New Criteria for Tuning PID Controllers

被引:8
作者
Polyak, B. T. [1 ,2 ]
Khlebnikov, M. V. [1 ,2 ]
机构
[1] Russian Acad Sci, Trapeznikov Inst Control Sci, Moscow 117997, Russia
[2] Moscow Inst Phys & Technol, Dolgoprudnyi 141701, Moscow Oblast, Russia
基金
俄罗斯科学基金会;
关键词
linear system; PID controller; optimization; Lyapunov equation; gradient method; convergence; LOW-ORDER CONTROLLERS; H-INFINITY; DESIGN;
D O I
10.1134/S00051179220110029
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We propose a new approach to the problem of tuning and optimizing the parameters of aPID controller based on reducing the problem to an optimization problem. In this case, theperformance of the controller is evaluated by a quadratic criterion of the system output: the PIDcontroller is tuned against the uncertainty in the initial conditions so that the system output isuniformly small; in this case, a given degree of stability of the closed-loop system is additionallyguaranteed. A gradient method for finding the PID controller parameters is given. Numerousexamples show that the recurrent procedure proposed is very efficient and leads to PID controllersthat are quite satisfactory in terms of engineering performance indices. The article continues aseries of papers by the present authors devoted to synthesizing feedback in control problems fromthe standpoint of optimization.
引用
收藏
页码:1724 / 1741
页数:18
相关论文
共 30 条
[1]  
Astrom K. J., 2006, Advanced PID Control
[2]  
Aström KJ, 2000, IFAC WORK S, P165
[3]  
Astrom KJ, 1995, PID controllers: Theory, Design and Tuning
[4]  
Bhattacharyya S., 2022, LINEAR MULTIVARIABLE, DOI [10.1017/9781108891561, DOI 10.1017/9781108891561]
[5]   Characterization of PID and lead/lag compensators satisfying given H∞ specifications [J].
Blanchini, F ;
Lepschy, A ;
Miani, S ;
Viaro, U .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2004, 49 (05) :736-740
[6]  
Bu JJ, 2019, Arxiv, DOI arXiv:1907.08921
[7]   OPTIMIZING STATIC LINEAR FEEDBACK: GRADIENT METHOD [J].
Fatkhullin, Ilyas ;
Polyak, Boris .
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2021, 59 (05) :3887-3911
[8]  
Fazel M, 2018, PR MACH LEARN RES, V80
[9]   A new heuristic optimization algorithm: Harmony search [J].
Geem, ZW ;
Kim, JH ;
Loganathan, GV .
SIMULATION, 2001, 76 (02) :60-68
[10]   Design of the low-order controllers by the H∞ criterion:: A parametric approach [J].
Gryazina, E. N. ;
Polyak, B. T. ;
Tremba, A. A. .
AUTOMATION AND REMOTE CONTROL, 2007, 68 (03) :456-466