目标轨线迭代可变的非线性系统自适应学习控制

针对含有混合参数的非线性不确定系统,提出了一种自适应迭代学习控制方案。该方案利用Back-stepping方法和参数重组技巧相结合,可以处理目标轨线迭代可变的跟踪问题。通过引入微分-差分自适应学习律,设计了一种自适应控制策略,使得跟踪误差在一个有限区间上的积分渐近收敛于零;通过构造Lyapunov-like函数,给出了闭环系统收敛的一个充分条件。数值仿真验证了所提方法的可行性。

Adaptive learning control of nonlinear systems with iteration-varying trajectory

An adaptive iterative learning control of nonlinear systems with mixed-type parameters is developed by combining the Backstepping approach with the parameter regrouping technique,which can handle the iteration-varying trajectory tracking problem.A differential-difference type adaptive law and an adaptive iterative learning controller are constructed to ensure the asymptotic convergence of tracking errors in the sense of square error norm on the finite interval,by introducing a Lyapunov-like function,a sufficient condition of the convergence of the method is given.A simulation example illustrates the feasibility of the proposed method.