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34th Chinese control Conference (CCC)

作者： Chan, Gao Hua, Liu Xiao Ludong Univ Sch Math & Stat Sci Yantai 264025 Shandong Peoples R China

ISBN: (纸本)9789881563897

The paper is concerned with decentralized robust H infinity model predictive control for a class of discrete-time singular large-scale systems with external disturbance and input constraints. A synthesis method to design decentralized robust H infinity model predictive controller is proposed based on H infinity performance. By applying the Lyapunov stable theory and linear matrix inequalities(LMI) technique, the sufficient condition for the existence of the decentralized robust H infinity model predictive controller is given. On the basis of the proposed decentralized robust model predictive control approach, it can be proved that the closed-loop discrete-time singular large-scale system is stable, regular and causal. Finally, a numerical simulation is given to illustrate the proposed method.

关键词： robust model predictive control Decentralized control singular large scale systems H infinity performance

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robust model predictive kinematic tracking control with terminal region for wheeled robotic systems

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AUTOMATIKA 2021年第3-4期62卷 513-519页

作者： Phuong Nam Dao Hong Quang Nguyen Hanoi Univ Sci & Technol Hanoi Vietnam Thai Nguyen Univ Technol Thai Nguyen City 251750 Vietnam

This paper addresses the nonlinear model predictive control (MPC) for wheeled mobile robots (WMRs) under external disturbance. The decoupling technique is utilized based on the non-holonomic constraint description for separating the WMR model. This method is able to achieve the under-actuated kinematic sub-system without disturbance and fully-actuated dynamic sub-system in presence of disturbance. Thanks to the decoupling technique, the disturbance is lumped into dynamic sub-system. The novelty lies in that the MPC-based tracking control with fixed initial point guarantees the stability based on a new establishment of terminal region and equivalent terminal controller. The feasibility problem is demonstrated to lead the tracking problem using theoretical analysis. Moreover, the control structure is inserted more the robust nonlinear dynamic controller. The effectiveness and advantages of the proposed control scheme are verified by numerical simulations using Yamip tool.

关键词： robust model predictive control wheeled mobile robots terminal controller terminal region feasibility

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Wide-area damping power system control based on robust self-triggered model predictive control

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2022年 141卷

作者： Nie, Yonghui Liu, Tianyu Wang, Zhunhang Zhao, Yan Northeast Elect Power Univ Acad Adm Off Jilin 132012 Peoples R China Northeast Elect Power Univ Dept Elect Engn Jilin 132012 Peoples R China State Grid Liaoning Elect Power Supply Co Ltd Yingkou Power Supply Co Yingkou 115000 Peoples R China

Unavoidable random disturbances during the operation of large-scale interconnected power systems may undermine their stability. To prevent this problem, we propose a damping control method based on robust selftriggered model predictive control. First, we linearize the power system model and determine the controller installation location and feedback signal through geometric measurements. Subsequently, the model order is reduced by applying Schur method for balanced truncation. According to the assumed distribution and boundary range of random disturbance, the multi-cell robust predictive control minimax optimization problem described by the vertex is established. By deriving the upper bound of the maximum problem, the minimax problem is transformed into minimizing the upper bound problem to deal with the uncertain problem, which is transformed into linear matrix inequality for controller design. Finally, we introduce a self-triggered control strategy that avoids solving a constrained optimization problem at every time step. This strategy reduces the number of controller responses and resource requirements for sampling and communication, thereby improving computational efficiency. Selecting the two zone four-machine system as the test system, the simulation results demonstrate that the proposed control strategy can effectively eliminate the effect of random disturbances on the stable operation of power systems, improve the damping characteristics of power systems, and suppress lowfrequency oscillations.

关键词： Damping analysis Low-frequency oscillation robust model predictive control Self-triggered control

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robust model predictive control of a class of uncertain nonlinear systems with application to typical CSTR problems

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JOURNAL OF PROCESS control 2013年第4期23卷 493-499页

作者： Ghaffari, V. Naghavi, S. Vahid Safavi, A. A. Shiraz Univ Sch Elect & Comp Engn Shiraz Iran

This paper proposes a robust predictive control approach for additive discrete time uncertain nonlinear systems. The controller design is characterized as an optimization problem of the "worst-case" objective function over an infinite moving horizon. A sufficient state feedback synthesis condition is provided in the form of a linear matrix inequality (LMI) optimization and is solved online at each time step. A few simulation examples are exploited to illustrate the effectiveness of this method. Among them are two typical CSTR problems. (c) 2013 Elsevier Ltd. All rights reserved.

关键词： LMI robust model predictive control Uncertain nonlinear systems CSTR

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robust event-triggered model predictive control of polytopic LPV systems: An input-to-state stability approach

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SYSTEMS & control LETTERS 2022年 163卷 105202-105202页

作者： Heydari, Reza Farrokhi, Mohammad Iran Univ Sci & Technol Dept Elect & Elect Engn Tehran Iran Iran Univ Sci & Technol Ctr Excellence Modeling & Control Complex Syst Tehran Iran

This paper addresses the problem of designing robust event-triggered tube-based model predictive control (TMPC) for constrained linear parameter-varying systems. The main challenge with implementing TMPC schemes in an event-triggered setup is that the assumption of feedback for all sampling times is not satisfied, which leads to an exponential growth of the predicted sets. First, a novel modification of homothetic TMPC is introduced to consider the effect of open-loop control between triggering times. At each sampling instant, the TMPC provides the maximal feasible number of open-loop steps and a sequence of control inputs, which can be applied in an open-loop fashion while satisfying the state and control constraints. Second, depending on the maximal number of open-loop steps, the triggering condition is derived based on the input-to-state stability (ISS) concept with the aim to reduce the communication traffic between sensors, controllers and actuators. Moreover, recursive feasibility and asymptotic stability of the closed-loop system are guaranteed. Simulation results demonstrate the efficacy of the proposed scheme while reducing the frequency of the update times. (C) 2022 Elsevier B.V. All rights reserved.

关键词： Even-triggered control robust model predictive control LPV systems

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A robust least squares based approach to min-max model predictive control

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INTERNATIONAL JOURNAL OF robust AND NONLINEAR control 2020年第13期30卷 4807-4825页

作者： Jetto, L. Orsini, V. Univ Politecn Marche Dipartimento Ingn Informaz Ancona Italy

This article deals with the model predictive control (MPC) of linear, time-invariant discrete-time polytopic (LTIDP) systems. The 2-fold aim is to simplify the treatment of complex issues like stability and feasibility analysis of MPC in the presence of parametric uncertainty as well as to reduce the complexity of the relative optimization procedure. The new approach is based on a two degrees of freedom (2DOF) control scheme, where the outputr(k) of the feedforward input estimator (IE) is used as input forcing the closed-loop system n-ary sumation (f). n-ary sumation (f)is the feedback connection of an LTIDP plant n-ary sumation (p)with an LTI feedback controller n-ary sumation (g). Both cases of plants with measurable and unmeasurable state are considered. The task of n-ary sumation (g)is to guarantee the quadratic stability of n-ary sumation (f), as well as the fulfillment of hard constraints on some physical variables for any inputr(k) satisfying an "a priori" determined admissibility condition. The inputr(k) is computed by the feedforward IE through the on-line minimization of a worst-case finite-horizon quadratic cost functional and is applied to n-ary sumation (f)according to the usual receding horizon strategy. The on-line constrained optimization problem is here simplified, reducing the number of the involved constraints and decision variables. This is obtained modelingr(k) as a B-spline function, which is known to admit a parsimonious parametric representation. This allows us to reformulate the minimization of the worst-case cost functional as a box-constrained robust least squares estimation problem, which can be efficiently solved using second-order cone programming.

关键词： input parametrization min-max model predictive control reference tracking robust least squares robust model predictive control

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robust Event-Triggered model predictive control for Multiple High-Speed Trains With Switching Topologies

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2020年第5期69卷 4700-4710页

作者： Zhao, Hui Dai, Xuewu Zhang, Qi Ding, Jinliang Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China China Acad Railway Sci Corp Ltd Signal & Commun Res Inst Beijing 100081 Peoples R China

This paper presents a robust event-triggered model predictive control (MPC) strategy for multiple high-speed trains (MHSTs) with random switching topologies. Due to the complicated operation environment of high-speed railways, the communication topology of MHSTs system is time-varying and changes among a set of directed graphs, which can be characterized as a Markov chain. By adopting the concept of MPC, this paper studies the distributed cooperative leader-following consensus control for MHSTs, in which a novel event-triggered strategy is introduced to determine when information exchange among neighboring trains and control update are executed. Firstly, the leader-following consensus problem of MHSTs system is transformed to the stabilization of a Markov jump system and a sufficient condition for leader-following consensus is derived with stability analysis of the Markov jump system based on the robust event-triggered MPC scheme. Then, the robust event-triggered MPC algorithm which minimizes the objective function is proposed. By optimizing the objective function, the deviation of states and amplitude of the control force are optimized. The effectiveness of the proposed robust event-triggered MPC method on cooperative cruise control of MHSTs is illustrated by numerical examples.

关键词： robust model predictive control multiple high-speed trains (MHSTs) Markov switching topologies leader-following consensus event-triggered

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robust observer-based model predictive control of non-uniformly sampled systems

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ISA TRANSACTIONS 2020年第0期98卷 37-46页

作者： Khan, Owais Mustafa, Ghulam Khan, Abdul Qayyum Abid, Muhammad Pakistan Inst Engn & Appl Sci Dept Elect Engn Control Theory & Applicat Grp Islamabad 45650 Pakistan

This paper presents a robust model predictive control design procedure for constrained non-uniformly sampled systems subject to bounded unknown disturbances. Unlike the existing results in this area, the proposed design procedure considers arbitrary variations of the sampling period between a lower and an upper bound, and ensures asymptotic stability and performance of the closed-loop control system for all variations of the sampling period, which is a theoretically challenging task. The uncertain optimization problem associated with the constrained model predictive control turns out to be intractable due to infinity many variations of the sampling period. To overcome this challenge, the non-uniformly sampled system is modeled as a linear polytopic uncertain system based on variations in the sampling period. A quasi min-max robust model predictive control technique based on an offline state observer is used for designing an output feedback controller. A case study is given to illustrate the effectiveness of the proposed approach. (C) 2019 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Non-uniform sampling robust model predictive control Observer-based control Quasi min-max Polytopic uncertainty

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robust model predictive control Based on MRAS for Satellite Attitude control System 3

Robust Model Predictive Control Based on MRAS for Satellite ...

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3rd International Conference on control, Instrumentation, and Automation (ICCIA)

作者： Pirouzmand, Fateme Ghahramani, Nemat Ollah Sci & Res Univ Dept Control Engn Tehran Iran Malek Ashtar Univ Technol Dept Control Engn Tehran Iran

ISBN: (纸本)9781479931170

In this paper, a robust model predictive control (RMPC) is proposed based on model reference adaptive system (MRAS). In this algorithm, using the MRAS a combinational RMPC controller for three degree freedom satellite is designed such that the effect of moment of inertia uncertainty and external disturbance is compensated on the stability and performance of closed loop system. control law is a state feedback which its gain is obtained by solving a convex optimization problem subject to several linear matrix inequalities (LMIs). To avoid the actuators saturation a linear matrix inequality is incorporated as LMI in the mentioned optimization problem. The advantages of this algorithm are needless to exact information from system's model, robustness against model uncertainties and external disturbance. The proposed algorithm is implemented on the satellite attitude control system and the results of them are compared to generalized incremental model predictive control (GIPC) algorithm. The results show that the suggestive controller is more robust than the GIPC method.

关键词： robust model predictive control Linear matrix inequality model reference adaptive system Satellite attitude control system

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A new robust LW-based model predictive control for continuous-time uncertain nonlinear systems

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AUTOMATIKA 2020年第4期61卷 670-681页

作者： Luo Huofa Marrani, Hashem Imani Jiaxing Univ Sch Marxism Jiaxing Zhejiang Peoples R China Islamic Azad Univ Ardabil Branch Young Researchers & Elite Club Ardebil Iran

This paper presents a new robust predictive controller for a special class of continuous-time non-linear systems with uncertainty. These systems have bounded disturbances with unknown upper bound as well as constraints on input states. The controller is designed in the form of an optimization problem of the 'worst-case' objective function over an infinite moving horizon. Through this objective function, constraints and uncertainties can be applied explicitly on the controller design, which guarantees the system stability. Next, LMI tool is used to improve the calculation time and complexity. To do this, in order to find the optimum gain for state-feedback, the optimization problem is solved using LMI method in each time step. Finally, to show the efficiency and effectiveness of the proposed algorithm, a surge phenomenon avoidance problem in centrifugal compressors is solved.

关键词： robust model predictive control LMI surge centrifugal compressors

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