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作者：Rakovic, Sasa V.; Zhang, Sixing
作者单位：Beijing Information Science & Technology University
摘要：This article revisits verification of positive invariance for polytopic sets with respect to linear dynamics. The existing necessary and sufficient conditions are applicable only to fixed candidate polytopic sets. This article derives alternative necessary and sufficient conditions for two main representations of polytopic sets. These novel necessary and sufficient conditions are derived by utilizing the Minkowski function in primal setting and the support function in dual setting. Developed r...
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作者：Wu, Guangyu; Tsiotras, Panagiotis; Lindquist, Anders
作者单位：Shanghai Jiao Tong University; University System of Georgia; Georgia Institute of Technology; University System of Georgia; Georgia Institute of Technology; Anhui University
摘要：Ensemble systems appear frequently in many engineering applications and, as a result, they have become an important research topic in control theory. These systems are best characterized by the evolution of their underlying state distribution. Despite the work to date, few results exist dealing with the problem of directly modifying (i.e., steering) the distribution of an ensemble system. In addition, in most existing results, the distribution of the states of an ensemble of discrete-time syst...
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作者：Li, Chunhui; Yu, Chengpu
作者单位：Beijing Institute of Technology; Beijing Institute of Technology; Beijing Institute of Technology
摘要：The identification of heterogeneous nonlinear networks consisting of homogeneous clusters is investigated, which is challenging due to high computational complexity and partial state observations. To improve the computational efficiency, a finite-time horizon particle-based online expectation-maximization (EM) algorithm is proposed that enables distributed identification of unknown parameters across all agents even under complex agent couplings. To overcome the limitations caused by partial st...
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作者：Mou, Shaoshuai; Liu, Ji; Morse, A. Stephen
作者单位：Purdue University System; Purdue University; State University of New York (SUNY) System; Stony Brook University; Yale University
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作者：Degner, Maximilian; Soloperto, Raffaele; Zeilinger, Melanie N.; Lygeros, John; Kohler, Johannes
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; University of Stuttgart; Swiss Federal Institutes of Technology Domain; ETH Zurich; Imperial College London
摘要：We consider the problem of optimizing the economic performance of nonlinear constrained systems subject to uncertain time-varying parameters and bounded disturbances. In particular, we propose an adaptive economic model predictive control framework that: 1) directly minimizes transient economic costs; 2) addresses parameteric uncertainty through online model adaptation; and 3) determines optimal setpoints online, and fourth, ensures robustness by using a tube-based approach. The proposed desig...
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作者：Liu, Hao; Huang, Zixin; Xu, Shengyuan; Niu, Ben; Wei, Zi-Ang
作者单位：Wuhan Institute of Technology; Nanjing University of Science & Technology; Dalian University of Technology
摘要：In this article, encrypted set-based estimation is investigated for cyber-physical systems with unknown-but-bounded noises, which permits to outsource the state estimation of privacy-sensitive data via public networks to the third-party platforms. To prevent the leakage of the key information by eavesdropping, homomorphic encryption approach is employed. First, the classic Paillier encryption is utilized to encrypt data and the effect caused by the quantization error is analyzed as well. Then,...
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作者：Ghosh, Poulomee; Bhasin, Shubhendu
作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Delhi
摘要：We propose a model reference adaptive controller (MRAC) for uncertain linear time-invariant plants with user-defined state and input constraints in the presence of unmatched bounded disturbances. Unlike popular optimization-based approaches for constrained control, such as model predictive control (MPC) and control barrier function (CBF) that solve a constrained optimization problem at each step using the system model, our approach is optimization-free and adaptive; it combines a saturated ada...
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作者：Cao, Lan; Huang, Xiucai; Lv, Maolong; Song, Yongduan
作者单位：Chongqing University; Air Force Engineering University; Lingnan University
摘要：This article presents an asymptotic tracking control framework that accommodates generalized performance specifications for a class of unknown strict-feedback nonlinear systems. The proposed method, which is approximation-free, confines transient performance within a preassigned more flexible region (rather than merely a funnel one) by employing unified performance functions (instead of monotonic functions) to facilitate the output tracking error transformation, and the underlying problem is r...
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作者：Didier, Alexandre; Zeilinger, Melanie N.
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：We propose integrating an approximation of a predictive control barrier function (PCBF) in a safety filter framework, resulting in a prediction horizon independent formulation. The PCBF is defined through the value function of an optimal control problem and ensures invariance as well as stability of a safe set within a larger domain of attraction. We provide a theoretical analysis of the proposed algorithm, establishing input-to-state stability of the safe set with respect to approximation err...
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作者：Evangelisti, Giulio; Santina, Cosimo Della; Hirche, Sandra
作者单位：Technical University of Munich; Technical University of Munich; Delft University of Technology
摘要：Designing accurate yet reliable tracking controllers with tight performance guarantees for Lagrangian systems is challenging due to nonlinear modeling uncertainties and conservative stability criteria. This article proposes a structure-preserving projector-based tracking control law for uncertain Euler-Lagrange systems using physically consistent Lagrangian-Gaussian processes (L-GPs). We leverage the uncertainty quantification of the L-GP for adaptive feedforward-feedback balancing. In particu...
