Predictive Control Algorithms Verification on the Laboratory Helicopter Model

The main goal of this paper is to present the suitability of predictive control application on a mechatronic system. A theoretical approach to predictive control and verification on a laboratory Helicopter model is considered. Firstly, the optimization of predictive control algorithms based on a state space, linear regression ARX and CARIMA model of dynamic systems are theoretically derived. A basic principle of predictive control, predictor deducing and computing the optimal control action sequence are briefly presented for the particular algorithm. A method with or without complying with required constraints is introduced within the frame of computing the optimal control action sequence. An algorithmic design manner of the chosen control algorithms as well as the particular control structures appertaining to the algorithms, which are based on the state space or the input-output description of dynamic systems, are presented in this paper. Also, the multivariable description of the educational laboratory model of the helicopter and a control scheme, in which it was used as a system to be controlled, is mentioned. In the end of the paper, the results of the real laboratory helicopter model control with the chosen predictive control algorithms are shown in the form of time responses of particular control closed loop's quantities.