A Control Lyapunov Approach to Finite Control Set Model Predictive Control for Permanent Magnet Synchronous Motors

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Gideon Prior ◽  
Miroslav Krstic
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Harmonic Distortion ◽  
Search Space ◽  
Control Lyapunov Function ◽  
Permanent Magnet Synchronous Motors ◽  
Synchronous Motors ◽  
Finite Control ◽  
Error System ◽  
Novel Model

In this paper, we present a novel model predictive control (MPC) scheme that incorporates stability information derived from a control Lyapunov function (CLF) to dynamically prune suboptimal sequences from the search space and decrease the computational burden placed on the controller. The CLF used for pruning is then incorporated into a cost function that penalizes energy in the error system as well as energy loss due to switching. Despite the very small control periods allowed due dynamic pruning, experimental results are given, showing the resulting controller generates low switching frequencies and low total harmonic distortion.

scholarly journals Total Harmonic Distortion Oriented Finite Control Set Model Predictive Control for Single-Phase Inverters

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3467 ◽  
Author(s):  
Po Li ◽  
Ruiyu Li ◽  
Haifeng Feng
Keyword(s):  
Model Predictive Control ◽  
Cost Function ◽  
Predictive Control ◽  
Single Phase ◽  
Tracking Error ◽  
Harmonic Distortion ◽  
Total Harmonic Distortion ◽  
Finite Control ◽  
Control Set ◽  
The Cost

Inverters are commonly controlled to generate AC current and Total Harmonic Distortion (THD) is the core index in judging the control effect. In this paper, a THD oriented Finite Control Set Model Predictive Control (FCS MPC) scheme is proposed for the single-phase inverter, where a optimization problem is solved to obtain the switching law for realization. Different from the traditional cost function, which focuses on the instantaneous deviation of amplitude between predictive current and its reference, we redesign a cost function that is the linear combination of the current fundamental tracking error, instantaneous THD value and DC component in one fundamental cycle (for 50 Hz, it is 0.02 s). Iterative method is developed for rapid calculation of this cost function. By choosing a switching state from a FCS to minimize the cost function, a FCS MPC is finally constructed. Simulation results in Matlab/Simulink and experimental results on rapid control prototype platform show the effect of this method. Analyses illustrate that, by choosing suitable weight of the cost function, the performance of this THD oriented FCS MPC method is better than the traditional one.

scholarly journals Runge-Kutta Model Predictive Speed Control for Permanent Magnet Synchronous Motors

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1216
Author(s):  
Adile Akpunar ◽  
Serdar Iplikci
Keyword(s):  
Model Predictive Control ◽  
Permanent Magnet ◽  
Predictive Control ◽  
Mimo Systems ◽  
Wide Spectrum ◽  
Speed Control ◽  
Current Control ◽  
Permanent Magnet Synchronous Motors ◽  
Synchronous Motors ◽  
Runge Kutta

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.

scholarly journals Explicit model predictive control of permanent magnet synchronous motors based on multi-point linearization

2021 ◽  
pp. 014233122110151
Author(s):  
Qian Guo ◽  
Tianhong Pan ◽  
Jinfeng Liu ◽  
Shan Chen
Keyword(s):  
Model Predictive Control ◽  
Permanent Magnet ◽  
Predictive Control ◽  
Block Diagram ◽  
Explicit Model ◽  
Servo Drive ◽  
Permanent Magnet Synchronous Motors ◽  
Synchronous Motors ◽  
Online Computation ◽  
Explicit Model Predictive Control

Permanent magnet synchronous motors (PMSMs) have been broadly applied in servo-drive applications. It is necessary to improve the performance of PMSM. An explicit controller designed for PMSM based on multi-point linearization is proposed to reduce the linearized model error caused by different running status of PMSM. The mathematical model of PMSM system in the synchronous rotating frame and the problem formulation are introduced at first. Then, the preliminaries about explicit model predictive control (MPC) algorithm are presented in this article. Based on this, the multi-point linearization model is created for explicit MPC controller design. Moreover, the block diagram of the proposed method for PMSM system is presented. Finally, the simulation results are provided to demonstrate that the proposed explicit MPC controller based on multi-point linearization achieves better performance than that based on traditional single-point linearization, but requires the same online computation time because of the offline optimization of explicit MPC.

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