Some Approaches to Adaptive Control of Non-linear Physical Laboratory Servo-system DR300
The physical laboratory model a servo – system "Speed Control with Variable Load DR300" contains the technical realization of a non-linear single-input/single-output system with appropriate actuator, sensors measurement outputs and the possibility to connect different controllers. Traditional controllers with fixed parameters are often unsuitable for control of non-linear processes because their parameters vary when the operating point changes. One possible alternative for improving the quality of control for such processes is the use of adaptive control systems. Different approaches were proposed and utilized. One successful approach is represented by self-tuning controller. This approach is also called system with indirect adaptation (with direct identification). The main idea of an self-tuning controller is based on the combination of a recursive identification procedure and a selected controller synthesis. The paper is focused in design of some approaches to adaptive control algorithms and their applications for control of the servo-system DR300. The algorithms consider constraints of a manipulated variable. The self-tuning controllers are based on an analytical design of a structure of the laboratory model and measured both static and dynamic characteristics. An ARX model is used in the identification part of the individual controllers. The standard STC approach based on the Linear Quadratic (LQ) method is verified and compared with two STC based on the Model Predictive Control (MPC). The designed algorithms of all three methods were verified and compared by the real-time control of an above-mentioned non-linear laboratory model.