Indoor temperature model is one of the large time-delay controlled object, and the response performance of system get worse. In consideration of the Fuzzy PID controllers strong robustness, this article adopts a Fuzzy PID-Smith control method ,and the control effect proves to be good.

The wheeled robot with non-integrity constraints is a typical nonlinear system, in order to achieve the ideal path tracing, presented a theory based on fuzzy neural network control. Centralized compensation system based on neural network uncertainty can be arbitrary-precision approximation of continuous nonlinear functions as well as the complex uncertainties with adaptive and learning ability. By MATLAB simulation showed that the control method to ensure fast convergence and error robustness of parameter uncertainties and external disturbance.

In the complex heating systems, higher order, large inertia, large delay and uncertainty typically exist. This work introduces generalized predictive PID control algorithm to adjust the system. The purpose of the control algorithm is to achieve a steady state in a shorter time. On the basis of analyzing PID control algorithm and Generalized Predictive Control (GPC), configuring a given performance function index control-weighted sequences to GPC control. Derived form of generalized predictive control algorithm with PID. The Matlab simulation shows that using generalized predictive PID control algorithm can produce better results in shorter time than simple using PID or GPC in the heating system.