Abstract
Permanent magnet synchronous motors (PMSMs) have commonly been used in a wide spectrum ranging from industry to home appliances because of their advantages over their conventional counterparts. However, PMSMs are multiple-input multiple-output (MIMO) systems with nonlinear dynamics, which makes their control relatively difficult. In this study, a novel model predictive control mechanism, which is referred to as the Runge-Kutta model predictive control (RKMPC), has been applied for speed control of a commercial permanent magnet synchronous motor. Furthermore, the RKMPC method has been utilized for the adaptation of the speed of the motor under load variations via RKMPC-based online parameter estimation. The superiority of RKMPC is that it can take the constraints on the inputs and outputs of the system into consideration, thereby handling the speed and current control in a single loop. It has been shown in the study that the RKMPC mechanism can also estimate the load changes and unknown load disturbances to eliminate their undesired effects for a desirable control accuracy. The performance of the employed mechanism has been tested on a 0.4 kW PMSM motor experimentally for different conditions and compared to the conventional Proportional Integral (PI) method. The tests have shown the efficiency of RKMPC for PMSMs.
Highlights
Permanent magnet synchronous motors (PMSMs) have been used in many variable speed-driving applications in industry and home appliances such as robotic actuators, computer disk drives, domestic application, automotive and renewable energy conversion systems because of their advantages namely small size, less maintenance, reliability, high efficiency, and high power density.In the control of electrical motor drivers, vector-based linear cascaded proportional integral (PI) control approach is widely used since it is quite reliable and easy to implement, where inner loop is responsible for regulating the currents in the d-q rotating reference framework and the outer loop provides the reference current for the inner loop to regulate the speed [1]
In order show the efficiency of the Runge-Kutta model predictive control (RKMPC) method, it has been tested in different operating conditions
RKMPC has been compared to a conventional PI controller, the parameters of which are tuned by trial-and-error
Summary
PMSMs have been used in many variable speed-driving applications in industry and home appliances such as robotic actuators, computer disk drives, domestic application, automotive and renewable energy conversion systems because of their advantages namely small size, less maintenance, reliability, high efficiency, and high power density. In [15], a new speed finite control set MPC algorithm has been implemented which is be applied to a PMSM driven by a matrix converter (MC). In this method, motor currents and speed are realized in a single control loop. In [16] direct speed control based on finite control set-model predictive speed control (FCS-MPSC) with voltage smoothing is presented to reduce current fluctuations. With this control method, sudden changes in the output voltage caused by large current ripple are avoided.
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