During motor operation, the motor parameters change, which causes parameter drift. They are also affected by internal and external unknown disturbances, which lead to reduced motor control performance, poor anti-interference performance, and low robustness. A method termed ultra-local modelfree predictive current control (MFPCC) has previously been proposed to solve this problem; it uses only the input and output of the system and does not involve any motor parameters, because of which it is free of problems caused by model mismatch. However, the conventional MFPCC method requires adjustment of several control parameters and the estimated value of the total disturbance of the system has a certain deviation and a large pulsation, which result in obvious chattering of the motor output, low stability, reduced anti-interference performance, and low robustness. Therefore, this paper proposes an MFPCC method based on nonlinear disturbance compensation (NDC). This method does not involve any motor parameters, and it can more accurately and stably estimate the total system disturbance, and feedforward compensation, real-time update control information, only need to adjust two control parameters, the workload is small. Simulation results show that the proposed control method has high anti-interference performance, high robustness, small output ripple, and improved dynamic characteristics and that it can estimate the system disturbance accurately and stably.
To solve the key problems of strong infrared radiation, poor continuous combat capability of the system, serious ablation of the launching device, and environmental pollution during missile launch, electromagnetic launch system (EMLS) has been studied for missile launching tasks. Since most of the current research is aimed at the key technologies and there is a lack of evaluation and balance of the entire system, the effectiveness of the missile electromagnetic launch system (MEMLS) needs to be evaluated. To solve the shortcomings of the existing effectiveness evaluation model, this paper establishes an improved model for effectiveness evaluation. The new model takes the availability-dependability-capability (ADC) model as the basic evaluation framework. The L20(2 19) orthogonal table is constructed by using the orthogonal design idea without interaction. On the basis of quantifying and normalizing the indicators, different weighting methods are adopted according to the different characteristics of the two level indicators. The improved combination weighting model of game theory (ICWGT) is used to obtain the combined weights for indicators of each level. To coordinate the incompleteness, ambiguity, and randomness of the information, and at the same time meet the requirements of flexible numerical feature values, the asymmetric gray cloud model (AGCM) is used to determine the evaluation level and evaluation value of the inherent capability C. On the basis of calculating the effectiveness evaluation value of each scheme by ADC model, the significance of each capability indicator of MEMLS was analyzed by variance analysis method. The conclusions obtained are consistent with the actual situation, which verifies the effectiveness of the model. INDEX TERMS Missile electromagnetic launch system (MEMLS), Effectiveness evaluation, Availabilitydependability-capability (ADC) model, Orthogonal design, The improved combination weighting model of game theory (ICWGT), Asymmetric gray cloud model (AGCM)
Model predictive control (MPC) has been widely implemented in the motor because of its simple control design and good results. However, MPC relies on the permanent magnet synchronous motor (PMSM) system model. With the operation of the motor, parameter drift will occur due to temperature rise and flux saturation, resulting in model mismatch, which will seriously affect the control accuracy of the motor. This paper proposes a model predictive control based on parameter disturbance compensation that monitors system disturbances caused by motor parameter drift and performs real-time parameter disturbance compensation. And the frequency-domain method was used to analyze the convergence and filterability of the model. The Bode diagram of measurement error and input disturbance was studied when the parameters were underdamped, critically damped, and overdamped. Guidelines for parameter selection are given. Simulation results show that the proposed method has good dynamic performance, anti-interference ability, and parameter robustness, which effectively avoids the current static difference and oscillation problems caused by parameter changes.
During the operation of a permanent magnet synchronous motor (PMSM), the control system is impacted by changes in the internal parameters and by external disturbances, resulting in reduced accuracy. The robustness and anti-interference ability of a PMSM can be improved using a speed loop-current loop integrated predictive control method. First, a PMSM mathematical model is constructed considering parameter changes and external disturbances. Second, using only the input and output of the speed loop and the current loop, without involving any motor parameters, an ultra-local model-free predictive control model of the speed loop and the current loop is built; this model has a lower sensitivity to parameter changes. Finally, to improve the tracking accuracy for speed and current, an extended state observer (ESO) and a disturbance observation compensator (DOC) are established to observe the total disturbance of system in real time and perform feedforward compensation. The experimental results show that the control model has strong robustness and anti-interference ability, high stability, high speed, and capable current-tracking performance.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
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