Vector Control Algorithm for Electric Vehicle AC Induction Motor Based on Improved Variable Gain PID Controller

The acceleration performance of EV, which affects a lot of performances of EV such as start-up, overtaking, driving safety, and ride comfort, has become increasingly popular in recent researches. An improved variable gain PID control algorithm to improve the acceleration performance is proposed in this paper. The results of simulation with Matlab/Simulink demonstrate the effectiveness of the proposed algorithm through the control performance of motor velocity, motor torque, and three-phase current of motor. Moreover, it is investigated that the proposed controller is valid by comparison with the other PID controllers. Furthermore, the AC induction motor experiment set is constructed to verify the effect of proposed controller

Cooperation of voltage controlled active power filter with grid-connected DGs in microgrid

Due to the excessive use of nonlinear loads and inverter interfaced distributed generators, harmonic issues have been regarded as a major concern in power distribution systems. Therefore, harmonic compensation in microgrids is a subject of current interest. Consequently, a novel direct harmonic voltage-controlled mode (VCM) active power filter (APF) is proposed to mitigate the harmonics in a cooperative manner and provide a better harmonic compensation performance of less than 5%. Due to the dispersive characteristics of renewable energy resources, voltage feedback based on a harmonic compensation control loop is implemented for the first time. This system can be smoothly combined with the current control loop. Our method proposes a better performance while mitigating the harmonics in comparison with conventional resistive active power filters (R-APF). Based on direct voltage detection at the point of common coupling (PCC), the proposed VCM-APF can therefore be seamlessly incorporated with multiple grid-connected generators (DGs) to enhance their harmonic compensation capabilities. The advantage of this scheme is that it avoids the need for designing and tuning the resistance, which was required in earlier conventional control schemes of R-APF for voltage unbalance compensation. Additionally, our scheme does not require the grid and load current measurements since these can be carried out at the PCC voltage, which further reduces the implementation cost of the system. Furthermore, the simulation results show the significance of proposed method

Multiple Second-Order Generalized Integrators Based Comb Filter for Fast Selective Harmonic Extraction

Fast and accurate harmonic extraction plays a vital role in power quality assessment, grid synchronization, harmonic compensation, etc. This paper proposes a multiple second-order generalized integrators (SOGIs) based comb filter (SOGIs-CF) for fast selective harmonic extraction. Compared with the conventional multiple SOGI-quadrature signal generators (SOGI-QSGs) scheme, the tedious harmonic decoupling network (HDN) is removed off without sacrificing steady-state detection accuracy, and thus the computation burden can be reduced. In addition, the parameters design criteria and the digital implementation issues have been discussed in detail. Finally, the experimental results confirm the fast response and high detection accuracy of the proposed scheme. The characteristic of fast harmonic magnitude signal detection makes the proposed method quite suitable for the realization of flexible output capacity-limit control of multifunction inverters

Bayesian estimation of human impedance and motion intention for human-robot collaboration

This article proposes a Bayesian method to acquire the estimation of human impedance and motion intention in a human-robot collaborative task. Combining with the prior knowledge of human stiffness, estimated stiffness obeying Gaussian distribution is obtained by Bayesian estimation, and human motion intention can be also estimated. An adaptive impedance control strategy is employed to track a target impedance model and neural networks are used to compensate for uncertainties in robotic dynamics. Comparative simulation results are carried out to verify the effectiveness of estimation method and emphasize the advantages of the proposed control strategy. The experiment, performed on Baxter robot platform, illustrates a good system performance

Rethinking the competition between detection and ReID in Multi-Object Tracking

Due to balanced accuracy and speed, joint learning detection and ReID-based one-shot models have drawn great attention in multi-object tracking(MOT). However, the differences between the above two tasks in the one-shot tracking paradigm are unconsciously overlooked, leading to inferior performance than the two-stage methods. In this paper, we dissect the reasoning process of the aforementioned two tasks. Our analysis reveals that the competition of them inevitably hurts the learning of task-dependent representations, which further impedes the tracking performance. To remedy this issue, we propose a novel cross-correlation network that can effectively impel the separate branches to learn task-dependent representations. Furthermore, we introduce a scale-aware attention network that learns discriminative embeddings to improve the ReID capability. We integrate the delicately designed networks into a one-shot online MOT system, dubbed CSTrack. Without bells and whistles, our model achieves new state-of-the-art performances on MOT16 and MOT17. Our code is released at https://github.com/JudasDie/SOTS

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The random time-varying delays would reduce control performance and even deteriorate the EV system. To deal with random time-varying delays and achieve a real-time steady-state response, considering randomness of delay and a rapid response, an H∞-based delay-tolerant linear quadratic regulator (LQR) control method based on Taylor series expansion is proposed in this paper. The results of cosimulations with Simulink and CarSim demonstrate the effectiveness of the proposed controller through the control performance of yaw rate, sideslip angle, and the running track. Moreover, the results of comparison with the other controller illustrate the strength of explicitly