A modulated model-free predictive control with minimum switching losses (MSL-MMFPC) is proposed to improve the steady-state performance and reduce the switching losses for a permanent magnet synchronous motor (PMSM) drive system. Firstly, two adjacent current vectors are determined based on the predefined first-level cost function, and then, make the current vector at the next control period equal to the reference current vector by modulating the selected current vectors properly. Additionally, in order to keep optimal control performance also in the over-modulation region, a new rotating coordinate frame is used to adjust the optimal voltage vector. Then, the second-level cost function is designed to select the optimal voltage vector sequence, so that the switching of a VSI leg does not happen during the phase-current maximum, which can reduce the switching losses of the inverter. The simulation and experimental results verify the effectiveness of the proposed control method. INDEX TERMS PMSM drive system, modulated model-free predictive control, optimal voltage vector, over-modulation operation, minimum switching losses.
In order to improve the dynamic and steady-state performance of the finite control set model predictive torque controlled surface-mounted permanent magnet synchronous motor drive system, a novel finite control set model predictive torque control (FCS-MPTC) with different dynamic and steady-state control schemes is proposed in this paper. When the SMPMSM drive system operates at transient state, the optimal basic voltage vector of inverter is the vector that minimizes torque tracking error, the proposed FCS-MPTC achieves fast dynamic response based on the optimal torque control. When the system operates at steady state, the relative importance of torque to the stator flux amplitude is calculated based on the quantitative analysis of minimum staggered errors between motor torque and stator flux amplitude control objectives, then the priority weighting factors based on the relative importance are determined online adaptively, the optimal control of motor torque and stator flux amplitude is achieved simultaneously. Finally, the comparison of the experimental results of proposed FCS-MPTC with different control methods is implemented and research conclusion is shown.
Model predictive torque control (MPTC) has become an effective control method for the permanent magnet synchronous machine (PMSM) drive system in recent years. However, large torque and flux ripples due to the limited numbers of inverter voltage vector deteriorate the steady-state performance. In this paper, a novel model predictive torque control based on extended control set (ECS-MPTC) is proposed. First, an innovative extended control set is generated by the proposed partition method of quasi longitude and latitude lines, in which, many virtual voltage vectors are generated. Then, based on the characteristic of cost function without weighting factor, the optimal inverter voltage vector can be selected quickly by using the double gradient descent methods, and the invalid enumeration can be avoided. Thus, the computation burden can be kept in a low level. Finally, the simulation results of conventional MPTC and proposed ECS-MPTC validate that the proposed control can achieve excellent steady-state performance of PMSM drive system and low computation burden simultaneously.
In order to improve the control performance and robustness of the surface-mounted permanent magnet synchronous motor drive system, the direct speed control is proposed based on the ultra-local model, which is established based on the input and output of the system, and the dynamics and disturbances are estimated by the differential algebra comprehensively. A dynamic variable with adaptive coefficients is defined first, which includes the speed error and armature q-axis current explicitly. The ultra-local model about it is established consequently. Then, a single controller is designed to control speed and current simultaneously under the cascade-free structure. To guarantee the stability of system and obtain the range of adaptive coefficients, the Lyapunov function is designed with speed and current errors. Moreover, the adaptive coefficients are online tuned by adaptive laws to suit operating conditions. At the same time, the current and voltage constraints are also handled to prevent overcurrent and make full use of the power supply. With the proposed method, excellent transient and steady-state performance can be achieved in the context of safe operation. The effectiveness of the proposed method is validated by the experiments, and comparisons with the double closed-loop proportional integral (PI) control verify its technical advantages.
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