In consideration of the limitation of the communication and the possibility that redundant robots might deliver information at different power levels, cases under weight-unbalanced directed graphs from the network top...
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In consideration of the limitation of the communication and the possibility that redundant robots might deliver information at different power levels, cases under weight-unbalanced directed graphs from the network topology perspective are in larger accordance with those in multiple redundant robot systems. By moving forward along this direction, a distributedcontroller is proposed in this article to handle circumstances of collaborativecontrol of multiple redundant robots under weight-unbalanced directed graphs. This kind of control problem is modeled into generalized quadratic programming (QP) problems with equality and inequality constraints. Then, the above QP problems are solved by a proposed neural-dynamics-based method, whose stability and convergence are theoretically proved subsequently. Besides, several experimental examples are conducted, and related comparisons are provided to demonstrate the feasibility of the proposed controller.
Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their *** work analyzes a collaborativecontrol problem of redundant manipulators with time delays and ...
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Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their *** work analyzes a collaborativecontrol problem of redundant manipulators with time delays and proposes a time-delayed and distributed neural dynamics *** assumptions that the network topology is fixed and connected and the existing maximal time delay is no more than a threshold value,it is proved that all manipulators in the distributed network are able to reach a desired *** proposed distributed scheme with time delays considered is converted into a time-variant optimization problem,and a neural dynamics solver is designed to solve it ***,the proposed neural dynamics solver is proved to be stable,convergent and ***,the allowable threshold value of time delay that ensures the proposed scheme’s stability is *** examples and comparisons are provided to intuitively prove the validity of the proposed neural dynamics scheme and solver.
distributed collaborative control strategies for microgrids often use periodic time to trigger communication,which is likely to enhance the burden of communication and increase the frequency of controller updates,lead...
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distributed collaborative control strategies for microgrids often use periodic time to trigger communication,which is likely to enhance the burden of communication and increase the frequency of controller updates,leading to greater waste of communication *** response to this problem,a distributed cooperative control strategy triggered by an adaptive event is *** introducing an adaptive event triggering mechanism in the distributedcontroller,the triggering parameters are dynamically adjusted so that the distributedcontroller can communicate only at a certain time,the communication pressure is reduced,and the DC bus voltage deviation is effectively reduced,at the same time,the accuracy of power distribution is *** MATLAB/Simulink modeling and simulation results prove the correctness and effectiveness of the proposed control strategy.
With the gradual development of bidirectional interacted future distribution network, it is necessary to enter distributed clean power sources with various characteristics, including wind turbine and solar panel. Trad...
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With the gradual development of bidirectional interacted future distribution network, it is necessary to enter distributed clean power sources with various characteristics, including wind turbine and solar panel. Traditional centralized control has difficulties to fulfill the demands of future distribution networks for safe, stable, and efficient operation. Aiming at the constrained power allocation problem widely studied in smart grid, with the cooperative control algorithm of continuous multi-agent system, this paper proposed a distributed optimization allocation strategy, which is free by the initial state. The proposed distributed algorithm implements parameterization by adding auxiliary variables. In the iterative process, the algorithm only needs to know the state of the distributed power supply of the neighbor, and finally solve the global optimal solution of the system. The simulations prove that the proposed scheme can effectively improve the economic dispatch performance. Furthermore, comparing to the existing algorithm, the proposed algorithm achieves faster optimal solution.
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