Research on improved active disturbance rejection control of continuous rotary motor electro-hydraulic servo system

Abstract

In order to meet the precision requirements and tracking performance of the continuous rotary motor electro-hydraulic servo system under unknown strong non-linear and uncertain strong disturbance factors, such as dynamic uncertainty and parameter perturbation, an improved active disturbance rejection control (ADRC) strategy was proposed. The state space model of the fifth order closed-loop system was established based on the principle of valve-controlled hydraulic motor. Then the three parts of ADRC were improved by parameter perturbation and external disturbance; the fast tracking differentiator was introduced into linear and non-linear combinations; the nonlinear state error feedback was proposed using synovial control; the extended state observer was determined by nonlinear compensation. In addition, the grey wolf algorithm was used to set the parameters of the three parts. The simulation and experimental results show that the improved ADRC can realize the system frequency 12 Hz when the tracking accuracy and response speed meet the requirements of double ten indexes, which lay foundation for the motor application.

Keywords

continuous rotary electro-hydraulic servo motor / active disturbance rejection control (ADRC) / fast tracking differentiator (TD) / non-linear state error feedback (NLSEF) / extended state observer (ESO) / grey wolf algorithm

References

[1] WangX-j, LiuM-z, ChenS, LiSong. Predictive function and sliding model controller of continuous rotary electro-hydraulic servo motor applied to simulator [J]. Journal of Jilin University (Engineering and Technology Edition), 2019, 49(5): 1547-1557

[2] YuanL-p, CuiS-m, LuH-y, LiS-yi. Research on low speed performance of electro-hydraulic servomotor based on improved simulated annealing genetic algorithm [J]. Journal of Shanghai Jiao Tong University, 2010, 44(12): 1741-1746

[3] CaoJ, MaY-h, WuX-feng. Application of QFT in continuous rotary electro-hydraulic servo motor [J]. Journal of Harbin Institute of Technology, 2009, 41(11): 69-72

[4] YuanL-peng. Structure optimization for improving low speed performance of continuous rotary electro-hydraulic servomotor based on the improved genetic algorithm [J]. Journal of Mechanical Engineering, 2010, 46(12): 166-174

[5] LiM-zhao. Simulation Analysis of Disturbance suppression by ADRC [J]. Scientific and Technological Innovation, 20194748

[6] LiM-zhao. Simulation analysis of active disturbance rejection control technology based on simulink [J]. China Computer & Communication, 2019167168

[7] ZhaoZ-liangActive disturbance rejection control technology and theoretical analysis [M], 2019, Beijing, Science Press

[8] MaZ, LiuP, WangJ-long. Simulation study on classical RLC system based on active disturbance rejection control [J]. Journal of Tangshan University, 2019, 32(6): 5-8

[9] TianG, GaoZ-qiang. Frequency response analysis of active disturbance rejection based control system [C]. Proceedings of the 16th IEEE International Conference on Control, Applications Part of IEEE Multi-conference on Systems and Control, 2007, Singapore, IEEE, 15951599

[10] XiaY-q, FuM-y, DengZ-h, RenXuemei. Recent developments in sliding mode control and active disturbance rejection control [J]. Control Theory & Applications, 2013, 30(2): 137-147

[11] ShenW, CuiXia. Study on hydraulic motor speed servo system controlled by proportional servo valves with active disturbance rejection controller [J]. Computer Simulation, 2016, 33(8): 317-321

[12] MaS-j, SunM-w, ChenZ-qiang. Interactive ADRC design for flight attitude control [C]. Proceedings of 2017 IEEE 6th Data Driven Control and Learning Systems Conference(DDCLS’17). IEEE Beijing Section, 2017, Beijing, IEEE Industrial Electronics Society

[13] ZhangX-d, YinD-yi. Simulation study of active disturbance rejection controller for high order systems [J]. Aerospace Control, 2018, 36(1): 3-7

[14] ChenZ-q, LiuJ-j, SunM-wei. Overview of a novel control method: active disturbance rejection control technology and its practical applications [J]. CAAI Transactions on Intelligent Systems, 2018, 13(6): 865-877

[15] FuC-f, TanWen. Parameters tuning of linear active disturbance rejection control based on high order controller design [J]. Control Theory & Applications, 2017, 34(2): 265-272

[16] GuoB-z, ZhaoZ-liang. Active disturbance rejection control: Theoretical perspectives [J]. Communications in Information and Systems, 2015, 15(3): 361-421

[17] ZhangH, ZhengJ-qiang. Study on the design method of an active disturbance rejection optimal controller [J]. Control Engineering, 2018, 25(12): 2219-2223

[18] ZhangM, YuJ, PangQ-w, ZhaoM-lin. Research on auto disturbance rejection parameter tuning based on multi target moth optimization algorithm [J]. Microelectronics & Computer, 2018, 35(11): 84-88

[19] LiuC-f, ZangBin. Application and the parameter tuning of ADRC based on CPSO [C]. Proceedings of the 24th Chinese Control and Decision Conference, 2012, Taiyuan, IEEE, 32773281

[20] HuY, WangM-g, YangYao. Parameters tuning of active disturbance rejection controller (ADRC) based on artificial fish swarm algorithm (AFSA) [J]. Command Control & Simulation, 2013, 35(2): 90-92

[21] LiJ-h, SunH-fei. Improvement and application of active disturbance rejection control [J]. Journal of Xiamen University (Natural Science Edition), 2018, 57(5): 695-701

[22] SunY-m, ZhangX-xiu. Parameter setting and application of ADRC by improved genetic algorithm [J]. Automation and Instrumentation, 2020, 35(3): 13-17

[23] HAN Wen-jie, TAN Wen. Parameter tuning of linear ADRC based on PID parameter tuning [EB/OL]. [2020-06-16]. https://doi.org/10.13195/j.kzyjc.2019.1408.

[24] ZHOU Tao. Parameter optimization of linear ADRC based on differential evolution algorithm [EB/OL]. [2020-06-16]. http://kns.cnki.net/kcms/detail/41.1228.TJ.20200219.0959.002.html.

[25] BaiJ, ZhuR-x, WangW, MaZhen. Control method based on linear ADRC controller design [J]. Science, Technology and Engineering, 2020, 20(10): 4149-4153

[26] GaoY, WuW-h, GaoLi. Linear ADRC for high order uncertain nonlinear systems [J]. Control and Decision, 2020, 35(2): 483-491

[27] LiuJ-f, YangZ, LiD-fang. A multiple search strategies based grey wolf optimizer for solving multi-objective optimization problems [J]. Expert Systems with Applications, 2020, 145: 113134

[28] PloS One, 2019, 14(3

[29] ZhangH, ZhengJ-q, XuY-lin. Study of auto disturbance rejection synchronous control for bilateral hydraulic motor of concept sprayer chassis [J]. Journal of China Agricultural University, 2017, 226): 135-143

[30] YangG-l, WangH-z, GuoL, HuangS-d, GongW-na. Simulation research on dynamic characteristic control of hydraulic valve-controlled motor [J]. Hydraulics Pneumatics & Seals, 2017, 37(1): 27-30

[31] HeH-lin. Research on frequency domain and time domain dynamic characteristics of servo valve [J]. Hydraulics Pneumatics & Seals, 2019, 39(11): 26-28

[32] ShengX-z, ZhongX-q, XuY, JiQ-qiang. Design and simulation analysis of electro-hydraulic position servo system [J]. Laboratory Research and Exploration, 2019, 38(4): 85-89

[33] YaoZ-y, CaoH-qing. A novel tracking differentiator with good stability and rapidity and its application [J]. Transactions of Beijing Institute of Technology, 2018, 38(8): 861-867

[34] LiuZ-gao. Design of improved tracking differentiator [J]. Navigation and Control, 2018, 17(4): 61-65

[35] CheJ-fengResearch on control of four rotor UAV Based on sliding mode auto disturbance rejection technology [D], 2019, Tianjin, Tianjin University of Technology

[36] ChenD-m, GuH-y, ZhangD-d, AnY-min. Active disturbance rejection control for steam temperature system of circulating fluidized bed boiler [J]. Journal of Guizhou University, 2019, 36(3): 91-95

[37] ZhouZ-gangApplication of active disturbance rejection control in superheated steam temperature and parameter optimization [D], 2019

[38] MirjaliliS, MirjaliliS M, LewisA. Grey wolf optimizer [J]. Advances in Engineering Software, 2014, 6946-61

[39] EswaramoorthyS, SivakumaranN, SekaranS. Grey wolf optimization based parameter selection for support vector machines [J]. COMPEL-the International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 2016, 35(5): 1513-1523

[40] JitkongchuenD, PhaidangP, PongtaweviratP, PiyalakP. An adaptive elitism-based immigration for grey wolf optimization algorithm [C]. 2017 International Conference on Digital Arts, Media and Technology (ICDAMT), 2017