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Adaptive Pseudo Inverse control for a Class of Nonlinear Asymmetric and Saturated Nonlinear Hysteretic systems

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IEEE/CAA Journal of Automatica Sinica 2021年第4期8卷 916-928页

作者： Xiuyu Zhang Ruijing Jing Zhiwei Li Zhi Li Xinkai Chen Chun-Yi Su School of Automation Engineering Northeast Electric Power Universityand also with Jilin Province International Research Center of Precision Drive and Intelligent ControlJilin 132012China State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China Department of Electronic and Information Systems Shibaura Institute of TechnologySaitama 337-8570Japan Department of Mechanical and Industrial Engineering Concordia UniversityQCMontreal H3B 1R6Canada

This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control(DSC)***"pseudo inverse"means that an on-line calculation mechanism of approximate control signal is developed by applying a searching method to the designed temporary control signal where the true control signal is *** main contributions are summarized as:1)to our best knowledge,it is the first time to compensate the asymmetric and saturated hysteresis by using hysteresis pseudo inverse compensator because the construction of the true saturated-type hysteresis inverse model is very difficult;2)by designing the saturated-type hysteresis pseudo inverse compensator,the construction of true explicit hysteresis inverse and the identifications of its corresponding unknown parameters are not required when dealing with the saturated-type hysteresis;3)by combining DSC technique with the tracking error transformed function,the"explosion of complexity"problem in backstepping method is overcome and the prespecified tracking performance is *** of stability and experimental results on the hardware-inloop platform illustrate the effectiveness of the proposed adaptive pseudo inverse control scheme.

关键词： Adaptive dynamic surface control adaptive pseudo inverse control asymmetric and saturated hysteresis robust control

Nonlinear Cooperative Output Regulation with Input Delay Compensation

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arXiv 2024年

作者： Zheng, Shiqi Ahn, Choon Ki Jiang, Xiaowei Yan, Huaicheng Shi, Peng The School of Automation China University of Geosciences Wuhan430079 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China The Shaoyang Institute of Advanced Manufacturing Technology Shaoyang422000 China The School of Electrical Engineering Korea University Seoul136-701 Korea Republic of The Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education East China University of Science and Technology Shanghai200237 China The School of Electrical and Mechanical Engineering The University of Adelaide AdelaideSA5005 Australia

This paper investigates the cooperative output regulation (COR) of nonlinear multi-agent systems (MASs) with long input delay based on periodic event-triggered mechanism. Compared with other mechanisms, periodic event-triggered control can automatically guarantee a Zeno-free behavior and avoid the continuous monitoring of triggered conditions. First, a new periodic event-triggered distributed observer, which is based on the fully asynchronous communication data, is proposed to estimate the leader information. Second, a new distributed predictor feedback control method is proposed for the considered nonlinear MASs with input delay. By coordinate transformation, the MASs are mapped into new coupled ODE-PDE target systems with some disturbance-like terms. Then, we show that the COR problem is solvable. At last, to further save the communication resource, a periodic event-triggered mechanism is considered in the sensor-to-controller transmission in every agent. A new periodic event-triggered filter is proposed to deal with the periodic event-triggered feedback data. The MASs with input delay are mapped into coupled ODE-PDE target systems with sampled data information. Then, Lyapunov-Krasovskii functions are constructed to demonstrate the exponential stability of the MASs. Simulations verify the validity of the proposed results. © 2024, CC BY-NC-ND.

关键词： Feedback control

Distributed Online Convex Optimization with Adversarial Constraints: Reduced Cumulative Constraint Violation Bounds under Slater’s Condition

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arXiv 2023年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Hong, Yiguang Chai, Tianyou Johansson, Karl H. Lab for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online convex optimization with adversarial constraints. In this setting, a network of agents makes decisions at each round, and then only a portion of the loss function and a coordinate block of the constraint function are privately revealed to each agent. The loss and constraint functions are convex and can vary arbitrarily across rounds. The agents collaborate to minimize network regret and cumulative constraint violation. A novel distributed online algorithm is proposed and it achieves an O(T max{c,1−c}) network regret bound and an O(T 1−c/2) network cumulative constraint violation bound, where T is the number of rounds and c ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints), the network cumulative constraint violation bound is reduced to O(T 1−c). Moreover, if the loss functions are strongly convex, then the network regret bound is reduced to O(log(T)), and the network cumulative constraint violation bound is reduced to O(√log(T)T) and O(log(T)) without and with Slater’s condition, respectively. To the best of our knowledge, this paper is the first to achieve reduced (network) cumulative constraint violation bounds for (distributed) online convex optimization with adversarial constraints under Slater’s condition. Finally, the theoretical results are verified through numerical simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： Economic and social effects

Numerical Investigation of Localized Surface Plasmon Resonance (LSPR) based Sensor for Glucose Level Monitoring

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Numerical Investigation of Localized Surface Plasmon Resonan...

First International Symposium on Instrumentation, control, Artificial Intelligence, and Robotics (ICA-SYMP)

作者： Kawintida Santavanond Charusluk Viphavakit Wisarn Patchoo Hala El-Khozondar Waleed Mohammed Faculty of Engineering International School of Engineering Chulalongkorn University Bangkok Thailand Faculty of Engineering International School of Engineering Intelligent Control Automation of Process Systems Research Unit Chulalongkorn University Bangkok Thailand The Bangkok University Center of Research in Optoelectronics Communications and Computational Systems School of Engineering Bangkok University Pathumthani Thailand Islamic University of Gaza Gaza Palestine The Bangkok University Center of Research in Optoelectronics Communications and Computational Systems School of Engineering Bangkok University Pathumthani Thailand

ISBN: (数字)9781728187600

ISBN: (纸本)9781728187617

This study aims to apply Localized Surface Plasmon Resonance (LSPR), Maxwell Garnett's formula, and Fabry-Perot theory together to design and develop a LSPR enhanced gold colloidal nanoparticles (AuNPs) sensor to be used in biomedical applications such as detection of glucose level in urine for early stage screening of diabetic patients. In this work, the LSPR based sensor has been designed and studied numerically to detect the glucose level from the change in the effective index resulting in a red shift of the absorption peak. The sensors were designed to have various sizes of the gold nanoparticles in a range between 20 nm and 100 nm by having different molar ratio with Trisodium Citrate (TSC) which acts as stabilizer in the synthesis. The maximum possible sensitivity of the sensor can be achieved with 70 nm diameter of gold nanoparticles at 0.2 volume fraction of AuNP to glucose solution.

关键词： Nanoparticles Gold Sensitivity Robot sensing systems Glucose Optical sensors Surface plasmons

Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization

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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Digital Futures Stockholm10044 Sweden The Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions. At each round, each agent selects a decision from the decision set, and then only a portion of the loss function and a coordinate block of the constraint function at this round are privately revealed to this agent. The goal of the network is to minimize the network-wide loss accumulated over time. Two distributed online algorithms with full-information and bandit feedback are proposed. Both dynamic and static network regret bounds are analyzed for the proposed algorithms, and network cumulative constraint violation is used to measure constraint violation, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. In particular, we show that the proposed algorithms achieve O(T max{κ,1-κ}) static network regret and O(T 1-κ/2) network cumulative constraint violation, where T is the time horizon and κ ∈ (0, 1) is a user-defined trade-off parameter. Moreover, if the loss functions are strongly convex, then the static network regret bound can be reduced to O(T κ). Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Economic and social effects

Regret and cumulative constraint violation analysis for online convex optimization with long term constraints

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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Institute for Advanced Study Tongji University Shanghai China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

This paper considers online convex optimization with long term constraints, where constraints can be violated in intermediate rounds, but need to be satisfied in the long run. The cumulative constraint violation is used as the metric to measure constraint violations, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. A novel algorithm is first proposed and it achieves an O(Tmax{c,1-c}) bound for static regret and an O(T (1-c)/2) bound for cumulative constraint violation, where c ϵ (0, 1) is a user-defined trade-off parameter, and thus has improved performance compared with existing results. Both static regret and cumulative constraint violation bounds are reduced to O(log(T )) when the loss functions are strongly convex, which also improves existing results. In order to achieve the optimal regret with respect to any comparator sequence, another algorithm is then proposed and it achieves the optimal O( p T (1 + PT )) regret and an O(√T) cumulative constraint violation, where PT is the path-length of the comparator sequence. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Comparators (optical)

Supervisory Robust Model Predictive control for Linear systems Subject to Parametric Uncertainty and Application to Level control process

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Supervisory Robust Model Predictive Control for Linear Syste...

International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Pongsorn Keadtipod David Banjerdpongchai Dept. of Electrical Engineering Chulalongkorn University Intelligent Control Automation of Process Systems (iCAPS) Research Unit Bangkok Thailand

ISBN: (纸本)9781538635568;9781538635551

This paper presents supervisory robust model predictive control (RMPC) for linear systems in the presence of parametric uncertainty. The control structure is cascade control where the outer loop controller is RMPC and the inner loop controller as proportional-integral (PI) controller. The parametric uncertainty appears in the dynamic matrix and input matrix and satisfies norm-bounded condition. First, we derive inner closed-loop model and use this model to design RMPC. The design of RMPC involves a min-max optimization problem which aims to find the optimal solution minimizing the worst case performance. We derive an upper bound of the worst case performance and apply Linear Matrix Inequality to determine the control input. We conduct the step tests on the level control loop and obtain 4 dynamic models. Numerical results reveal that supervisory RMPC can ensure reference tracking regardless of uncertain dynamics.

关键词： process control Uncertainty Level control Computational modeling Linear systems Telecommunications Information technology

Design of Output Feedback Nonlinear Model Predictive control for Inverted Pendulum on Cart

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Design of Output Feedback Nonlinear Model Predictive Control...

International Conference on control, automation and systems

作者： Petchakrit Pinyopawasutthi David Banjerdpongchai Yasuaki Oishi Intelligent Control Automation of Process Systems (iCAPS) Research Unit Department of Electrical Engineering Chulalongkorn University 254 Phayathai Road Pathumwan Bangkok Thailand Department of Mechatronics Nazan University Yamazatocho 18 Showa-ku Nagoya Japan

ISBN: (纸本)9781538670804;9788993215168

This paper presents designing of output feedback nonlinear model predictive control (NMPC) for nonlinear systems. NMPC employs the state feedback and updates the control input at each sampling step. The control design of NMPC is formulated as optimal control which requires the information of states of the process. However, in practice, we can measure only some states of the process. This paper aims to use the state observer to estimate the unknown states and use them as feedback for NMPC. We apply output feedback NMPC to inverted pendulum on cart. Numerical results show the response of output feedback NMPC asymptotically converges to that of state feedback NMPC.

关键词： Optimal control Nonlinear systems Nonlinear model predictive control State observer Inverted pendulum on cart

Robust Decentralized control of Interconnected Nonlinear systems Subject to Uncertainties and Disturbances via Generalized Extended State Observers 34

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Robust Decentralized Control of Interconnected Nonlinear Sys...

第三十四届中国控制会议

作者： ZHANG Chuanlin YANG ning HE Shuaipeng JIA Ruting Shanghai Engineering Research Center of Intelligent Management and Control for Power Process College of Automation EngineeringShanghai University of Electric Power Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Electrical and Computer Engineering Department California State University

ISBN: (纸本)9789881563897

This paper studies the problem of robust decentralized control for a class of large-scale interconnected systems subject to uncertainties and disturbances via a generalized active disturbance rejection control method. First, a novel extended state observer(ESO) is constructed separately for each subsystem with less dependence of the precise system information and structure. Second, an explicit formula of the decentralized active disturbance rejection control(DADRC) law is presented by utilizing the output feedback domination approach. It is shown that by a delicate analysis procedure, the closed-loop system can be rendered semi-globally asymptotically stable only using decentralized output feedback anti-disturbance controller. Numerical simulations show the efficiency of the proposed method.

关键词： output feedback control global stabilization disturbance rejection control extended state observer