Pub Date : 2024-06-17DOI: 10.1109/LCSYS.2024.3415489
Anchita Dey;Shubhendu Bhasin
In this letter, we address the problem of computing the maximal admissible robust positive invariant (MARPI) set for discrete-time linear time-varying systems with parametric uncertainties and additive disturbances. The system state and input are subject to hard constraints, and the system parameters and the exogenous disturbance are assumed to belong to known convex polytopes. We provide necessary and sufficient conditions for the existence of the non-empty MARPI set, and explore relevant features of the set that lead to an efficient finite-time converging algorithm with a suitable stopping criterion. The analysis hinges on backward reachable sets defined using recursively computed halfspaces and the minimal RPI set. A numerical example is used to validate the theoretical development.
{"title":"Computation of Maximal Admissible Robust Positive Invariant Sets for Linear Systems With Parametric and Additive Uncertainties","authors":"Anchita Dey;Shubhendu Bhasin","doi":"10.1109/LCSYS.2024.3415489","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3415489","url":null,"abstract":"In this letter, we address the problem of computing the maximal admissible robust positive invariant (MARPI) set for discrete-time linear time-varying systems with parametric uncertainties and additive disturbances. The system state and input are subject to hard constraints, and the system parameters and the exogenous disturbance are assumed to belong to known convex polytopes. We provide necessary and sufficient conditions for the existence of the non-empty MARPI set, and explore relevant features of the set that lead to an efficient finite-time converging algorithm with a suitable stopping criterion. The analysis hinges on backward reachable sets defined using recursively computed halfspaces and the minimal RPI set. A numerical example is used to validate the theoretical development.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17DOI: 10.1109/LCSYS.2024.3415471
Yuhao Zhang;Hang Zhang;Xiangru Xu
The surging popularity of neural networks in controlled systems underscores the imperative for formal verification to ensure the reliability and safety of such systems. Existing set propagation-based approaches for reachability analysis in neural network control systems encounter challenges in scalability and flexibility. This letter introduces a novel tunable hybrid zonotope-based method for computing both forward and backward reachable sets of neural network control systems. The proposed method incorporates an optimization-based network reduction technique and an activation pattern-based hybrid zonotope propagation approach for ReLU-activated feedforward neural networks. Furthermore, it enables two tunable parameters to balance computational complexity and approximation accuracy. A numerical example is provided to illustrate the performance and tunability of the proposed approach.
{"title":"Reachability Analysis of Neural Network Control Systems With Tunable Accuracy and Efficiency","authors":"Yuhao Zhang;Hang Zhang;Xiangru Xu","doi":"10.1109/LCSYS.2024.3415471","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3415471","url":null,"abstract":"The surging popularity of neural networks in controlled systems underscores the imperative for formal verification to ensure the reliability and safety of such systems. Existing set propagation-based approaches for reachability analysis in neural network control systems encounter challenges in scalability and flexibility. This letter introduces a novel tunable hybrid zonotope-based method for computing both forward and backward reachable sets of neural network control systems. The proposed method incorporates an optimization-based network reduction technique and an activation pattern-based hybrid zonotope propagation approach for ReLU-activated feedforward neural networks. Furthermore, it enables two tunable parameters to balance computational complexity and approximation accuracy. A numerical example is provided to illustrate the performance and tunability of the proposed approach.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141544099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17DOI: 10.1109/LCSYS.2024.3415498
Jinjiang Li;Kaijian Hu;Tao Liu
This letter investigates the data-driven control (DDC) problem for a class of nonlinear systems satisfying the linear growth condition. The studied system has completely unknown model parameters and mismatched nonlinearity and input. A static linear state-feedback domination controller is proposed to make the closed-loop system globally exponentially stable, which is obtained by offline solving the data-based mixed integer programs (MIPs). Compared to the existing DDC methods, our approach can handle high-order nonlinear systems with nontriangular structures. In contrast to adaptive control methods that require introducing adaptive parameters or Nussbaum functions for handling unknown parameters in the control path, resulting in a dynamic nonlinear controller, our proposed approach only requires offline computation to achieve the desired control objectives using a static linear controller. Two numerical examples are given to illustrate the effectiveness of the proposed method.
{"title":"Data-Driven Feedback Domination Control of a Class of Nonlinear Systems","authors":"Jinjiang Li;Kaijian Hu;Tao Liu","doi":"10.1109/LCSYS.2024.3415498","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3415498","url":null,"abstract":"This letter investigates the data-driven control (DDC) problem for a class of nonlinear systems satisfying the linear growth condition. The studied system has completely unknown model parameters and mismatched nonlinearity and input. A static linear state-feedback domination controller is proposed to make the closed-loop system globally exponentially stable, which is obtained by offline solving the data-based mixed integer programs (MIPs). Compared to the existing DDC methods, our approach can handle high-order nonlinear systems with nontriangular structures. In contrast to adaptive control methods that require introducing adaptive parameters or Nussbaum functions for handling unknown parameters in the control path, resulting in a dynamic nonlinear controller, our proposed approach only requires offline computation to achieve the desired control objectives using a static linear controller. Two numerical examples are given to illustrate the effectiveness of the proposed method.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17DOI: 10.1109/LCSYS.2024.3415485
Yichao Wang;Mohamadamin Rajabinezhad;Shan Zuo
This letter presents fully distributed, resilient secondary defense strategies for AC microgrids considering both communication link faults and a broader spectrum of unbounded false data injection (FDI) attacks on control input channels. In contrast to existing solutions that address bounded faults or unbounded attacks on the input channels with bounded first-order time derivatives, the proposed strategies aim to enhance the defense capabilities against polynomially unbounded FDI attacks while the communication links are under faults. Resilient defense strategies for AC microgrids are developed to mitigate the adverse effects of the polynomially unbounded FDI attacks on control input channels and communication link faults, ensuring the stable and resilient operation of AC microgrids. Through rigorous Lyapunov-based stability analysis, the formal certification of the proposed strategies is demonstrated in achieving uniformly ultimately bounded convergence in frequency regulation, voltage containment, and active power sharing in multi-inverter-based AC microgrids. The effectiveness of these resilient strategies is further validated on a modified IEEE 34-bus test feeder system with four inverter-based distributed energy resources.
{"title":"Secondary Defense Strategies of AC Microgrids Under Polynomially Unbounded FDI Attacks and Communication Link Faults","authors":"Yichao Wang;Mohamadamin Rajabinezhad;Shan Zuo","doi":"10.1109/LCSYS.2024.3415485","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3415485","url":null,"abstract":"This letter presents fully distributed, resilient secondary defense strategies for AC microgrids considering both communication link faults and a broader spectrum of unbounded false data injection (FDI) attacks on control input channels. In contrast to existing solutions that address bounded faults or unbounded attacks on the input channels with bounded first-order time derivatives, the proposed strategies aim to enhance the defense capabilities against polynomially unbounded FDI attacks while the communication links are under faults. Resilient defense strategies for AC microgrids are developed to mitigate the adverse effects of the polynomially unbounded FDI attacks on control input channels and communication link faults, ensuring the stable and resilient operation of AC microgrids. Through rigorous Lyapunov-based stability analysis, the formal certification of the proposed strategies is demonstrated in achieving uniformly ultimately bounded convergence in frequency regulation, voltage containment, and active power sharing in multi-inverter-based AC microgrids. The effectiveness of these resilient strategies is further validated on a modified IEEE 34-bus test feeder system with four inverter-based distributed energy resources.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17DOI: 10.1109/LCSYS.2024.3415477
Maison Clouâtré;Makhin Thitsa;Wesley Kinney;Andrea Conti;Moe Z. Win
This letter explores safety-critical control of nonlinear systems in settings where a finite-rate communication channel stands in the path of state feedback. We show that the mere existence of a nominally safe control law (certified by an exponential barrier function) suffices to provide safe control in these limited-information settings. We introduce the notion of “safety escape time”, the minimum time a system takes to become unsafe in the absence of actuation. The results complement the existing literature on stabilizing control with limited information and represent a step towards a complete understanding of safety-critical control with limited information.
{"title":"Safety-Critical Control With Limited Information","authors":"Maison Clouâtré;Makhin Thitsa;Wesley Kinney;Andrea Conti;Moe Z. Win","doi":"10.1109/LCSYS.2024.3415477","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3415477","url":null,"abstract":"This letter explores safety-critical control of nonlinear systems in settings where a finite-rate communication channel stands in the path of state feedback. We show that the mere existence of a nominally safe control law (certified by an exponential barrier function) suffices to provide safe control in these limited-information settings. We introduce the notion of “safety escape time”, the minimum time a system takes to become unsafe in the absence of actuation. The results complement the existing literature on stabilizing control with limited information and represent a step towards a complete understanding of safety-critical control with limited information.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17DOI: 10.1109/LCSYS.2024.3415458
J. R. Keulen;B. Jayawardhana
We study the properties of remnant function, which is a function of output remnant versus amplitude of the input signal, of Preisach hysteresis operators. The remnant behavior (or the leftover memory when the input reaches zero) enables an energy-optimal application of piezoactuator systems where the applied electrical field can be removed when the desired strain/displacement has been attained. We show that when the underlying weight of Preisach operators is positive, the resulting remnant curve is monotonically increasing and accordingly a Newton and secant update laws for the iterative remnant control are proposed that allows faster convergence to the desired remnant value than the existing iterative remnant control algorithm in literature as validated by numerical simulation.
{"title":"Newton and Secant Methods for Iterative Remnant Control of Preisach Hysteresis Operators","authors":"J. R. Keulen;B. Jayawardhana","doi":"10.1109/LCSYS.2024.3415458","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3415458","url":null,"abstract":"We study the properties of remnant function, which is a function of output remnant versus amplitude of the input signal, of Preisach hysteresis operators. The remnant behavior (or the leftover memory when the input reaches zero) enables an energy-optimal application of piezoactuator systems where the applied electrical field can be removed when the desired strain/displacement has been attained. We show that when the underlying weight of Preisach operators is positive, the resulting remnant curve is monotonically increasing and accordingly a Newton and secant update laws for the iterative remnant control are proposed that allows faster convergence to the desired remnant value than the existing iterative remnant control algorithm in literature as validated by numerical simulation.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141544003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1109/LCSYS.2024.3414970
Lorenzo Sabug;Lorenzo Fagiano;Fredy Ruiz
The problem of contextual global optimization is treated, in which a generally non-convex scalar objective (possibly black-box) depends not only on the decision variables, but also on uncontrollable, observable context variables. Assuming Lipschitz continuity of the objective function with respect to its arguments, the proposed approach builds a Set Membership model from observed samples. According to the observed context, a submodel that relates the objective to the decision variables is isolated, and used by a zeroth-order technique to pick the appropriate decision variable for sampling. A novel trust region dynamic is introduced, adjusting its size with samples instead of iterations. Such a technique makes the resulting contextual optimization algorithm more flexible with respect to the context behavior, whether it is changing smoothly, abruptly, or a combination of both. Benchmark tests and a case study demonstrate the efficacy of the proposed method.
{"title":"Sample-Based Trust Region Dynamics in Contextual Global Optimization","authors":"Lorenzo Sabug;Lorenzo Fagiano;Fredy Ruiz","doi":"10.1109/LCSYS.2024.3414970","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3414970","url":null,"abstract":"The problem of contextual global optimization is treated, in which a generally non-convex scalar objective (possibly black-box) depends not only on the decision variables, but also on uncontrollable, observable context variables. Assuming Lipschitz continuity of the objective function with respect to its arguments, the proposed approach builds a Set Membership model from observed samples. According to the observed context, a submodel that relates the objective to the decision variables is isolated, and used by a zeroth-order technique to pick the appropriate decision variable for sampling. A novel trust region dynamic is introduced, adjusting its size with samples instead of iterations. Such a technique makes the resulting contextual optimization algorithm more flexible with respect to the context behavior, whether it is changing smoothly, abruptly, or a combination of both. Benchmark tests and a case study demonstrate the efficacy of the proposed method.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10558714","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141495213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1109/LCSYS.2024.3414976
Jaehan Im;Yue Yu;David Fridovich-Keil;Ufuk Topcu
Coordination in multiplayer games enables players to avoid the lose-lose outcome that often arises at Nash equilibria. However, designing a coordination mechanism typically requires the consideration of the joint actions of all players, which becomes intractable in large-scale games. We develop a novel coordination mechanism, termed reduced rank correlated equilibria. The idea is to approximate the set of all joint actions with the actions used in a set of pre-computed Nash equilibria via a convex hull operation. In a game with n players and each player having m actions, the proposed mechanism reduces the number of joint actions considered from ${mathcal {O}}(m^{n})$ to ${mathcal {O}}(mn)$ and thereby mitigates computational complexity. We demonstrate the application of the proposed mechanism to an air traffic queue management problem. Compared with the correlated equilibrium—a popular benchmark coordination mechanism—the proposed approach is capable of solving a problem involving four thousand times more joint actions while yielding similar or better performance in terms of a fairness indicator and showing a maximum optimality gap of 0.066% in terms of the average delay cost. In the meantime, it yields a solution that shows up to 99.5% improvement in a fairness indicator and up to 50.4% reduction in average delay cost compared to the Nash solution, which does not involve coordination.
多人游戏中的协调能让玩家避免纳什均衡时经常出现的双输结果。然而，设计协调机制通常需要考虑所有博弈者的联合行动，这在大规模博弈中变得非常棘手。我们开发了一种新的协调机制，称为 "降低等级的相关均衡"。其思路是通过凸壳操作，用一组预先计算好的纳什均衡状态中使用的行动来近似所有联合行动的集合。在一个有 n 个棋手且每个棋手有 m 个行动的博弈中，所提出的机制将考虑的联合行动的数量从 ${mathcal {O}}(m^{n})$ 减少到 ${mathcal {O}}(mn)$ ，从而降低了计算复杂度。我们演示了所提机制在空中交通队列管理问题中的应用。与相关均衡--一种流行的基准协调机制--相比，所提出的方法能够解决涉及四千倍以上联合行动的问题，同时在公平性指标方面具有相似或更好的性能，并且在平均延迟成本方面显示出 0.066% 的最大最优性差距。同时，与不涉及协调的纳什方案相比，它所得到的方案在公平性指标上提高了 99.5%，在平均延迟成本上降低了 50.4%。
{"title":"Coordination in Noncooperative Multiplayer Matrix Games via Reduced Rank Correlated Equilibria","authors":"Jaehan Im;Yue Yu;David Fridovich-Keil;Ufuk Topcu","doi":"10.1109/LCSYS.2024.3414976","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3414976","url":null,"abstract":"Coordination in multiplayer games enables players to avoid the lose-lose outcome that often arises at Nash equilibria. However, designing a coordination mechanism typically requires the consideration of the joint actions of all players, which becomes intractable in large-scale games. We develop a novel coordination mechanism, termed reduced rank correlated equilibria. The idea is to approximate the set of all joint actions with the actions used in a set of pre-computed Nash equilibria via a convex hull operation. In a game with n players and each player having m actions, the proposed mechanism reduces the number of joint actions considered from \u0000<inline-formula> <tex-math>${mathcal {O}}(m^{n})$ </tex-math></inline-formula>\u0000 to \u0000<inline-formula> <tex-math>${mathcal {O}}(mn)$ </tex-math></inline-formula>\u0000 and thereby mitigates computational complexity. We demonstrate the application of the proposed mechanism to an air traffic queue management problem. Compared with the correlated equilibrium—a popular benchmark coordination mechanism—the proposed approach is capable of solving a problem involving four thousand times more joint actions while yielding similar or better performance in terms of a fairness indicator and showing a maximum optimality gap of 0.066% in terms of the average delay cost. In the meantime, it yields a solution that shows up to 99.5% improvement in a fairness indicator and up to 50.4% reduction in average delay cost compared to the Nash solution, which does not involve coordination.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141500218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1109/LCSYS.2024.3414971
Philipp Schitz;Johann C. Dauer;Paolo Mercorelli
Implementation of Model Predictive Control (MPC) on hardware with limited computational resources remains a challenge. Especially for long-distance maneuvers that require small sampling times, the necessary horizon lengths prevent its application on onboard computers. In this letter, we propose a computationally efficient tube-based shrinking horizon MPC that is scalable to long prediction horizons. Using move blocking, we ensure that a given number of decision inputs is efficiently used throughout the maneuver. Next, a method to substantially reduce the number of constraints is introduced. The approach is demonstrated with a helicopter landing on an inclined platform using a prediction horizon of 300 steps. The constraint reduction decreases the computation time by an order of magnitude with a slight increase in trajectory cost.
{"title":"Robust Maneuver Planning With Scalable Prediction Horizons: A Move Blocking Approach","authors":"Philipp Schitz;Johann C. Dauer;Paolo Mercorelli","doi":"10.1109/LCSYS.2024.3414971","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3414971","url":null,"abstract":"Implementation of Model Predictive Control (MPC) on hardware with limited computational resources remains a challenge. Especially for long-distance maneuvers that require small sampling times, the necessary horizon lengths prevent its application on onboard computers. In this letter, we propose a computationally efficient tube-based shrinking horizon MPC that is scalable to long prediction horizons. Using move blocking, we ensure that a given number of decision inputs is efficiently used throughout the maneuver. Next, a method to substantially reduce the number of constraints is introduced. The approach is demonstrated with a helicopter landing on an inclined platform using a prediction horizon of 300 steps. The constraint reduction decreases the computation time by an order of magnitude with a slight increase in trajectory cost.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1109/LCSYS.2024.3414968
Olga Napolitano;Annamaria Pinizzotto;Matteo Verdecchia;Alessio Pettinari;Daniela Selvi;Lucia Pallottino;Paolo Salaris
This letter proposes an optimal active perception strategy using the Constructibility Gramian (CG) as a metric to quantify the richness of the information acquired along the planned trajectory. A critical issue is the dependence of the CG on the transition matrix, whose closed-form expression is not available for most robotic systems while its numerical computation is usually costly. We leverage differential flatness to transform the nonlinear system in the Brunovsky form, for which the transition matrix reduces to the exponential of a Jordan block. The resulting CG is a measure of the acquired information through the flat outputs about the flat outputs themselves and their derivatives. The inverse flatness change of coordinates is then used to come back to the original state variables, needed for computing the feedback control law. The flat outputs are parameterized through B-Splines with control points determined by actively maximizing CG. We simulate our approach on a unicycle vehicle and a planar UAV that need to estimate their configuration while measuring their distance w.r.t. two fixed markers. Simulations show the effectiveness of our methodology in reducing both the computational time and the estimation uncertainty.
{"title":"Active Sensing Control for Differentially Flat Systems","authors":"Olga Napolitano;Annamaria Pinizzotto;Matteo Verdecchia;Alessio Pettinari;Daniela Selvi;Lucia Pallottino;Paolo Salaris","doi":"10.1109/LCSYS.2024.3414968","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3414968","url":null,"abstract":"This letter proposes an optimal active perception strategy using the Constructibility Gramian (CG) as a metric to quantify the richness of the information acquired along the planned trajectory. A critical issue is the dependence of the CG on the transition matrix, whose closed-form expression is not available for most robotic systems while its numerical computation is usually costly. We leverage differential flatness to transform the nonlinear system in the Brunovsky form, for which the transition matrix reduces to the exponential of a Jordan block. The resulting CG is a measure of the acquired information through the flat outputs about the flat outputs themselves and their derivatives. The inverse flatness change of coordinates is then used to come back to the original state variables, needed for computing the feedback control law. The flat outputs are parameterized through B-Splines with control points determined by actively maximizing CG. We simulate our approach on a unicycle vehicle and a planar UAV that need to estimate their configuration while measuring their distance w.r.t. two fixed markers. Simulations show the effectiveness of our methodology in reducing both the computational time and the estimation uncertainty.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10557683","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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