New optimal controller tuning method for an AVR system using a simplified Ant Colony Optimization with a new constrained Nelder-Mead algorithm

被引:64
作者
Blondin, M. J. [1 ]
Sanchis, J. [2 ]
Sicard, P. [1 ]
Herrero, J. M. [2 ]
机构
[1] Univ Quebec Trois Rivieres, Dept Elect & Comp Engn, Res Grp Ind Elect, 3351 Boul Forges, Trois Rivieres, PQ, Canada
[2] Univ Politecn Valencia, Inst Univ Automot & Informat Ind, Camino Vera S-N, E-46022 Valencia, Spain
基金
加拿大自然科学与工程研究理事会;
关键词
Automatic voltage regulator; PID controller; Optimization; Nelder-Mead algorithm; Ant Colony Optimizationa; PARTICLE SWARM OPTIMIZATION; PID CONTROLLER; EVOLUTIONARY ALGORITHMS; SIMPLEX SEARCH; DESIGN;
D O I
10.1016/j.asoc.2017.10.007
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, an optimal gain tuning method for PID controllers is proposed using a novel combination of a simplified Ant Colony Optimization algorithm and Nelder-Mead method (ACO-NM) including a new procedure to constrain NM. To address Proportional-Integral-Derivative (PID) controller tuning for the Automatic Voltage Regulator (AVR) system, this paper presents a meta-analysis of the literature on PID parameter sets solving the AVR problem. The investigation confirms that the proposed ACO-NM obtains better or equivalent PID solutions and exhibits higher computational efficiency than previously published methods. The proposed ACO-NM application is extended to realistic conditions by considering robustness to AVR process parameters, control signal saturation and noisy measurements as well as tuning a two-degree-of-freedom PID controller (2DOF-PID). For this type of PID, a new objective function is also proposed to manage control signal constraints. Finally, real time control experiments confirm the performance of the proposed 2DOF-PIDs in quasi-real conditions. Furthermore, the efficiency of the algorithm is confirmed by comparing its results to other optimization algorithms and NM combinations using benchmark functions. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:216 / 229
页数:14
相关论文
共 56 条
[31]   A constrained, globalized, and bounded Nelder-Mead method for engineering optimization [J].
Luersen, MA ;
Le Riche, R ;
Guyon, F .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2004, 27 (1-2) :43-54
[32]   Optimization of process parameters through fuzzy logic and genetic algorithm - A case study in a process industry [J].
Mariajayaprakash, A. ;
Senthilvelan, T. ;
Gnanadass, R. .
APPLIED SOFT COMPUTING, 2015, 30 :94-103
[33]   Tuning and Assessment of Proportional-Integral-Derivative Controller for an Automatic Voltage Regulator System Employing Local Unimodal Sampling Algorithm [J].
Mohanty, Pradeep K. ;
Sahu, Binod K. ;
Panda, Sidhartha .
ELECTRIC POWER COMPONENTS AND SYSTEMS, 2014, 42 (09) :959-969
[34]   Autotuning Controller for Motion Control System Based on Intelligent Neural Network and Relay Feedback Approach [J].
Nguyen, Giap Hoang ;
Shin, Jin-Ho ;
Kim, Won-Ho .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2015, 20 (03) :1138-1148
[35]  
Omar B., 2014, INT C CONTROL ENG IN, P158
[36]   Optimal tuning rules for proportional-integral-derivative and fractional-order proportional-integral-derivative controllers for integral and unstable processes [J].
Padula, F. ;
Visioli, A. .
IET CONTROL THEORY AND APPLICATIONS, 2012, 6 (06) :776-786
[37]   Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization [J].
Panda, S. ;
Sahu, B. K. ;
Mohanty, P. K. .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2012, 349 (08) :2609-2625
[38]  
Pedersen M.E.H., 2003, SWARMOPS HEURISTIC O
[39]  
Peng AH, 2013, CHIN CONT DECIS CONF, P1628
[40]  
Priyambada Snigdha, 2014, 2014 9th International Conference on Industrial and Information Systems (ICIIS), P1, DOI 10.1109/ICIINFS.2014.7036595