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SUBOPTIMAL SPEED CONTROL BY MULTI-AGENT SYSTEMS UNDER INFORMATION CONSTRAINTS

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A robust suboptimal control solution of the speed control is proposed for multi-agent systems described by nonstationary nonlinear differential equations with uncertain parameters, disturbances, communication delay, and possible information constraints in the measurement channels. To compensate for disturbances, the method of auxiliary loop method is used with the loop presented by a parallel reference model for each agent. Classical methods of optimal control are used for speed control, and therefore calculation of optimal control may be carried out with the use of standard packages of existing software, e.g. MatLab. Simulation results are presented to demonstrate the effectiveness of the proposed scheme under uncertainties, delay, and information constraints. The results show that the control accuracy can be improved by increasing the gain in the control law, reduce the high frequency gain in the auxiliary loop, and increase the feedback gain of the observer.

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