This paper describes a new approach to adaptive control of uncertain nonlinear systems. A fuzzy logic controller is used to combine both direct and indirect methods. Based on the fuzzy neural networks, the plant unknown nonlinear functions are estimated, and then combined to form the indirect control law. In parallel, another fuzzy neural network approximates the direct adaptive control. According to the modelling error and its derivatives, the fuzzy logic controller modulates between direct and indirect adaptive controllers. The global stability of the overall system is shown by constructing a Lyapunov function. The simulation results show that within this scheme, the control objectives can be achieved with a fast convergence and optimal control for different dynamic regimes.

中文翻译：

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不确定非线性系统的混合模糊直接/间接自适应控制器

本文描述了一种新的不确定非线性系统自适应控制方法。模糊逻辑控制器用于结合直接和间接方法。基于模糊神经网络对被控对象的未知非线性函数进行估计，然后组合形成间接控制律。同时，另一个模糊神经网络近似于直接自适应控制。根据建模误差及其导数，模糊逻辑控制器在直接和间接自适应控制器之间进行调制。整个系统的全局稳定性通过构造一个李雅普诺夫函数来表示。仿真结果表明，在该方案内，可以通过快速收敛和针对不同动态状态的优化控制来实现控制目标。