Design of a UDE Frequency Selective Filter to Reject Periodical Disturbances

In this paper a new filter design for the Uncertainty and Disturbance Estimator (UDE) is proposed to reject periodical disturbances when a limited bandwidth is required for the control output. The motivation comes from several applications where the system actuator may introduce a bandwidth limitation, as a result of internal delays, or when the actuator itself is a limited bandwidth closed-loop system. When the traditional UDE approach is applied in these systems, the stability requirements impose a limitation over the effective bandwidth of the UDE filter and therefore disturbances cannot be fully rejected by the filter. In the case where the expected disturbance is periodical with a known fundamental frequency, the proposed UDE filter is designed as a chain of filters to match selected bands of the expected disturbance spectrum and fully reject them while maintaining the desired stability margins. A design example of a power inverter application is investigated and extensive simulation results are provided to verify the proposed UDE filter design

GPU Implementation of DPSO-RE Algorithm for Parameters Identification of Surface PMSM Considering VSI Nonlinearity

In this paper, an accurate parameter estimation model of surface permanent magnet synchronous machines (SPMSMs) is established by taking into account voltage-source-inverter (VSI) nonlinearity. A fast dynamic particle swarm optimization (DPSO) algorithm combined with a receptor editing (RE) strategy is proposed to explore the optimal values of parameter estimations. This combination provides an accelerated implementation on graphics processing unit (GPU), and the proposed method is, therefore, referred to as G-DPSORE. In G-DPSO-RE, a dynamic labor division strategy is incorporated into the swarms according to the designed evolutionary factor during the evolution process. Two novel modifications of the movement equation are designed to update the velocity of particles. Moreover, a chaotic-logistic-based immune RE operator is developed to facilitate the global best individual (gBest particle) to explore a potentially better region. Furthermore, a GPU parallel acceleration technique is utilized to speed up parameter estimation procedure. It has been demonstrated that the proposed method is effective for simultaneous estimation of the PMSM parameters and the disturbance voltage (Vdead) due to VSI nonlinearity from experimental data for currents and rotor speed measured with inexpensive equipment. The influence of the VSI nonlinearity on the accuracy of parameter estimation is analyzed

Parameter estimation for VSI-Fed PMSM based on a dynamic PSO with learning strategies

© 1986-2012 IEEE.A dynamic particle swarm optimization with learning strategy (DPSO-LS) is proposed for key parameter estimation for permanent magnet synchronous machines (PMSMs), where the voltage-source inverter (VSI) nonlinearities are taken into account in the parameter estimation model and can be estimated simultaneously with other machine parameters. In the DPSO-LS algorithm, a novel movement modification equation with variable exploration vector is designed to effectively update particles, enabling swarms to cover large areas of search space with large probability and thus the global search ability is enhanced. Moreover, a Gaussian-distribution-based dynamic opposition-based learning strategy is developed to help the pBest jump out local optima. The proposed DPSO-LS can significantly enhance the estimator model accuracy and dynamic performance. Finally, the proposed algorithm is applied to multiple parameter estimation including the VSI nonlinearities of a PMSM. The performance of DPSO-LS is compared with several existing PSO algorithms, and the comparison results show that the proposed parameters estimation method has better performance in tracking the variation of machine parameters effectively and estimating the VSI nonlinearities under different operation conditions

UDE-based Controller Equipped with a Multi-Band-Stop Filter to Improve the Voltage Quality of Inverters

In this paper, a method to directly shape the output impedance of an inverter is proposed to reduce the total harmonic distortion of the output voltage, based on the uncertainty and disturbance estimator (UDE)-based robust control framework. It is shown that, because of the two-degree-of-freedom feature of the UDE-based control strategy, the UDE filter directly affects the inverter output impedance. A multi-band-stop filter instead of a commonly adopted low-pass filter is then proposed to directly minimize the output impedance around the harmonics to reduce the effect of nonlinear loads and assure robustness to frequency variations. Two trade-offs are revealed: one between filter bandwidth and stability and the other between robustness and the number of harmonics suppressed. The effectiveness of the proposed control strategy is fully supported by experimental results