Convergence performance oriented data-driven tuning method for parameterised controller design with cases investigation

2016 ◽  
Vol 10 (12) ◽  
pp. 1322-1330 ◽  
Author(s):  
Yu Zhu ◽  
Chuxiong Hu ◽  
Yi Jiang ◽  
Haihua Mu ◽  
Kaiming Yang
Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 949
Author(s):  
Keita Hara ◽  
Masaki Inoue

In this paper, we address the data-driven modeling of a nonlinear dynamical system while incorporating a priori information. The nonlinear system is described using the Koopman operator, which is a linear operator defined on a lifted infinite-dimensional state-space. Assuming that the L2 gain of the system is known, the data-driven finite-dimensional approximation of the operator while preserving information about the gain, namely L2 gain-preserving data-driven modeling, is formulated. Then, its computationally efficient solution method is presented. An application of the modeling method to feedback controller design is also presented. Aiming for robust stabilization using data-driven control under a poor training dataset, we address the following two modeling problems: (1) Forward modeling: the data-driven modeling is applied to the operating data of a plant system to derive the plant model; (2) Backward modeling: L2 gain-preserving data-driven modeling is applied to the same data to derive an inverse model of the plant system. Then, a feedback controller composed of the plant and inverse models is created based on internal model control, and it robustly stabilizes the plant system. A design demonstration of the data-driven controller is provided using a numerical experiment.


Author(s):  
O. Tolga Altinoz

In this study, the PID tuning method (controller design scheme) is proposed for a linear quarter model of active suspension system installed on the vehicles. The PID tuning scheme is considered as a multiobjective problem which is solved by converting this multiobjective problem into single objective problem with the aid of scalarization approaches. In the study, three different scalarization approaches are used and compared to each other. These approaches are called linear scalarization (weighted sum), epsilon-constraint and Benson’s methods. The objectives of multiobjective optimization are selected from the time-domain properties of the transient response of the system which are overshoot, rise time, peak time and error (in total there are four objectives). The aim of each objective is to minimize the corresponding property of the time response of the system. First, these four objective is applied to the scalarization functions and then single objective problem is obtained. Finally, these single objective problems are solved with the aid of heuristic optimization algorithms. For this purpose, four optimization algorithms are selected, which are called Particle Swarm Optimization, Differential Evolution, Firefly, and Cultural Algorithms. In total,twelve implementations are evaluated with the same number of iterations. In this study, the aim is to compare the scalarization approaches and optimization algorithm on active suspension control problem. The performance of the corresponding cases (implementations) are numerically and graphically demonstrated on transient responses of the system.


2017 ◽  
Vol 50 (1) ◽  
pp. 10889-10894 ◽  
Author(s):  
T.D. Gupta ◽  
H. Habibullah ◽  
H.R. Pota ◽  
I.R. Petersen

2012 ◽  
Vol 531-532 ◽  
pp. 726-731
Author(s):  
Yue Hua Xiong ◽  
Chun Liang Zhang ◽  
Bai Xiang Fu

This paper focus on designing a fuzzy PID controller design about the vapor pressure of the EPE foaming machine parameters, and raise a self-tuning method of PID parameters, and use the fuzzy control toolbox of MATLAB to simulate its control system, which are compared with the simulation of conventional PID controller, the results show the design of fuzzy PID controller have high control precision, small overshoot, good dynamic performance characteristics.


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