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Xiong D.,Hefei University of Technology | Xiong D.,Jiangsu Sujing Purification Group Co. | Chen Y.H.,Georgia Institute of Technology | Zhao H.,Hefei University of Technology | Huang J.,Hunan University
Xitong Fangzhen Xuebao / Journal of System Simulation | Year: 2013

A new decentralized control design (HDC) is considered for a large-scale system with uncertainty. The uncertainty may be due to the unknown parameters and the uncertainty is bounded with uncertain bound. The bound is in high-order form that may be due to the unknown parameters and input disturbance. The available information of the uncertainty is prescribed by fuzzy characteristics. That is, the uncertainty is assumed to be within certain fuzzy sets. HDC is adopted for the system. The optimal design problem is solved by obtaining the minimization of a performance index with the decentralized control method which reflects the system's average fuzzy characteristics. The problem is cast into an optimal gain design setting. It is shown how to obtain the optimal gain solutions of a whole large-scale system. The solution to this optimization system performance index is proved to be always exists and is unique. Furthermore, the closed-form expression and cost are explicitly listed. The procedure of design is also summarized for the ease of illustration of the control design. Finally, a mechanical system is considered for further verification by simulation. The uncertainties in the system are transformed to mathematics expression from language information before the execution of simulation. The results show that the system is uniformly bounded and uniformly ultimately bounded. The control cost and control effect are well balanced. For further demonstration, system simulation also executed under another two typical control: PD control and adaptive trajectory control. The results show superiority of HDC than the other under the same initial condition.

Xiong D.,Hefei University of Technology | Xiong D.,Jiangsu Sujing Purification Group Co. | Chen Y.H.,Georgia Institute of Technology | Zhao H.,Hefei University of Technology
Journal of Intelligent and Fuzzy Systems | Year: 2014

We consider a decentralized control design for a class of fuzzy complex systems. This system contains uncertainty, consists of multiple subsystems, and faces information structure constraints. The uncertainty is represented by an uncertain bound, which is described by a fuzzy membership function. The control scheme is decentralized. In addition, it is robust and optimal: while it guarantees certain performance regardless of the uncertainty, it also minimizes a performance index. With regard to the minimization phase of the design, the solution is shown to be existent and unique. © 2014 IOS Press and the authors.

Yin X.,Zhejiang Normal University | Yang C.,Zhejiang Normal University | Zhou X.,Zhejiang Normal University | Wu D.,Jiangsu Sujing Purification Group Co.
Journal of Computational Information Systems | Year: 2014

Due to the limited energy-storage capability, energy conservation has become one of the most important issues for wheeled mobile robots (WMRs). Besides, with the initial position error or/and the discontinuity of the reference trajectory, using traditional control methods may lead to obvious velocity jump at the early motion stage. In this paper the trajectory tracking control problem of the WMR was addressed and an energy-effcient tracking control approach based on bio-inspired neurodynamics was proposed. The proposed approach was successfully applied to a non-holonomic WMR kinematics model. In addition, simulation results were presented to validate the effectiveness of the proposed control approach. Copyright © 2014 Binary Information Press.

Yin X.-H.,Zhejiang Normal University | Yang C.,Zhejiang Normal University | Xiong D.,Jiangsu Sujing Purification Group Co.
International Journal of Advanced Manufacturing Technology | Year: 2014

Nowadays, the automated guided vehicles (AGV) have been widely used with increasing missions in a variety of fields such as the industry, military, and research. Due to the nonholonomic constraints, fulfilling satisfactory control of the AGV becomes a big challenge. In the present work, a bio-inspired neurodynamics-based cascade tracking control strategy was proposed. Specifically, the bio-inspired neurodynamics module was utilized to generate smooth forward velocities for overcoming the sharp velocity jump. Moreover, with the cascade tracking approach, the nonholonomic system was transformed into a chained system. Additionally, a state differential feedback controller was applied to improve the tracking accuracy. Finally, simulation investigations based on Matlab codes with various parameter settings were carried out to verify the effectiveness of the proposed strategy. The simulation results showed that the proposed strategy in the present work is able to produce accurate, smooth, robust, and globally stable control for the AGV. © 2014 Springer-Verlag London.

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