenarkiv Vis sammendrag

  Signed networks have been a topic of recent interest in the network control community as they allow studying antagonistic interactions in multi-agent systems. Although dynamical characteristics of signed networks have been well-studied, notions such as controllability and stabilizability for signed networks for protocols such as consensus are missing in the literature. Classically, graph automorphisms with respect to the input nodes have been used to characterize uncontrol-lability of consensus networks. In this paper, we show that in addition to the graph symmetry, the topological property of structural balance facilitates the derivation of analogous sufficient conditions for uncontrollability for signed networks. In particular, we provide an analysis which shows that a gauge transformation induced by structural balance allows symmetry arguments to hold for signed consensus networks. Lastly, we use fractional automorphisms to extend our observations to output controllability and stabilizability of signed networks.

• Badyn, Mathias Hudoba de & Mesbahi, Mehran (2017). Large-Scale Distributed Kalman Filtering via an Optimization Approach. IFAC-PapersOnLine. ISSN 2405-8971. 50(1), s. 10747–10747. doi: 10.1016/j.ifacol.2017.08.2268. Fulltekst i vitenarkiv Vis sammendrag

  Large-scale distributed systems such as sensor networks, often need to achieve filtering and consensus on an estimated parameter from high-dimensional measurements. Running a Kalman filter on every node in such a network is computationally intensive; in particular the matrix inversion in the Kalman gain update step is expensive. In this paper, we extend previous results in distributed Kalman filtering and large-scale machine learning to propose a gradient descent step for updating an estimate of the error covariance matrix; this is then embedded and analyzed in the context of distributed Kalman filtering. We provide properties of the resulting filters, in addition to a number of applications throughout the paper.

• Badyn, Mathias Hudoba de & Mesbahi, Mehran (2016). Growing controllable networks via whiskering and submodular optimization. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. s. 5276–5281. doi: 10.1109/cdc.2016.7798376. Fulltekst i vitenarkiv Vis sammendrag

  Simplicial complexes are generalizations of graphs that describe higher-order network interactions among nodes in the graph. Network dynamics described by graph Laplacian flows have been widely studied in network science and control theory, and these can be generalized to simplicial complexes using Hodge Laplacians. We study weighted Hodge Laplacian flows on simplicial complexes. In particular, we develop a framework for weighted consensus dynamics based on weighted Hodge Laplacian flows and show some decomposition results for weighted Hodge Laplacians. We then show that two key spectral functions of the weighted Hodge Laplacians, the trace of the pseudoinverse and the smallest non-zero eigenvalue, are jointly convex in upper and lower simplex weights and can be formulated as semidefinite programs. Thus, globally optimal weights can be efficiently determined to optimize flows in terms of these functions. Numerical experiments demonstrate that optimal weights can substantially improve these metrics compared to uniform weights.

• Badyn, Mathias Hudoba de; Marchand, Richard & Sydora, Richard D. (2016). Using orbital tethers to remediate geomagnetic radiation belts. Journal of Geophysical Research (JGR): Space Physics. ISSN 2169-9380. 121(2), s. 1123–1123. doi: 10.1002/2015ja021715. Fulltekst i vitenarkiv Vis sammendrag

  Abstract The Van Allen radiation belts pose a hazard to spacecraft and astronauts, and similar radiation belts around other planets pose a hazard to interplanetary probes. We discuss a method of remediating these radiation belts first proposed by Danilov and Vasilyev, and recently improved by Hoyt, Minor, and Cash, where a long, charged tether is placed in orbit inside a radiation belt. In this approach, an electric field of the tether scatters the belt particles into a pitch angle loss cone leading to absorption of the particles in the atmosphere. A test particle calculation is presented which computes the scattered pitch angle of belt particles as a function of initial pitch angle and gyrophase for different particle energies. The moments of the resulting distribution of scattered angle versus initial pitch angle are used to compute the number density of the belt as a function of time using a Fokker‐Planck diffusion approximation. Finally, we use the characteristic timescales of scattering for particles of different energies to discuss the feasibility of using such a system of tethers as a long and short‐term remediation solution.

• Badyn, Mathias Hudoba de; Karczmarek, Joanna L.; Sabella-Garnier, Philippe & Yeh, Ken Huai-Che (2015). Emergent geometry of membranes. Journal of High Energy Physics (JHEP). ISSN 1126-6708. 2015(11). doi: 10.1007/jhep11(2015)089. Fulltekst i vitenarkiv Vis sammendrag

  In work [1], a surface embedded in flat ℝ^3 is associated to any three hermitian matrices. We study this emergent surface when the matrices are large, by constructing coherent states corresponding to points in the emergent geometry. We find the original matrices determine not only shape of the emergent surface, but also a unique Poisson structure. We prove that commutators of matrix operators correspond to Poisson brackets. Through our construction, we can realize arbitrary noncommutative membranes: for example, we examine a round sphere with a non-spherically symmetric Poisson structure. We also give a natural construction for a noncommutative torus embedded in ℝ^3. Finally, we make remarks about area and find matrix equations for minimal area surfaces.

• Badyn, Mathias Hudoba de & Tahir, Adam (2015). Orbital Electromagnetic Field Generators as a Method for Removing Small and Untrackable Space Debris. AIAA SPACE 2015 Conference and Exposition. doi: 10.2514/6.2015-4660. Fulltekst i vitenarkiv Vis sammendrag

  Space debris poses a hazard to all space operations and programs. Of particular concern are small pieces of debris that are untrackable by surface radar. This paper discusses two passive methods for remediating this small debris using electrodynamic tethers; a scattering method which accelerates debris into a hyperbolic escape orbit, and a `vacuum' method which collects debris onto the tether itself. Both methods are shown via simulation to be effective at removing the debris, and a discussion of the risks and benefits of each method is presented.

• Badyn, Mathias Hudoba de; Chapman, Airlie & Mesbahi, Mehran (2015). Network entropy: A system-theoretic perspective. IEEE Conference on Decision and Control. Proceedings. ISSN 0743-1546. s. 5512–5517. doi: 10.1109/cdc.2015.7403083. Fulltekst i vitenarkiv Vis sammendrag

  In this paper, we highlight the importance of two measures associated with networked dynamic systems, namely the loop entropy and the Kolmogorov-Sinai entropy, that quantify the notion of information content in the network. We then proceed to show connections between these measures and certain system theoretic properties that these networks exhibit for two classes of network dynamics. Throughout the paper, we also provide relevant bounds and insights into what these network measures quantify.

• Owen, James E.; Badyn, Mathias Hudoba de; Clarke, Cathie J. & Robins, Luke (2013). Characterizing thermal sweeping: a rapid disc dispersal mechanism. Monthly notices of the Royal Astronomical Society. ISSN 0035-8711. 436(2), s. 1438–1438. doi: 10.1093/mnras/stt1663. Fulltekst i vitenarkiv Vis sammendrag

  We consider the properties of protoplanetary discs that are undergoing inside-out clearing by photoevaporation. In particular, we aim to characterize the conditions under which a protoplanetary disc may undergo ‘thermal sweeping’, a rapid (≲10^4 years) disc destruction mechanism proposed to occur when a clearing disc reaches sufficiently low surface density at its inner edge and where the disc is unstable to runaway penetration by the X-rays. We use a large suite of 1D radiation-hydrodynamic simulations to probe the observable parameter space, which is unfeasible in higher dimensions. These models allow us to determine the surface density at which thermal sweeping will take over the disc's evolution and to evaluate this critical surface density as a function of X-ray luminosity, stellar mass and inner hole radius. We find that this critical surface density scales linearly with X-ray luminosity, increases with inner hole radius and decreases with stellar mass, and we develop an analytic model that reproduces these results. This surface density criterion is then used to determine the evolutionary state of protoplanetary discs at the point that they become unstable to destruction by thermal sweeping. We find that transition discs created by photoevaporation will undergo thermal sweeping when their inner holes reach 20–40 au, implying that transition discs with large holes and no accretion (which were previously a predicted outcome of the later stages of all flavours of the photoevaporation model) will not form. Thermal sweeping thus avoids the production of large numbers of large, non-accreting holes (which are not observed) and implies that the majority of holes created by photoevaporation should still be accreting. We emphasize that the surface density criteria that we have developed apply to all situations where the disc develops an inner hole that is optically thin to X-rays. It thus applies not only to the case of holes originally created by photoevaporation but also to holes formed, for example, by the tidal influence of planets.

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• Holdcroft, Sam; Bocci, Alessio; Scholtz, Laura-Kristin; Retselis, Anastasios-Faidon; Knutsen, Elise Wright & Jebali, Ramsey Al [Vis alle 20 forfattere av denne artikkelen] (2025). CENSSAT-1 mission concept: a CubeSat for space weather monitoring. doi: 10.5281/ZENODO.17036544. Fulltekst i vitenarkiv Vis sammendrag

  This paper presents an introduction to the CENSSAT-1 mission, an 8U CubeSat, which aims to study space situational awareness. It will investigate the effects of space weather on Earth from a 500 km orbit, using a camera, multi-purpose particle detector, and a Langmuir probe. It will additionally monitor space debris using a radar instrument, and conduct experiments on optimal control and drag based manoeuvring. CENSSAT-1 is aiming for launch in 2027.

• Badyn, Mathias Hudoba de (2014). Born-Infeld action geometries. doi: 10.14288/1.0085973. Fulltekst i vitenarkiv
• Badyn, Mathias Hudoba de (2014). On the Hilbert-Pólya and Pair Correlation Conjectures. doi: 10.14288/1.0080660. Fulltekst i vitenarkiv
• Badyn, Mathias Hudoba de (2019). Consensus Over Networked Dynamical Systems: Control, Design, & Interaction. University of Washington Libraries. Fulltekst i vitenarkiv
• Badyn, Mathias Hudoba de (2017). On the Control of Consensus Networks: Theory and Applications. University of Washington Libraries. Fulltekst i vitenarkiv

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