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4th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2019

作者： Xue, Hongxiang Wen, Shuhuan Yang, Chao Liu, Huaping Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China Department of Computer Science and Technology State Key Laboratory of Intelligent Technology and System Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing100084 China

ISBN: (纸本)9781728100647

Trajectory generation is a fundamental problem for successful robotic grasping. However, most of the existing work dealt with this problem using supervised learning with a prescribed model. It prevents the developed grasp strategies from being used for new unknown scenarios. In this paper, inspired by the success of the reinforcement learning method, we developed a new method which optimizes grasp trajectories using a policy search method. An important advantage of the proposed method is that the complicated 3D model could be used to generate the multi-dimensional grasp configurations. The developed algorithm has been validated on some typical robotic hand. The experimental results show that the proposed method achieves excellent performance. © 2019 IEEE.

关键词： Trajectories

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controlling velocity of armature based on the multi-pulse forming network

Controlling velocity of armature based on the multi-pulse fo...

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International Conference on Pulsed Power

作者： Zhenchun Wang Zhiyong Bao Fucai Liu Lijie Jia Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University QinHuangDao China

Given the accuracy of the muzzle velocity of railgun, based on the capacitive energy-stored type of pulse forming network, electromechanical model of railgun is established, a multistage multi-module velocity control strategy based on velocity closed-loop control is proposed. Through the simulate analyze of the multiple of PFU by using electromechanical model of railgun, the best PFU electrical parameters and the best multi-stage control strategy are obtained, test shows that the system model and the control strategy can be applied to the actual system experiment, and achieve good results.

关键词： Interference Load modeling Accuracy Velocity control Electromagnetics Capacitors

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A fuzzy-PI hybrid controller based on a disturbance observer

A fuzzy-PI hybrid controller based on a disturbance observer

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International Conference on Natural Computation (ICNC)

作者： Manjun Cai Yue Wang Key lab of industrial computer control engineering in Hebei province Yanshan University Qinhuangdao China

This paper proposes a fuzzy PI hybrid speed controller for a PMSLM (Permanent Magnet Synchronous Linear Motor), which is based on a friction disturbance observer. It can improve the problems caused by the friction disturbance and the system parameters perturbation. Also the problem of the blind area for fuzzy control is eventually eliminated, because of the introduction of the PI control. Finally, through the simulation test and comparative analysis with the traditional PID control method, the validity and rationality of the control scheme is illustrated.

关键词： Observers Mathematical model Fuzzy control PD control Steady-state Equations Friction

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An Ameliorated Moth-flame Optimization Algorithm

An Ameliorated Moth-flame Optimization Algorithm

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Chinese control Conference

作者： Xiao-dong Zhao Yi-ming Fang Zhuang Ma Miao Xu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

To improve the global search ability under the condition of ensuring convergence speed, it is still a major challenge for most meta-heuristic optimization algorithms. The Moth-Flame Optimization (MFO) algorithm is an innovative nature-inspired algorithm. To improve the precision of the solution and to quicken the convergence speed and to increase the stability of MFO, an ameliorated Moth-flame optimization algorithm (A-MFO) that combines the crisscross optimization algorithm with MFO is proposed to solve this problems that are mentioned above. The performance of proposed A-MFO is demonstrated on six benchmark mathematical function optimization problems regarding superior accuracy and lower computational time achieved compared to other well-known nature-inspired algorithms.

关键词： Optimization Fires Convergence Sociology Statistics Benchmark testing Heuristic algorithms

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Relaxed Stability Analysis and Event-Triggered controller Design for Discrete-Time Positive T-S Fuzzy Networked control Systems

Relaxed Stability Analysis and Event-Triggered Controller De...

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Annual Conference of Industrial Electronics Society

作者： Xiaoxiao Wang Xiaomiao Li Zhiyong Bao Fucai Liu Yuehao Du Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

This paper deals with the relaxation stability analysis and event-triggered controller design of discrete-time positive Takagi-Sugeno (T-S) fuzzy networked control systems (FNCSs). The constraints of positive conditions in NCSs bring significant challenges to stability analysis and controller design. A 1-norm event-triggered scheme is proposed for the positive system, which can effectively reduce the frequency of network communication. Since the event-triggered T-S fuzzy controller (ETTSFC) can only observe the latest transmission state after the triggering action, the ETTSFC selects the premise variables different from the T-S fuzzy model, improving design and implementation flexibility. Using the linear copositive Lyapunov function (LCLF), the design criteria of the event-triggered controller to ensure the positivity and stability of the closed-loop system are derived. To relax the sum-of-squares (SOS) based conservative condition, we adopt the Taylor series membership functions (TSMFs) and introduce TSMFs and their approximation error into the stability conditions. Finally, an example is given to illustrate the effectiveness of the design.

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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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Chinese control Conference (CCC)

作者： Xia Wu Jianxiong Li Yiming Fang Zhiqiang Wang Key Lab of Industrial Computer Control Engineering of Yanshan University Qinhuangdao Hebei Province China

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： Observers Casting Mathematical model Servomotors Adaptive systems Vibrations Upper bound

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An Improved NSGAII Algorithm for Flexible Job-shop Scheduling Problem Based on A New Decoding Mechanism

An Improved NSGAII Algorithm for Flexible Job-shop Schedulin...

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IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Man Li Kai Ma Shiliang Guo Shuai Li Bin Yang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

The flexible job-shop scheduling problem (FJSP) is a famous combinatorial optimization problem. FJSP is widely used in process manufacturing industry, so it is of great significance to study FJSP to improve production efficiency. In this paper, a non-dominated sorting genetic algorithm II based on a new decoding mechanism (NSGAII_NDM) is proposed. Firstly, the opposite-based learning strategy is introduced on the basis of NSGAII, and the sufficiency of global search is improved by generating the opposite value. Secondly, an improved adaptive crossover and mutation probability strategy is added, which can dynamically adjust the inherent crossover and mutation probability with the number of iterations and improve the convergence speed of the algorithm. Furthermore, based on fully active scheduling strategy, a new decoding mechanism is proposed, which can get a better scheduling scheme by arranging the machines and starting time of each process more reasonably. Finally, the improved algorithm is tested in a standard test case, which verifies the superiority of NSGAII_NDM in solving the flexible job-shop scheduling problem.

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Multiple Relay Selection Scheme Based on Artificial Bee Colony Algorithm

Multiple Relay Selection Scheme Based on Artificial Bee Colo...

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International Conference on Instrumentation, Measurement, computer, Communication and control (IMCCC)

作者： Juan Wang Xinbin Li Kai Ma Key Lab of Industrial Computer Control Engineering Hebei Province Yanshan University Qinhuangdao China

ISBN: (纸本)9781479913930

Relay selection (RS) and power control are two essential parts in cooperative cognitive relay network. RS is equal to power control in the condition that a relay cooperates with its full power or doesn't cooperate at all. So the optimal signal-to noise ratio (SNR) value is described as a 0-1 nonlinear programming integer problem (NLIP). In this paper, a multiple relay selection (MRS) scheme based on artificial bee colony algorithm (ABC) is proposed that can fully obtain optimal SNR value. Simulations show the performance of MRS scheme by ABC algorithm is better than that of exhaustive search, single RS scheme and other sub optimal MRS schemes.

关键词： Signal to noise ratio Cognitive radio Power control Relay networks (telecommunications)

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Robust stabilization of nonlinear uncertain systems by dynamic output feedback

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ICIC Express Letters 2011年第7期5卷 2293-2298页

作者： Li, Jianxiong Fang, Yiming Shi, Shengli Chang, Ru Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University No. 438 Hebei Street Qinhuangdao 066004 China

This paper proposes a constructive way to design dynamic output feedback control law to stabilize a class of nonlinear systems with unknown control coefficients. The unknown parameters are described in polytopic forms, and control parameter matrices of the dynamic controller are obtained by solving series of linear matrix inequalities in sequence. It is shown that the robust asymptotic stability of closed-loop system can be guaranteed by the proposed method. Finally, a numerical example illustrates the effectiveness of the proposed algorithm. © 2011.

关键词： Nonlinear systems

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An Improved Seagull Optimization Algorithm for Flexible Job-shop Scheduling Problem

An Improved Seagull Optimization Algorithm for Flexible Job-...

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IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Kai Ma Shijie Yao Shiliang Guo Bin Yang Shuai Li Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

Job-shop scheduling problem is the core link and key technology to realize smart factory and develop smart manufacturing technology. Among them, the flexible job-shop scheduling problem (FJSP) which is more consistent with the actual production and processing mode has been focused. This paper proposes an improved seagull optimization algorithm(ISOA) for solving the FJSP. The ISOA uses chaos initialization and reverse learning to optimize initial population, and introduces Q-learning to change the fitting parameters to balance global search and local search. In addition, we propose a local search model that is adaptive iterative process to enhance the algorithm's optimization search capability. The results of the experiment proved that the algorithm is superior in terms of optimization speed and scheduling results.

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