Abstract
This paper investigates the application of the model predictive control (MPC) approach to control the speed of a permanent magnet synchronous motor (PMSM) drive system. The MPC is used to calculate the optimal control actions including system constraints. To alleviate computational effort and to reduce numerical problems, particularly in large prediction horizon, an exponentially weighted functional model predictive control (FMPC) is employed. In order to validate the effectiveness of the proposed FMPC scheme, the performance of the proposed controller is compared with a classical PI controller through simulation studies. Obtained results show that accurate tracking performance of the PMSM has been achieved.
Highlights
Permanent magnet synchronous motors fed by PWM inverters are widely used for industrial applications, especially servo drive applications, in which constant torque operation is desired
The research has focused on improvement of the performance related to current loop, speed loop, and/or position loop
The results obtained proved that the functional model predictive control (MPC) is able to control successfully the permanent magnet synchronous motor (PMSM) system in the transient and steady state cases
Summary
Permanent magnet synchronous motors fed by PWM inverters are widely used for industrial applications, especially servo drive applications, in which constant torque operation is desired. Several researchers have investigated the speed controller design of adjustable-speed PMSM systems to improve their transient responses, load disturbance rejection capability, tracking ability, and robustness [2,3,4,5,6,7,8,9,10,11]. The presence of the constraint is one of the main reasons why, for example, state space controllers have limited application in electrical drives. In spite of these advantages, MPC applications to electrical drives are still largely unexplored and only few research laboratories are involved in them. The proposed centralized scheme improves the control performance in a coordinated manner Another challenge of centralized MPC for PMSM is its large computational effort needed. The results obtained proved that the functional MPC is able to control successfully the PMSM system in the transient and steady state cases
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