摘要
提出了一种用于控制复杂非线性系统的超稳定自适应控制算法。使用波波夫超稳定性原理设计控制器。用神经网络在线辨识系统的建模误差及不确定性因素 ,辨识结果作为补偿信号以实现系统的鲁棒控制。对一双输入双输出非线性系统的仿真结果表明 。
The author proposed a hyperstable adaptive control algorithm for complicated nonlinear systems. The Popov hyperstability principle is used in the design of the controller. The modeling errors and uncertainties of the system are identified on line by a neural network. The identification results are taken as compensation signals to realize robust control of nonlinear systems. Simulation results of a nonlinear dual input, dual output system indicate that dynamic property of the proposed hyperstable adaptive control algorithm is desirable.
出处
《电光与控制》
2003年第3期16-18,22,共4页
Electronics Optics & Control
