关键词: 神经模糊系统, 自适应控制, 线性化误差模型, 单神经元控制器

Abstract:

In order to overcome the nonlinearity and time-varying uncertainty of actual industrial processes, an adaptive control system based on linearization error model is proposed. In this system, first, a composite model consisting a ARX model and a linearization error model based on the neuro-fuzzy system is constructed to describe the nonlinear process. Then, by employing a single-neuron controller and by considering the error between the ARX model output and the system output, as well as the gradient information of the composite model, the controller pa- rameters are adjusted online with high control performance. Simulated results indicate that, as compared with the conventional PID controller, the proposed adaptive controller based on linearization error model is of higher response speed.

Key words: neuro-fuzzy system, adaptive control, linearization error model, single-neuron controller