基于CSA-SQP的预测控制器参数整定研究
PDF下载 (23131)陈 杨 1,姜文丽 2,史旭华 2,赵 均 3,徐祖华 3.基于CSA-SQP的预测控制器参数整定研究[J].宁波大学学报(理工版),2017,30(4):51-57.DOI:
CHEN Yang 1,JIANG Wen-li 2,SHI Xu-hua 2,ZHAO Jun 3,XU Zu-hua 3.Tuning parameters for model predictive controller based on CSA-SQP[J].Journal of Ningbo University(Natural Science & Engineering Edition),2017,30(4):51-57.DOI:
| Title: | Tuning parameters for model predictive controller based on CSA-SQP |
| 作者: | 陈 杨 1, 姜文丽 2, 史旭华 2, 赵 均 3, 徐祖华 3 |
| Author(s): | CHEN Yang 1, JIANG Wen-li 2, SHI Xu-hua 2, ZHAO Jun 3, XU Zu-hua 3 |
| 关键词: | 模型预测控制; 克隆选择算法; 序列二次规划; 事件触发; 抗体 |
| Keywords: | model-predictive control; clonal selection algorithm; sequential quadratic programming; events trigger; antibody |
| 分类号: | TP273 |
| 文献标识码: | A |
| 摘要: | 针对预测控制器参数整定困难, 提出了一种基于克隆选择和序列二次规划的预测控制器参数整定算法, 建立了一个基于免疫原理和序列二次规划算法进行控制器参数整定的机制, 并给出了参数整定问题中的抗原、抗体及亲和力的定义. 在此基础上, 针对系统的不确定性干扰, 构造了基于事件触发的参数调整框架. 最后, 将算法应用于仿真实验, 通过与设定值控制结果的对比, 证明所提出的预测控制器参数整定方法是有效的. |
| Abstract: | A hybrid algorithm is presented to solve the difficulty of tuning the parameters of a model predictive controller (MPC). The algorithm is based on both the immune clonal selection algorithm and sequential quadratic programming. Antibodies, antigens, and affinity are also defined. The framework of tuning parameters based on events trigger is introduced in case of uncertain disturbance. Finally, the simulation is conducted using the presented algorithm. Comparison with the results of set point control indicates that the proposed method is more efficient than other tuning methods and can be used to solve the problems with the predictive controller parameter tuning. |
| 参考文献 /References: | [1] 席裕庚, 李德伟, 林姝. 模型预测控制–―现状与挑战[J]. 自动化学报, 2013(3):222-236. [2] GARRIGA J L, SOROUSH M. Model predictive control tuning methods: A review[J]. Industrial & Engineering Chemistry Research, 2010, 49(8):3505-3515. [3] SALSBURY T, MHASKAR P, QIN S J. Predictive control methods to improve energy efficiency and reduce demand in buildings[J]. Computers and Chemical Engineering, 2013, 51(13):77-85. [4] CAMACHO E F, ALBA C B. Model predictive control [M]. New York: Springer Science & Business Media, 2013:1-13. [5] MORARI M, BARI?C M. Recent developments in the control of constrained hybrid systems[J]. Computers and Chemical Engineering, 2006, 30(10/12):1619-1631. [6] WANG J H, GAO X W. Design of multivariable PID controller of electroslag remelting process based on improved shuffled frog leaping algorithm[J]. Control and Decision, 2011, 26(11):1731-1734. [7] LI C J, GUO Y N, ZHANG Y H. Parameter tuning for the attitude control algorithm of wheel controlled spacecraft based on time and frequency domain analysis[J]. Journal of Astronautics, 2011, 32(11):3319-3322. [8] HAO Q, GUAN L W, WANG L P. GA-based control parameter tuning of parallel machine tool motor servo systems[J]. Journal of Tsinghua University (Sci & Tech), 2010, 50(11):1081-1086. [9] CHEN X S, YANG Y M. A novel adaptive PID controller based on actor-critic learning[J]. Control Theory & Applications, 2011, 28(8):1187-1192. [10] CHU J Z, DU B. Performance analysis and online fuzzy self-tuning of RTD-a controller’s parameters[J]. Journal of Shanghai Jiaotong University, 2011, 45(8):1167-1170. [11] WANG W B, FENG Q Y, LIU D. Synthesis of thinned linear and planar antenna arrays using binary PSO algorithm[J]. Progress in Electromagnetics Research, 2012, 127:371-387. [12] TAO X M, LIU F R, LIU Y, et al. Clone selection optimization algorithm with directional multi-scale mutation[J]. Control and Decision, 2011, 26(2):175-181. [13] MOLLA-ALIZADEH-ZAVARDEHI S, HAJIAGHAEI- KESHTELI M, TAVAKKOLI-MOGHADDAM R. Solving a capacitated fixed-charge transportation problem by artificial immune and genetic algorithms with a prüfer number representation[J]. Expert Systems with Applications, 2011, 38(8):10462-10474. [14] AYDIN I, KARAKOSE M, AKIN E. A multi-objective artificial immune algorithm for parameter optimization in support vector machine[J]. Applied Soft Computing, 2011, 11(1):120-129. [15] LIU H Q. Semisupervised immune clone selection graph partition algorithm[J]. Computer and Applications, 2014, 50(22):11-16. [16] ZHANG D N, LIU Y. Reentry trajectorty optimization based on an improved genetic algorithm and sequential quadratic programming[J]. Journal of Zhejiang University (Engineering Science), 2014, 48(1):161-167. [17] LUO J. The Sequential Quadratic Programming (SQP) algorithm and applying to pursuit-evasion of the spacecraft[D]. Harbin: Harbin Institute of Technology, 2012. [18] ZHAO F F. Improved clonal selection algorithm and its application in parameters tuning of controller[D]. Changsha: Hunan University, 2013. [19] DE CASTRO L N, VON ZUBEN F J. Leaning and optimization using the clonal selection principle[J]. IEEE Transaction on Evolution Computation, 2002, 6(3):239-251. [20] DE CASTRO L N, VON ZUBEN F J. The clonal selection algorithm with engineering applications[EB/OL]. [2016-01-10]. http://www.dca.fee.unicamp.br/~vonzuben/research/lnunes_dout/artigos/gecco00.pdf. [21] XU Y, ZHANG G H, QIAN F. New clonal selection algorithm application in kinetic parameter estimation[J]. Computers and Applied Chemistry, 2008, 10:1175-1179. [22] 龚固丰, 章兢, 王炼红. 基于克隆选择的免疫预测控制方法[J]. 湖南大学学报(自然科学版), 2008, 35(6):36-40. [23] 徐祖华, 赵均, 钱积新. 基于Min-Max的预测控制鲁棒参数设计[J]. 化工学报, 2004(4):613-617. [24] 陈杨, 邵之江, 游江洪, 等. 一类非线性系统的变负荷预测控制[J]. 化工学报, 2011(8):2253-2257. |
| 备注/Memo: | 收稿日期: 2016－03－12. 宁波大学学报（理工版）网址: http://journallg.nbu.edu.cn/ 基金项目: 国家自然科学基金（61273146）; 工业控制国家重点实验室项目（ICT1237）; 浙江省自然科学基金（LY14F030004）;“十二五”浙江省高校重点学科计划（20121114）. 第一作者: 陈杨（1977－）, 女, 湖南岳阳人, 博士/讲师, 主要研究方向: 预测控制. E-mail: chenyang@nbu.edu.cn 宁波大学学报（理工版）网址：http://journallg.nbu.edu.cn/ |
