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Tuning of PID controllers Using Reinforcement Learning for nonlinear system control

PROCESSES 2025年第3期13卷 735-735页

作者： Bujgoi, Gheorghe Sendrescu, Dorin Univ Craiova Dept Automat Control & Elect Craiova 200585 Romania

This paper presents the application of reinforcement learning algorithms in the tuning of PID controllers for the control of some classes of continuous nonlinear systems. Tuning the parameters of the PID controllers is performed with the help of the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which presents a series of advantages compared to other similar methods from machine learning dedicated to continuous state and action spaces. The TD3 algorithm is an off-policy actor-critic-based method and is used as it does not require a system model. Double Q-learning, delayed policy updates and target policy smoothing make TD3 robust against overestimation, increase its stability, and improve its exploration. These enhancements make TD3 one of the state-of-the-art algorithms for continuous control tasks. The presented technique is applied for the control of a biotechnological system that has strongly nonlinear dynamics. The proposed tuning method is compared to the classical tuning methods of PID controllers. The performance of the tuning method based on the TD3 algorithm is demonstrated through a simulation, illustrating the effectiveness of the proposed methodology.

关键词： learning-based control nonlinear system control PID controller bioprocess

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Enlarging nonlinear Discrete system's Domain of Attraction Via Linear control Law 5

Enlarging Nonlinear Discrete System's Domain of Attraction V...

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5th IEEE International Conference on Advanced systems and Emergent Technologies (IC_ASET)

作者： Bedoui, Sabrine Bacha, Anis Belhadj Brahim Elloumi, Salwa Braiek, Naceur Benhadj Univ Carthage Ecole Natl Ingenieurs Carthage Carthage Tunisia Univ Sousse Ecole Natl Ingenieurs Sousse Sousse Tunisia Univ Carthage Ecole Polytechn Tunisie Carthage Tunisia

ISBN: (纸本)9781665427357

This paper investigates the problem of designing controllers to enlarge the stability domain of polynomial discrete systems. In order to deal with this problem, we propose a method for computing a linear feedback control law, which extends the largest estimate of the stability domain. The designing of the control law is established in the form of an optimization problem that focuses on expanding the stability domain. An application example is presented to illustrate the efficiency of the proposed controller law for maximizing stability domain. The simulation results prove clearly the capability of our linear controller approach to increase the radium of the stability domain for the studied nonlinear system.

关键词： nonlinear system control domain of attraction feedback controller optimization problem

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A sensorless control system of permanent magnet synchronous motor based on observation error threshold EKF

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND control 2025年第9期47卷 1835-1848页

作者： Ruan, Guanqiang Su, Yuhan Yang, Kuo Cao, Jinliang Su, Yiyu Gong, Zhengda Hu, Xing Shanghai Dianji Univ Automot Struct & Energy Storage Engn Ctr Sch Mech Engn Shanghai 201306 Peoples R China Shanghai Aowei Technol Dev Co Ltd Shanghai Peoples R China

The control of nonlinear system of permanent magnet synchronous motor (PMSM) can be realized using extended Kalman filter (EKF). However, the traditional EKF algorithm has limited tracking accuracy and is prone to accumulated error. In addition, the existing improved EKF algorithm pursues the adaptability to nonlinear system, which is susceptible to noise interference and overfitting. For this reason, this paper proposes an observation error threshold EKF (OET-EKF) algorithm from the perspective of error reduction. On the basis of the traditional EKF, a threshold is set for the error between the estimated observation and the actual observation of the rotational speed. In addition, the traditional EKF algorithm is corrected by the threshold, which improves the robustness. In this paper, MATLAB/Simulink simulation is used to verify the robustness of the OET-EKF algorithm. In addition, it is found that the anti-interference ability of the system under a certain value of white noise is better than the traditional EKF algorithm.

关键词： Extended Kalman filtering observation error threshold EKF nonlinear system control

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A Trust-Region Method for Data-Driven Iterative Learning control of nonlinear systems

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IEEE control systemS LETTERS 2024年 8卷 1847-1852页

作者： Wang, Jia Hemelhof, Leander Markovsky, Ivan Patrinos, Panagiotis Katholieke Univ Leuven Dept Elect Engn ESAT STADIUS B-3001 Leuven Belgium Gran Capita Int Ctr Numer Methods Engn Barcelona 08034 Spain Catalan Inst Res & Adv Studies Barcelona 08010 Spain

This letter employs a derivative-free trust-region method to solve the norm-optimal iterative learning control problem for nonlinear systems with unknown dynamics. The iteration process is composed by two kinds of trials: main and additional trials. The tracking error is reduced in each main trial, and the additional trials explore the nonlinear dynamics around the main trial input. Then the trust-region subproblem is constructed based on the additional trial data, and solved to generate the next main trial input. The convergence of the tracking error is proved under mild assumptions. Our method is illustrated in simulations https://***/JiaaaWang/TRILC.

关键词： Polynomials Interpolation Vectors Jacobian matrices Trajectory Process control Periodic structures Data-driven control iterative learning control nonlinear system control derivative-free optimization

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Spline adaptive inverse control scheme with filtered error feedback

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nonlinear DYNAMICS 2021年第3期106卷 2309-2328页

作者： Yang, Liangdong Liu, Jinxin Zhang, Qian Yan, Ruqiang Chen, Xuefeng Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710054 Peoples R China

This paper presents a new scheme for the control of unknown block-oriented nonlinear systems using spline adaptive filter (SAF). The principle of adaptive inverse control (AIC) is utilized as the control structure in this scheme. First, the mathematical model of the unknown controlled plant was established through SAF, which consists of a linear FIR filter and a nonlinear spline interpolation function. The controller is obtained by adaptively establishing the inverse model of linear FIR filter and nonlinear spline function, respectively. In this process, a shift form DCT-LMS with variable learning rate (VL-DCTS-LMS) algorithm is proposed in order to adapt the inverse of FIR filter, and a modified Newton-Raphson method is used for directly calculating the inverse of spline interpolation function. Considering the steady-state error resulted by the plant modeling inaccuracy, filtered error feedback is introduced into the plant input in order to eliminate the control error. The effectiveness of the proposed control scheme is verified by several numerical examples, including some additional discussions and a comparison with other control methods.

关键词： Adaptive inverse control Block-oriented system nonlinear system control Spline adaptive filter

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Superheated Steam Temperature control Optimization Using Outsourced LABVIEW DMC controller 39

Superheated Steam Temperature Control Optimization Using Out...

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39th Chinese control Conference (CCC)

作者： Yuan Xiaolei Yin Zhe Yang Chunlai Li Jianfeng Feng Xuyang Ren Sulong Yuan Hongbo Hebei Elect Power Res Inst Instrumentat & Control Shijiazhuang 050021 Hebei Peoples R China UIUC Grainger Coll Engn Urbana IL 61801 USA

ISBN: (数字)9789881563903

ISBN: (纸本)9789881563903

Superheated steam temperature control is essential to improve lifetime efficiency of thermal power generators. in this paper, the superheated steam temperature control was outsourced from DCS (distributed control system) to LABVIEW based DMC (dynamic matrix control) controller (an industrial WINDOWS computer). The DMC controller communicated with DCS to realize real-time data exchange using MODBUS TCP protocol, and LABVIEW was used to programme the DMC algorithm. A 'tracing- switching -monitoring' mechanism ensured the safe operation of the whole control system. The control scheme was implemented on a 300MW unit and plant test run was carried out, results showed that DMC control outran cascaded PID control in respect of dynamic characteristics and regulation time. The outsourced DMC control scheme was proven to he effective,safe and reliable.

关键词： DMC Thermal Power Plant Automation nonlinear system control

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A Robust Method for Dual Faceted Linearization 21st

A Robust Method for Dual Faceted Linearization

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21st IFAC World Congress on Automatic control - Meeting Societal Challenges

作者： Igarashi, Yusuke Yamakita, Masaki Ng, Jerry Asada, H. Harry Tokyo Inst Technol Dept Syst & Control Engn Tokyo Japan MIT Dept Mech Engn Cambridge MA 02139 USA

The dynamics of nonlinear systems become linear systems when lifted to higher or infinite dimensional spaces. We call such linear system representations and approximations, 'lifting linear' representations. The lifting linear representations are linear system representations that are closer to the original systems than Taylor series approximations. Once we have such a linear system representation, we can apply linear control theory to the nonlinear systems. In Model Predictive control (MPC), the computation time is reduced because the nonlinear optimization problem becomes a convex quadratic optimization problem. In this paper, we propose a method to make Dual Faceted Linearization (DFL) robust for uncertainties of the plants. It will be shown that the proposed method can yield a lifting linearization leading to better control results for MPC by numerical examples. Copyright (C) 2020 The Authors.

关键词： Lifting Linearization Model Predictive control(MPC) nonlinear system control Robustification Optimal control

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Asymptotic Stabilization of Nonholonomic Four-Wheeled Vehicle with Steering Limitation

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2019年第1期E102A卷 227-234页

作者： Hashimoto, Wataru Yamashita, Yuh Kobayashi, Koichi Hokkaido Univ Grad Sch Informat Sci & Technol Sapporo Hokkaido 0600814 Japan

In this paper, we propose a new asymptotically stabilizing control law for a four-wheeled vehicle with a steering limitation. We adopt a locally semiconcave control Lyapunov function (LS-CLF) for the system. To overcome the nonconvexity of the input-constraint set, we utilize a saturation function and a signum function in the control law. The signum function makes the vehicle velocity nonzero except at the origin so that the angular velocity can be manipulated within the input constraint. However, the signum function may cause a chattering phenomenon at certain points of the state far from the origin. Thus, we integrate a lazy-switching mechanism for the vehicle velocity into the control law. The mechanism makes a sign of the vehicle velocity maintain, and the new control input also decreases the value of the LS-CLF. We confirm the effectiveness of our method by a computer simulation and experiments.

关键词： nonlinear system control Lyapunov function mobile robot steering limitation

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A Robust Method for Dual Faceted Linearization

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IFAC-PapersOnLine 2020年第2期53卷 6095-6100页

作者： Yusuke Igarashi Masaki Yamakita Jerry Ng H. Harry Asada Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan Department of Mechanical Engineering Massachusetts Institute of Technology Massachusetts USA

The dynamics of nonlinear systems become linear systems when lifted to higher or infinite dimensional spaces. We call such linear system representations and approximations, ‘lifting linear’ representations. The lifting linear representations are linear system representations that are closer to the original systems than Taylor series approximations. Once we have such a linear system representation, we can apply linear control theory to the nonlinear systems. In Model Predictive control (MPC), the computation time is reduced because the nonlinear optimization problem becomes a convex quadratic optimization problem. In this paper, we propose a method to make Dual Faceted Linearization (DFL) robust for uncertainties of the plants. It will be shown that the proposed method can yield a lifting linearization leading to better control results for MPC by numerical examples.

关键词： Lifting Linearization Model Predictive control(MPC) nonlinear system control Robustification Optimal control

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Projected Gradient and Model Predictive control : Optimal Energy and Pollutants Management for Hybrid Electric Vehicle 9th

Projected Gradient and Model Predictive Control : Optimal En...

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9th IFAC International Symposium on Advances in Automotive control (AAC)

作者： Kuchly, Jean Nelson-Gruel, Dominique Charlet, Alain Chamaillard, Yann Nouillant, Cedric Univ Orleans Lab PRISME Orleans France PSA Peugeot Citroen Rueil Malmaison France

This article aims to propose a real-time compatible strategy for the energy management of a compression-ignition Hybrid Electric Vehicle (HEV), under pollutants emissions constraints. First, an offline method is applied in order to obtain a performance reference. Then, an online-oriented approach based on Model Predictive control (MPC) is described, and a projected gradient algorithm used to solve the successive optimal control problems is explicitly presented. Both approaches are compared through simulation and the results are validated through experimentation. (C) 2019, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： nonlinear system control Numerical Optimization Model Predictive control Dynamic Programming Hybrid Electric Vehicle Pollutants management Energy management

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