耦合时空混沌的模糊混沌神经网络鲁棒自适应控制

Fuzzy Chaos Neural-network Robust Adaptive Control in Coupled system

将模糊逻辑系统和混沌神经网络结合起来,利用模糊逻辑系统的逼近能力和混沌神经网络的时空混沌行为,对模型未知的耦合时空混沌系统提出了一种模糊混沌神经网络自适应控制方案;同时考虑系统扰动、未建模动态特性和建模误差的影响,设计自适应补偿器,增强时空混沌系统控制的鲁棒性;并用Laypunov方法证明了该方案的稳定性;仿真验证了方案的有效性和鲁棒性。

Combined fuzzy logic with chaos neural-network, a new fuzzy chaos neural-network adaptive control scheme is proposed for unknown-model spatio-temporal chaos in coupled system by utilizing the approximation capacity of the fuzzy logic and the spatio-temporal behavior of the chaos neural-network. Taken the effects from disturbance, unmodeled dynamics and modeling errors into account, the additional adaptive compensation controller is designed to improve the robustness of the spatio-temporal chaos control scheme. The stability of the proposed method is verified with Lyapunov method, and the effectiveness and the robustness of the scheme are demonstrated via simulation examples.