NDLI: Data-driven control based on simultaneous perturbation stochastic approximation with adaptive weighted gradient estimation

Content Provider	IET Digital Library
Author	Dong, Na Wu, Chun Ho Gao, Zhong Ke Chen, Zeng qiang Ip, Wai Hung
Abstract	This study proposes one novel data-driven control strategy based upon the simultaneous perturbation stochastic approximation method with adaptive weighted gradient estimation for general discrete non-linear systems. A function approximator is used to construct the controller, and here, it is fixed as a neural network (NN), whose structure is fixed previously, while allowing its connecting weights to be updated. The control parameters are then the connecting weights of the NN controller. The biggest advantage of this data-driven control approach is that it can generate a control signal to affect system's future performance without establishing the plant's mathematical model first. In this novel approach, to improve the control ability and accuracy, an adaptive weighted gradient estimation method is designed to do the parametric estimation with convergence analysis. Non-linear tracking problems for typical discrete-time non-linear plants are introduced for simulation comparison tests, and the convergence and feasibility of this newly proposed data-driven control strategy are well demonstrated through the simulation results. Finally, empirical study on a simulated wastewater treatment system is carried out to further illustrate the effectiveness of this newly proposed approach.
Starting Page	201
Ending Page	209
Page Count	9
ISSN	17518644
Volume Number	10
e-ISSN	17518652
Issue Number	Issue 2, Jan (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/10/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2015.0636
Journal	IET Control Theory & Applications
Publisher Date	2016-01-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Estimation Adaptive Weighted Gradient Estimation Method Convergence Convergence Analysis Data-driven Control Strategy Discrete Control System Discrete Time System Discrete-time Nonlinear Plants Function Approximation Function Approximator General Discrete Nonlinear System Gradient Method Interpolation And Function Approximation Modelling And Identification Neural Network Neurocontrol Neurocontrollers NN Controller Nonlinear Control System Nonlinear Tracking Problem Numerical Analysis Parametric Estimation Perturbation Technique Simulation Simultaneous Perturbation Stochastic Approximation Stochastic Linearised SCUC Wastewater Treatment System
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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