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作者：Muthirayan, Deepan; Kalathil, Dileep; Khargonekar, Pramod P.
作者单位：Texas A&M University System; Texas A&M University College Station
摘要：In this article, we consider the problem of finding a meta-learning online control algorithm that can learn across the tasks when faced with a sequence of N (similar) control tasks. Each task involves controlling a linear dynamical system for a finite horizon of T time steps. The cost function and system noise at each time step are adversarial and unknown to the controller before taking the control action. Meta-learning is a broad approach where the goal is to prescribe an online policy for an...
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作者：Huang, Feng; Cao, Ming; Wang, Long
作者单位：Peking University; University of Groningen
摘要：In stochastic dynamic environments, multiagent Markov decision processes have emerged as a versatile paradigm for studying sequential decision-making problems of fully cooperative multiagent systems. However, the optimality of the derived policies is usually sensitive to model parameters, which are typically unknown and required to be estimated from noisy data in practice. To investigate the sensitivity of optimal policies to these uncertain parameters, we study a robust stochastic control pro...
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作者：Zou, Lei; Wang, Zidong; Shen, Bo; Dong, Hongli
作者单位：Donghua University; Brunel University; Northeast Petroleum University
摘要：This article addresses the problem of secure recursive state estimation for a networked linear system, which may be vulnerable to interception of transmitted measurement data by eavesdroppers. To effectively protect information security, an encryption-decryption-based communication scheme can be used, but encrypting all the measurement data from sensors can result in significant computational costs. To address this issue, a partial-encryption-decryption (PED) mechanism is proposed to enhance i...
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作者：Zhang, Ruichang; Liu, Zhixin; Chen, Ge; Mei, Wenjun
作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Peking University
摘要：The Friedkin-Johnsen (FJ) model introduces prejudice into the opinion evolution and has been successfully validated in many practical scenarios; however, due to its weighted average mechanism, only one prejudiced agent can always guide all unprejudiced agents synchronizing to its prejudice under the connected influence network, which may not be in line with some social realities. To fundamentally address the limitation of the weighted average mechanism, a weighted-median opinion dynamics has b...
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作者：Mallick, Samuel; Dabiri, Azita; De Schutter, Bart
作者单位：Delft University of Technology
摘要：In this article, we present a novel approach for distributed model predictive control (MPC) for piecewise affine (PWA) systems. Existing approaches rely on solving mixed-integer optimization problems, requiring significant computation power or time. We propose a distributed MPC scheme that requires solving only convex optimization problems. The key contribution is a novel method, based on the alternating direction method of multipliers, for solving the nonconvex optimal control problem that ar...
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作者：Zhao, Shengchao; Song, Siyuan; Liu, Yongchao
作者单位：China University of Mining & Technology; The Chinese University of Hong Kong, Shenzhen; Dalian University of Technology
摘要：This article studies the distributed optimization problem over directed networks with noisy information-sharing. To resolve the imperfect communication issue over directed networks, a series of noise-robust variants of Push-Pull/AB method have been developed. These methods improve the robustness of Push-Pull method against the information-sharing noise through adding small factors on weight matrices and replacing the global gradient tracking with the cumulative gradient tracking. Based on the ...
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作者：Li, Hanfeng; Li, Min
作者单位：Shandong University; Shandong University
摘要：In this article, we propose a dynamic gain method to solve the event-triggered output feedback tracking control problem of uncertain strict-feedback nonlinear systems subject to input quantization. The nonlinear terms admit an incremental rate depending on an unknown constant and an output polynomial function. Two configurations of the event-triggered quantized controller are presented, namely, quantization after triggering and quantization before triggering. Based on the dynamic scaling trans...
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作者：Li, Kuo; Ding, Steven X.; Hua, Changchun; Li, Yafeng; Yang, Yana
作者单位：Yanshan University; University of Duisburg Essen
摘要：This article explores the distributed leader-following consensus control problem of nonlinear multiagent systems subject to stochastic output sensing noises under a fixed directed topology. Different from existing research, we pay attention to the effect of multiplicative stochastic noises on the sensors, and the noise intensity can be described as an unknown time-varying function with an arbitrarily large bound. In this condition, we put forward the noise intensity classification-based distri...
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作者：Sahan, Gokhan; Trenn, Stephan
作者单位：Izmir Institute of Technology; Izmir Institute of Technology; University of Groningen
摘要：This study addresses the deficiencies in the assumptions of the results in (Chen and Yang, 2017) due to the lack of uniformity. We first show the missing hypothesis by presenting a counterexample. Then, we prove why they are wrong in that form and show the errors in the proof of the main result of (Chen and Yang, 2017). Next, we compare the assumptions and related results of (Chen and Yang, 2017) with similar works in the literature. Lastly, we give suggestions to complement the shortcomings o...
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作者：Zhang, Cui-Hua; Li, Yu-Jia; Hua, Chang-Chun; Sun, Zong-Yao; Zhang, Ying
作者单位：Yanshan University; Qufu Normal University
摘要：This article solves the problem of prescribed-time (PT) prescribed-performance tracking for a class of nonlinear systems with nonvanishing uncertainties based on a finite-time command filter (FTCF). To deal with nonvanishing uncertainties, a novel PT stabilization criterion that incorporates an adaptive method is proposed and a compensation mechanism is established to reduce the errors caused by FTCF, where the parameter adaptive estimation error achieves asymptotically zero convergence. Based...
