基于线性化误差模型的自适应控制系统设计

本文提出了一种基于线性化误差模型的自适应控制系统。该控制系统首先为非线性过程建立一个ARX模型与一个基于神经模糊系统的线性化误差模型组成的合成模型，然后再引入单神经元控制器，利用线性ARX模型输出和系统输出值之间的误差以及被控制过程的合成模型的梯度信息对控制器参数进行在线调节，从而获得较好的控制结果。最后，将提出的基于线性化误差模型的自适应控制系统用于简单不可逆放热反应的连续搅拌型化学反应器CSTR中，并和传统的PID控制器进行比较。仿真结果表明，这种基于线性化误差模型的自适应控制和PID控制器相比，具有更快的响应速度。

Adaptive Control Scheme Design Based on Linearization Error Model

An adaptive control scheme based on linearization error model, is proposed. Firstly, a class of SISO nonlinear processes is approximated by a composite model consisting a linear ARX model and a FNN-based linearization error model (FNNM). Then a single neuron controller is employed. The parameters of the controller can be adjusted by using the error between the output of the linear ARX model and the output of the system, and the gradient information of the composite model. Finally, the proposed controller is used in CSTR, and is compared with the conventional PID controller. Simulation results show that the proposed controller has better performance.