Designed the control system policy for automobile electric seat using fuzzy control technology, therefore established its control model by Fuzzy Logic Toolbox, and carried on the off-line simulation to choose controller's optimum control parameters. From the dynamic viewpoint, the auto electric seat adjustment system is not only a complex nonlinear function which includes the location of the DC servo motor and the speed, but also contains serious nonlinear coupling interference, so the system is a highly nonlinear strong coupling, variable multivariable system. Application of traditional control methods (such as traditional PID) is difficult to meet its order requirements, so the research is highly robust method of intelligent control is an effective way to solve the problem. Fuzzy control technology has become the field in which drawn greater attention and researched in recent years. It doesn’t depend on the mathematical model of controlled object, has a good robustness, and nonlinear control characteristics, so it is an effective means to control the object with time-varying, non- linear parameters. In this paper, fuzzy control technology to achieve the orders of auto electric seat adjustment control system functions in the Literature [1], and the tracking of the system was simulated.
Seeing motion of controlled object improves grip timing in adults with autism spectrum condition: evidence for use of inverse dynamics in motor control
