In order to obtain a robust optimal control for a DC drive system a different solution from the existing technical literature is proposed in this paper. By using the linear quadratic control the optimal speed of the DC dive is obtained. This serves as a reference to the adaptive DC drive system. The model reference adaptive control (MRAC) ensures the robustness to parameters and load variations, to unmodelled uncertainties and high dynamic performances. Moreover, the MRAC provides on-line the controller parameters. The problem statement of the optimal control, model reference adaptive control mechanism and the validation of the new proposed control by numerical simulations are presented in this paper. The transient regimes (starting, reversing or braking) are dominant in electric drive systems, therefore the energetic optimization of the DC motor is proposed.
This paper describes the model reference adaptive fuzzy controller design and its application on automatic gauge control system. The controller produces the error of the closed loop control system response and the actual system output for the desired system by reference model, instead of ordinary adaptive mechanism. The analysis of dynamic performance for traditional PID controller and fuzzy adaptive controller is performed in detail with simulation software. Simulation results show that the system is with strong adaptive ability and can adapt to the wide range of changes of the controlled object. This study provides the primary theoretical guide for the design, optimization and control research of the automatic gauge control system.
It is proved, by using topological properties, that when a group automorphism of a locally compact totally disconnected group is ergodic under the Haar measure, the group is compact. The result is an answer for Halmos's question that has remained open for the totally disconnected case.