Low-complexity robust tracking of high-order nonlinear systems with application to underactuated mechanical dynamics

被引:13
作者
Yoo, Sung Jin [1 ]
机构
[1] Chung Ang Univ, Sch Elect & Elect Engn, 84 Heukseok Ro, Seoul 156756, South Korea
基金
新加坡国家研究基金会;
关键词
Low-complexity tracking; High-order nonlinear systems; Unknown nonlinearities; Underactuated mechanical systems; STATE-FEEDBACK STABILIZATION; ADAPTIVE NEURAL-CONTROL; OUTPUT-FEEDBACK; SURFACE CONTROL; PRESCRIBED PERFORMANCE; CONTROL COEFFICIENTS; PARAMETERIZATION; DESIGN;
D O I
10.1007/s11071-017-3969-0
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This paper presents a low-complexity design approach with predefined transient and steady-state tracking performance for global practical tracking of uncertain high-order nonlinear systems. It is assumed that all nonlinearities and their bounding functions are unknown and the reference signal is time varying. A simple output tracking scheme consisting of nonlinearly transformed errors and positive design parameters is presented in the presence of virtual and actual control variables with high powers where the error transformation technique using time-varying performance functions is employed. Contrary to the existing results using known nonlinear bounding functions of model nonlinearities, the proposed tracking scheme can be implemented without using nonlinear bounding functions (i.e., the feedback domination design), any adaptive and function approximation techniques for estimating unknown nonlinearities. It is shown that the tracking performance of the proposed control system is ensured within preassigned bounds, regardless of high-power virtual and actual control variables. The motion tracking problem of an underactuated unstable mechanical system with unknown model parameters and nonlinearities is considered as a practical application, and simulation results are provided to show the effectiveness of the proposed theoretical result.
引用
收藏
页码:1627 / 1637
页数:11
相关论文
共 39 条
  • [1] Agha R., 2017, IEEE T SYST MAN CYBE
  • [2] [Anonymous], 2013, Mathematical control theory: deterministic finite dimensional systems
  • [3] [Anonymous], 1995, NONLINEAR ADAPTIVE C
  • [4] A low-complexity global approximation-free control scheme with prescribed performance for unknown pure feedback systems
    Bechlioulis, Charalampos P.
    Rovithakis, George A.
    [J]. AUTOMATICA, 2014, 50 (04) : 1217 - 1226
  • [5] Global finite-time stabilization of a class of switched nonlinear systems with the powers of positive odd rational numbers
    Fu, Jun
    Ma, Ruicheng
    Chai, Tianyou
    [J]. AUTOMATICA, 2015, 54 : 360 - 373
  • [6] Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems
    Ge, SS
    Wang, J
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (06): : 1409 - 1419
  • [7] Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients
    Ge, SZS
    Hong, F
    Lee, TH
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2004, 34 (01): : 499 - 516
  • [8] A novel adaptive control approach for nonlinear strict-feedback systems using nonlinearly parameterised fuzzy approximators
    Li, Ping
    Yang, Guang-Hong
    [J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2011, 42 (03) : 517 - 527
  • [9] OUTPUT-FEEDBACK STABILIZATION OF STOCHASTIC HIGH-ORDER NONLINEAR SYSTEMS UNDER WEAKER CONDITIONS
    Li, Wuquan
    Xie, Xue-Jun
    Zhang, Siying
    [J]. SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2011, 49 (03) : 1262 - 1282
  • [10] Adaptive output-feedback control design with prescribed performance for switched nonlinear systems
    Li, Yongming
    Tong, Shaocheng
    Liu, Lu
    Feng, Gang
    [J]. AUTOMATICA, 2017, 80 : 225 - 231