不确定非线性系统的自适应迭代学习控制研究

【作者】 刘萍；

【导师】 郭毓；

【作者基本信息】 南京理工大学 ， 控制理论与控制工程， 2007， 硕士

【摘要】 不确定非线性系统普遍存在于实际工程领域，充分利用系统的非线性结构特征，有利于简化控制器设计，提高控制性能。本文讨论了两类典型参数不确定非线性系统，设计了相应的自适应迭代学习控制方案，进行了相关理论分析、算例仿真和应用研究。针对一类带未知干扰和时变参数的非线性系统，提出了一种鲁棒自适应迭代学习控制算法。在迭代域内对未知参数进行估计，利用鲁棒控制抑制干扰，引入反馈环节进一步提高控制性能；针对一类带未知常参数和时变参数的非线性系统，提出了一种组合自适应迭代学习控制算法。通过对系统非线性结构特征的分析，该算法在时域内对未知常参数进行估计，在迭代域内对未知时变参数进行估计，充分利用了时域和迭代域信息。采用Backstepping技术将上述两种算法推广到二阶不确定非线性系统中，基于Lyapunov稳定性理论分析了这两种算法在相同初始条件和对准条件下的收敛性。仿真验证了所提控制算法的有效性。将上述算法分别应用于带未知不可重复干扰和带未知可重复时变干扰的两种参数不确定机械臂系统。推导了二自由度机械臂系统动力学模型，根据系统特性对算法进行了改进，给出了系统所有内部信号有界性和跟踪误差收敛性的证明。与传统自适应迭代学习控制的实例仿真相对比，结果表明所提方案具有更好的控制性能，在给定区间上实现了对期望轨迹的精确跟踪。更多还原

【Abstract】 Uncertain nonlinear systems are widely existed in practice engineering. Controllerdesign can be simplified and control performance can be improved by using the nonlinearcharacteristics fully. Two classes of typical nonlinear systems with uncertain parametersare discussed and adaptive iterative learning control (AILC) approaches are designedaccordingly. Moreover, theoretical analysis, numerical simulations and applicationresearches are given.For a class of nonlinear systems with unknown disturbance or time-varyingparameters, a robust adaptive iterative learning control (RAILC) algorithm is proposed.The unknown parameters are estimated in time-domain and the disturbance is inhibited byrobust control. Feedback control is also introduced to improve the control performance; fora class of nonlinear systems with unknown time-invariant or time-varying parameters, acomposite adaptive iterative learning control (CAILC) algorithm is proposed. Through theanalysis of the structure properties, time-invariant and time-varying parameters areestimated in time-domain and iteration-domain respectively in the algorithm, which makesfull use of the time-domain and the iteration-domain information. Both of the algorithmsare promoted to the second order uncertain nonlinear systems by means of backsteppingtechnology. The convergence analysis of the two approaches under identical initialcondition and alignment condition are carried out based on Lyapunov stability theory. Theeffectiveness of these algorithms is demonstrated by simulations.The applications of the above algorithms in parametric uncertain robot manipulatorswith unknown nonrepeatbal disturbance and in those with unknown repeatbal time-varyingdisturbance are discussed. The dynamic modal of the robot manipulator system is given,and the algorithms are adjusted according to the system properties. The boundedness of allinternal siginals and the convergence along the iteration horizon of output tracking errorare proved. Compared with a traditional AILC, the simulation results show that betterperformance can be obtained with the proposed methods, and the accurate tracking ofdesired trajectory on specified time interval can be achieved.更多还原