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Stability and Hopf bifurcation of a nonlinear electromechanical coupling system with time delay feedback

Chinese Physics B 2015年第1期24卷 345-353页

作者：刘爽赵双双王兆龙李海滨 Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan University

The stability and the Hopf bifurcation of a nonlinear electromechanical coupling system with time delay feedback are studied. By considering the energy in the air-gap field of the AC motor, the dynamical equation of the electromechanical coupling transmission system is deduced and a time delay feedback is introduced to control the dynamic behaviors of the system. The characteristic roots and the stable regions of time delay are determined by the direct method, and the relationship between the feedback gain and the length summation of stable regions is analyzed. Choosing the time delay as a bifurcation parameter, we find that the Hopf bifurcation occurs when the time delay passes through a critical value.A formula for determining the direction of the Hopf bifurcation and the stability of the bifurcating periodic solutions is given by using the normal form method and the center manifold theorem. Numerical simulations are also performed, which confirm the analytical results.

关键词： electromechanical coupling time delay Hopf bifurcation stability

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Anti-saturation fault-tolerant adaptive torsional vibration control with fixed-time prescribed performance for rolling mill main drive system

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Journal of Iron and Steel Research International 2024年第3期31卷 660-669页

作者： Shuang Liu Chen Du Cong Zhang Zhen-hua Bai Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan UniversityQinhuangdao 066004HebeiChina National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan UniversityQinhuangdao 066004HebeiChina

An anti-saturation fault-tolerant adaptive torsional vibration control method with fixed-time prescribed performance for the rolling mill main drive system(RMMDS)was investigated,which is affected by control input saturation,actuator faults,sensor measurement errors,and parameter ***,we gave a continuously differentiable saturation function to approximate the control input saturation characteristic of the RMMDS,translating the saturation characteristic into the matched uncertainty and unknown time-varying gain in the ***,an RMMDS mathematical model with unmatched uncertainty and unknown time-varying gain was developed,taking into account the presence of control input saturation,actuator faults,sensor measurement errors,and parameter *** on the established mathematical model,an error transformation model of the roll speed tracking was constructed by the equivalent error transformation *** to the error transformation model,a barrier Lyapunov function and a novel adaptive controller were studied to ensure that the roll speed tracking error always evolves inside a fixed-time asymmetric ***,numerical simulations were performed in Matlab/Simulink to verify the effectiveness and superiority of the proposed control method in suppressing the RMMDS torsional vibration.

关键词： Fixed-time prescribed performance control input saturation Actuator fault Unknown time-varying gain Adaptive control Asymmetric constraint

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Distributed containment control for multi-robot system based on binocular vision and RBF neural network

International Journal of Control and Automation

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International Journal of control and Automation 2015年第9期8卷 139-152页

作者： Shao, Nuan Li, Huiguang Liu, Le Li, Guoyou Key Lab of Industrial Computer Control Engineering of Hebei Province College of Electrical Engineering Yanshan University Qinhuangdao China

Aiming at the distributed containment control problem for Multi-Robot system with dynamic leaders, we use binocular vision as the sensing device, so firstly, a binocular visual model for dynamic target is established by introducing the pseudo depth variable, and it is used to provide Real-Time status information for the followers. Then, in the case that each follower can only get information from part of the leaders, even individual follower can not get any information from the leaders directly, the topological relationship among robots is built by using the graph theory. Once more, RBF neural networks are employed to approximate the uncertainties in the system model of followers, and L2robust control laws are used to restrain the influences of the approximation errors. Finally, a simulation is carried out on multiple 2 Degrees-Of-Freedom (DOF) robots, and results validate the designed controllers can drive the followers converge to the convex hull spanned by the leaders asymptotically and realize synchronization motion ultimately. © 2015 SERSC.

关键词： Multipurpose robots

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control of epileptiform spikes based on nonlinear unscented Kalman filter

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Chinese Physics B 2014年第1期23卷 41-48页

作者：刘仙高庆李小俚 Key Lab of lndustrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University Qinhuangdao 066004 China

A new control strategy based on nonlinear unscented Kalman filter(UKF) is proposed for a neural mass model that serves as a model for simulating real epileptiform stereo-electroencephalographic (SEEG) signals. The UKF is used as an observer to estimate the state from the noisy measurement because it has been proved to be effective for state estimation of nonlinear systems. A UKF controller is constructed via the estimated state and is illustrated to be effective for epileptiform spikes suppression of aforementioned model by numerical simulations.

关键词： unscented Kalman filter(UKF) control epileptiform spike closed-loop control neural mass model

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Iterative learning control for nonlinear systems with uncertain state delay and arbitrary initial error

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控制理论与应用（英文版） 2011年第4期9卷 541-547页

作者： Hongbin WANG Yan WANG Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao Hebei 066004 China

Most of the existing iterative learning control algorithms proposed for time-delay systems are based on the condition that the time-delay is precisely available, and the initial state is reset to the desired one or a fixed value at the start of each operation, which makes great limitation on the practical application of corresponding results. In this paper, a new iterative learning control algorithm is studied for a class of nonlinear system with uncertain state delay and arbitrary initial error. This algorithm needs to know only the boundary estimation of the state delay, and the initial state is updated, while the convergence of the system is guaranteed. Without state disturbance and output measurement noise, the system output will strictly track the desired trajectory after successive iteration. Furthermore, in the presence of state disturbance and measurement noise, the tracking error will be bounded uniformly. The convergence is strictly proved mathematically, and sufficient conditions are obtained. A numerical example is shown to demonstrate the effectiveness of the proposed approach.

关键词： Iterative learning control State-delay system Initial condition Uncertain disturbances

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Friction compensation control of space manipulator considering the effects of gravity 35

Friction compensation control of space manipulator consideri...

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第35届中国控制会议

作者： QIN Li JIA Xiao-jing LIU Cai-feng LIU Fu-cai Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781509009107

All space manipulators are debugged on the ground and on-orbit serviced in space. Compared with in ground gravity environment their friction characteristics in space microgravity environment have great changes. For sake of tracking the desired trajectory, in both ground and space, considering these characteristics, a friction compensation control method based on an Active Disturbance Rejection control(ADRC) is proposed and its effectiveness is validated on a planar 2-DOF free-floating space manipulator. The friction models and the dynamic models under different gravity environment have been derived based on the torque balance, the Kane equation and the Lagrange method. Particle Swarm Optimization(PSO) is put forward to optimize parameters of ADRC so as to improve the efficiency of designing process. Compared with PD controller in tracking simulation under different gravity environment, the results verify the advantage of the proposed improved control method.

关键词： space manipulator gravity friction compensation ADRC Trajectory tracking PSO

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A novel multi-objective decomposition particle swarm optimization based on comprehensive learning strategy 36

A novel multi-objective decomposition particle swarm optimiz...

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第36届中国控制会议

作者： Lixin Wei Rui Fan Xin Li Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781538629185

Comprehensive learning particle swarm optimization（CLPSO） algorithm has a good performance in overcoming premature convergence and avoiding getting stuck in local minima, which are shortcomings in particle swarm optimization. It can solve complex, multi-modal of single-objective problems, but it has not such performance in handling multi-objective optimization problems because of the difficulty of selective solution mechanism. In this article, a multi-objective decomposition particle swarm optimization based on comprehensive learning strategy is proposed, which uses a comprehensive learning strategy for multi-objective problems to prevent premature convergence;updates the leading particles by decomposition method to enhance the distribution of solutions;adds the archive to preserve non-dominated solutions, and adopts mutation in archive to avoid falling into local optimum. The proposed approach is compared with three multi-objective evolutionary algorithms and the results indicate that the proposed approach is competitive respect to which it is compared in most of the test problems adopted.

关键词： comprehensive learning particle swarm optimization multi-objective optimization decomposition

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Vibration suppress of flexible spacecraft considering the effects of gravity 34

Vibration suppress of flexible spacecraft considering the ef...

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第三十四届中国控制会议

作者： GAO Juan-juan CHEN Xin JIA Xiao-jing LIU Fu-cai Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781467374439

Considering that gravity on the ground alignment phase is different from that in space application phase, an adaptive backstepping sliding mode control method is proposed to achieve the attitude control and vibration suppression of the flexible spacecraft under different gravity environment. Fully considering the change of dynamic models, the sliding mode controller is designed according to the backstepping theory to control the flexible spacecraft under the influence of model and disturbances uncertainties, and the adaptive control laws are proposed to estimate the disturbances and gravity item online. The control strategy can guarantee the stability of the system based on the Lyapunov theory. The simulation results show that the controller is effective in attitude control and vibration suppression of the flexible spacecraft under different gravity environment, and has important value for theoretical research and engineering application.

关键词： Flexible spacecraft,Gravity,Vibration suppression,Backstepping sliding mode,Adaptive

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Design of Robotic Visual Servo control Based on Neural Network and Genetic Algorithm

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International Journal of Automation and computing 2012年第1期9卷 24-29页

作者： Hong-Bin Wang Mian Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical EngineeringYanshan UniversityQinhuangdao 066004PRC

A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.

关键词： Visual servo image Jacobian back propagation （BP） neural network genetic algorithm robot control

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A study on clutch multi-modal fuzzy control in AMT vehicle starting process

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Journal of Computational Information Systems 2013年第6期9卷 2121-2129页

作者： Zang, Huaiquan Li, Dongdong Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical and Engineering Yanshan University Qinhuangdao 066004 China

In this paper, mathematical model of relationship between clutch engaging speed and engine output torque is firstly established to solve the problem of clutch engaging speed in AMT vehicle starting process, basing on analysis of the reduced kinetic model of clutch. Then multi-modal fuzzy control algorithm is adopted to precisely predict clutch engagement stage, and then driver's intension is considered to fuzzy control the clutch engaging speed. Finally, simulation modal is established. The simulation results show that, basing on the drivers intension and external environment, the control strategy proposed in this paper not only makes the vehicle start fast and stably, but also reduces slip friction work with the premise of comfort, which extends clutch working life and obtains better control performance in clutch starting process. Copyright © 2013 Binary Information Press.

关键词： Clutches

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