Evaluation of model based predictive control algorithms for fractional horse power drives

摘要

Model based predictive control is a new promising control method in the field of power electronics and electrical drives. The main advantages of MPC are simplicity and intuitiveness of the control method. Constraints and nonlinearities of the system can easily be included, which makes the linearisation of the system unnecessary. By using MPC it is possible to avoid the cascaded structure of common linear control methods and to gain a fast dynamic performance. A disadvantage is the need to calculate the optimal actuating variable multiple times in every single sampling cycle leads to a huge requirement of computational power. So far the computational requirement was the greatest barrier for the practical application of model based predictive control in the field of power electronics and electrical drive systems. In addition the small time constants of fractional horse power drives complicate the application of predictive control algorithms. In this paper, the feasibility of hardware implementation of a cost function based Finite Control Set MPC (FCS-MPC) algorithm for direct speed control of fractional horse power drives is explored. The cost function allows to address various control goals like dynamics of transitions and energy efficiency – an advantage linear conventional control methods cannot offer. Hitherto there are very few publications for direct predictive speed. The presented approach for direct predictive speed control includes a finite number of possible switching states of the converter. This considers the discrete nature of power converters and avoids the need for modulation. The basic principle of the control method is presented and the performance is demonstrated by simulations and experimental results for an industrial brushed type DC-motor.