Parallel-Observer-Based Predictive Current Control of Permanent Magnet Synchronous Machines With Reduced Switching Frequency

Abstract

Model predictive control (MPC) strategies have attracted wide attention due to its inherently high dynamic characteristics and flexible control capability. When the MPC is adopted to regulate the currents of permanent magnet synchronous machines, the cost function is typically constructed based on tracking errors of current components. Reduced switching frequency can be obtained by means of minimizing a revised cost function which includes a penalty item related to the predicted switching frequency. This will inevitably affect current tracking performances and, meanwhile, increase the computational burden due to the required long-horizon minimization. In order to solve this problem, this paper proposes a predictive current controller which inherently takes the converter zero-order-hold characteristics and system delay into account. Besides, with the aim of simultaneously realizing system behavior prediction and disturbance estimation, a structure of parallel extended-state observers is proposed. Theoretical analyses and experimental validations are both conducted to confirm its effectiveness. It is demonstrated that, under the situation of reduced switching frequency, improved control performances can be expected when the proposed controller is adopted, including highly dynamic responses inherently presented by typical predictive controllers and enhanced steady-state performances with the help of parallel observation structure.