Abstract
This paper presents a novel Model Predictive Direct Power Control (MPDPC) approach for the pulse width modulation (PWM) rectifiers in the Aircraft Alternating Current Variable Frequency (ACVF) power system. The control performance of rectifiers may be largely affected by variations in the AC side impedance, especially for systems with limited power volume system. A novel idea for estimating the impedance variation based on the Bayesian estimation, using an algorithm embedded in MPDPC is presented in this paper. The input filter inductance and its equivalent series resistance (ESR) of PWM rectifiers are estimated in this algorithm by measuring the input current and input voltage in each cycle with the probability Bayesian estimation theory. This novel estimation method can overcome the shortcomings of traditional data based estimation methods such as least square estimation (LSE), which achieves poor estimation results with the small samples data set. In ACVF systems, the effect on the parameters estimation accuracy caused by the number of sampling points in one cycle is also analyzed in detail by simulation. The validity of this method is verified by the digital and Hard-in-loop simulation compared with other estimation methods such as the least square estimation method. The experimental testing results show that the proposed estimation algorithm can improve the robustness and the control performance of the MPDPC under the condition of the uncertainty of the AC side parameters of the three-phase PWM rectifiers in aircraft electrical power system.
Highlights
In the recent years, thanks to technological advances in microprocessors, model predictive control (MPC) has been proposed and studied as a promising alternative for the control of power converters and drives [1]
pulse width modulation (PWM) rectifiers based on Bayesian estimation with Model Predictive Direct Power Control (MPDPC)
In view of the problem that the uncertainty model parameters, the model parameter can be updated every cycle with the proposed algorithm by sampling input Ac current and voltage waveform.With the estimated value of input inductance in each sampling period, the future value of input current, active power and reactive power can be accurately predicted
Summary
Thanks to technological advances in microprocessors, model predictive control (MPC) has been proposed and studied as a promising alternative for the control of power converters and drives [1]. In Reference [18], Based on a three-phase PWM rectifier, a robust model predictive control algorithm with disturbance observer is proposed. A non-linear constrained control strategy based on robust model prediction and sliding mode control with the parameter estimation is proposed in Reference [19]. This method is not applicable to referring to discrete-time model of PWM rectifiers, which is only designed for continuous-time model. Based on the aerospace three-phase PWM rectifier, the cause and influence of inaccurate input filter inductance’s variation are discussed in this paper.
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