An open-closed-loop iterative learning control approach for nonlinear switched systems with application to freeway traffic control - 钟任新

钟任新

简介城市交通系统建模/动态交通分配/最优控制和非线性控制/随机动态规划/自适应动态规划/强化学习与智能交通系统应用

For nonlinear switched discrete-time systems with input constraints, this paper presents an open-closed-loop iterative learning control (ILC) approach, which includes a feedforward ILC part and a feedback control part. Under a given switching rule, the mathematical induction is used to prove the convergence of ILC tracking error in each subsystem. It is demonstrated that the convergence of ILC tracking error is dependent on the feedforward control gain, but the feedback control can speed up the convergence process of ILC by a suitable selection of feedback control gain. A switched freeway traffic system is used to illustrate the effectiveness of the proposed ILC law.