自动化学报2026，Vol.52Issue(1)：137-147,11.DOI:10.16383/j.aas.c250327
连续时间系统混合迭代鲁棒自适应评判控制
Robust Adaptive Critic Control With Hybrid Iteration for Continuous-time Systems
摘要
Abstract
By integrating a hybrid iteration mechanism with an adaptive critic framework,a robust control method is designed for disturbed continuous-time nonlinear systems.The goal of accelerating learning and relaxing preset conditions are achieved by improving the traditional value iteration method.By incorporating adjustable paramet-ers,the admissibility of the control policy during the iteration process is ensured,thereby relaxing the conditions for setting the accelerated factor.Combined the idea of generalized policy iteration,a novel hybrid iteration mechan-ism is constructed to acquire better convergence performance.Finally,two simulation examples are used to verify the performance of the proposed method.The simulation results of the linear system show the higher convergence accuracy of the method in this paper.In the simulation of the missile autopilot system,it is demonstrated that the convergence speed is improved by approximately 49%without relying on an initial admissible control policy com-pared to value iteration method.关键词
自适应动态规划/连续时间系统/评判网络/混合迭代/HJI方程/鲁棒控制Key words
adaptive dynamic programming/continuous-time systems/critic network/hybrid iteration/Hamilton-Jacobi-Isaacs equation/robust control引用本文复制引用
王鼎,刘奥,乔俊飞..连续时间系统混合迭代鲁棒自适应评判控制[J].自动化学报,2026,52(1):137-147,11.基金项目
国家自然科学基金(62473012,62222301,62021003),新一代人工智能国家科技重大专项(2021ZD0112302,2021ZD0112301),北京市自然科学基金(F251019)资助 Supported by National Natural Science Foundation of China(62473012,62222301,62021003),National Science and Techno-logy Major Project(2021ZD0112302,2021ZD0112301),and Bei-jing Natural Science Foundation(F251019) （62473012,62222301,62021003）
