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IEEE International Conference on Robotics and Biomimetics

作者： Shuhuan Wen Jianhua Chen Shen Wang Hong Zhang Xueheng Hu department of Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Department of Computing Science University of Alberta Edmonton Canada

ISBN: (纸本)9781728103785;9781728103778

The robot arm with multiple degrees of freedom and working in a 3D space needs to avoid obstacles during the grasping process by its end effector. Path planning to avoid obstacles is very important for accomplishing a grasping task. This paper proposes a new obstacle avoidance algorithm, based on an existing deep reinforcement learning framework called deep deterministic policy gradient (DDPG). Specifically, we propose to use DDPG to plan the trajectory of a robot arm to realize obstacle avoidance. The rewards are designed to overcome the difficulty in convergence of multiple rewards, especially when the rewards are antagonistic with respect to each other. Obstacle avoidance of the robot arm using DDPG is achieved by self-learning, and the convergence problem caused by the high dimension state input and multiple return values is solved. The simulation model of an arm of the Nao robot is built based on the MuJoCo simulation environment. The simulation demonstrates that the proposed algorithm successfully allows the robot arm to avoid obstacles.

关键词： Manipulators Neural networks Robot kinematics Planning Reinforcement learning Trajectory

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Sensor Fault Detection of Continuous Casting Mold Vibration System Driven by Servo Motor

Sensor Fault Detection of Continuous Casting Mold Vibration ...

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第37届中国控制会议

作者： Xia Wu Jianxiong Li Yiming Fang Zhiqiang Wang Key Lab of Industrial Computer Control Engineering of Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

The problem of sensor fault diagnosis and reconstruction of the continuous casting mold vibration displacement system driven by servo motor is investigated in this paper, and a fault reconstruction method based on adaptive sliding mode observer is proposed. Firstly, the matching condition of the observer is satisfied by constructing an auxiliary output, and a new state variable is selected as the low-pass filter with the fault vector output. Then an adaptive sliding mode observer is designed for the auxiliary output system in the present of the unknown upper bound of the fault, in which the adaptive switching gain is updated online. The gain matrix of the observer is obtained by solving a LMI optimization problem. And a linear transforming matrix is introduced to realize the direct estimation of the fault by the principle of the equivalent control output error injection. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

关键词： continuous casting mold sensor fault reconstruction adaptive sliding mode observer equivalent control output error injection

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Nonlinear control of triple inverted pendulum based on T-S cloud inference network 29

Nonlinear control of triple inverted pendulum based on T-S c...

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第29届中国控制与决策会议

作者： Xiu-ling Zhang Jing-huan Dai Yan-tao Cheng Shuang Hao Jia-huan Li 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

ISBN: (纸本)9781509046584

The triple inverted pendulum is a nonlinear, dynamic and unsteady system. The traditional control methods of triple inverted pendulum have limited control accuracy and slow responding. This kind of pendulum system is difficult to control due to the inherent instability and nonlinear behavior. In this paper, GA-RBF-ARX model is applied to model triple inverted pendulum based on its input/output data. According to the nonlinear identification model, a novel method via T-S cloud inference network controller optimized by genetic algorithm(GA) is proposed. T-S cloud inference network is constituted by T-S fuzzy neural network and the cloud model. Therefore, the rapid of fuzzy logic and the uncertain of cloud model for processing data are both taken into account. What's more, GA possesses global optimization characteristics and good parallel design structure. Compared with the simulation recognition results of T-S fuzzy neural network controller, T-S cloud reference network controller has strong robust and fast calculate speed. So, T-S cloud inference network by GA is an effective method in control.

关键词： T-S cloud inference network GA-RBF-ARX Triple inverted pendulum

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Backstepping Sliding Mode control for Continuous Casting Mold Vibration Displacement System Driven by Servo Motor 36

Backstepping Sliding Mode Control for Continuous Casting Mol...

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第36届中国控制会议

作者： LI Jianxiong GUO Cui FANG Yiming ZHANG Qiyu Key Lab of Industrial Computer Control Engineering of Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

ISBN: (纸本)9781538629185

Aiming at the time-varying load torque disturbance in the vibration displacement system of continuous casting mold driven by servo motor,an extended state observer(ESO) based backsteppmg sliding mode control method is ***,a mapping function is established to deal with the non-uniqueness of the nonlinear inverse relationship from eccentric shaft angle to mold ***,an ESO is constructed to estimate the time-varying load torque,and the estimate of load torque is employed to compensate the disturbance in *** a backsteppmg sliding mode controller is then developed for the vibration displacement system of continuous casting mold,which can guarantee the asymptotical stability and the robust stability of the resulting closed-loop ***,simulation results are given to show the effectiveness of the proposed method.

关键词： servo motor drive system vibration displacement system extended state observer backstepping sliding mode control

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EV Charging Network Design with Transportation and Power Grid Constraints

EV Charging Network Design with Transportation and Power Gri...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Yongmin Zhang Jiayi Chen Lin Cai Jianping Pan The State Key Lab. of Industrial Control Technology Zhejiang University China The Department of Electrical & Computer Engineering University of Victoria BC Canada The Department of Computer Science University of Victoria BC Canada

Connected electric vehicles (EVs) are a key component of future intelligent and green transportation systems, and the penetration of EVs depends on convenient and cost-effective charging services. In addition to being charged at home or on parking lots, a charging network is needed for EVs right off the road. This paper first focuses on the optimal charging network design for charging service providers, considering the time-varying and location-dependent demands from vehicles and constraints of power grids. To optimize the charging station locations and the number of chargers in each station, we first model the coverage area of each possible location to estimate the dynamic charging requirements of EVs. Then, we formulate the problem as profit maximization, which is a mixed-integer program. To make the problem tractable, we investigate the features of the problem and obtain a necessary condition to deploy a charging station and derive the upper and lower bounds of the number of chargers in each station. Given the analysis, we take two steps to transform and relax the problem to convex optimization. A fast-converging search algorithm is further proposed based on the profit of each possible location. Using real vehicle traces, simulation results show that the proposed algorithm can maximize the total profit when fewer charging stations and chargers are initially needed, which is more attractive for charging service providers.

关键词： Charging stations Power grids Upper bound Space stations Nickel Electric vehicle charging

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Fuzzy Sliding Mode controller Design for Active Suspension Systems with Load Variation

Fuzzy Sliding Mode Controller Design for Active Suspension S...

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第六届工程机械与车辆工程新进展国际学术会议

作者： S.Liu Z.G.Wang Y.P.Zhang Z.J.Lin Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University

This paper mainly investigates the fuzzy sliding mode control of 1/4 vehicle suspension ***,the dynamical model of suspension system with uncertainty is established for the time-varying of

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Open-closed-loop iterative learning control for a class of nonlinear systems with random data dropouts

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IOP Conference Series: Materials Science and engineering 2018年第1期359卷

作者： X Y Cheng H B Wang Y L Jia YH Dong The Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

In this paper, an open-closed-loop iterative learning control (ILC) algorithm is constructed for a class of nonlinear systems subjecting to random data dropouts. The ILC algorithm is implemented by a networked control system (NCS), where only the off-line data is transmitted by network while the real-time data is delivered in the point-to-point way. Thus, there are two controllers rather than one in the control system, which makes better use of the saved and current information and thereby improves the performance achieved by open-loop control alone. During the transfer of off-line data between the nonlinear plant and the remote controller data dropout occurs randomly and the data dropout rate is modeled as a binary Bernoulli random variable. Both measurement and control data dropouts are taken into consideration simultaneously. The convergence criterion is derived based on rigorous analysis. Finally, the simulation results verify the effectiveness of the proposed method.

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Adaptive finite time consensus control of multiple mechanical systems under a switching graph 35

Adaptive finite time consensus control of multiple mechanica...

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第35届中国控制会议

作者： WANG Hongbin ZHOU Zhen WANG Yueling Key Lab of Industrial Computer Control Engineering of Hebei Province Yansnan University

ISBN: (纸本)9781509009107

In this paper,adaptive finite time consensus control problem is investigated for multiple mechanical systems with *** adaptive distributed control algorithms are proposed for the multiple mechanical systems under a switching undirected graph,which is addressed through a novel Markov *** any detailed information of the system model,the adaptive distributed controller has a faster and higher precision tracking *** is shown that the states of the mechanical systems can reach a consensus within finite *** finally,an illustrative simulation on the multiple robotic manipulators is given to demonstrate the effectiveness of the proposed controller.

关键词： Finite time consensus Adaptive control Multiple mechanical system Markov chain

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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 Fast Channel State Information Feedback Scheme Based on Compressive Sensing for Underwater Acoustic MIMO Systems 35

A Fast Channel State Information Feedback Scheme Based on Co...

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第35届中国控制会议

作者： MA Hui JIAO Jianzhou CHEN Jianmei LI Xinbin Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781509009107

In this paper,a compressive feedback scheme based on compressed sensing is investigated to reduce feedback load and enhance the sum throughput at low feedback rates for underwater acoustic MIMO ***,to avoid the outof-date channel state information at the transmitter under the high dynamic underwater channel,we present a modified SL0（M-SLO） algorithm to recover the CSI at the transmitter,which adopts more steep approximate hyperbolic tangent function to approximate the l norm in the *** minimization problem of the l norm canbe transformed into a convex optimization problem for the smoothed ***,in order to solve the problem of slow convergence and inaccuracy estimation caused by notched ejfect of the gradient method,hybrid optimization algorithm that combines the advantages of the gradient method and the revised Newton method is introduced to improve the accuracy of sparse *** simulations show that the recovery accuracy and speed are improved by the proposed M-SL0 algorithm comparing with SL0,OMP ***,CSI feedback based compressive sensing performs better than the feedback based on a vector quantitation codebook.

关键词： compressive feedback compressed sensing M-SLO recovery algorithm channel state information

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