Optimal control under communication constraints for multi-agent unmanned vehicles

Daniel Zhang; Colleen P. Bailey

doi:10.1117/12.2574176

20 September 2020 Optimal control under communication constraints for multi-agent unmanned vehicles

Daniel Zhang, Colleen P. Bailey

Proceedings Volume 11543, Artificial Intelligence and Machine Learning in Defense Applications II; 115430J (2020) https://doi.org/10.1117/12.2574176
Event: SPIE Security + Defence, 2020, Online Only

Abstract

This paper considers the linear quadratic regulator (LQR) optimal control problem of multi-agent unmanned vehicle systems under communication constraints with packet drops. The problem is formulated into a distributed optimization problem of minimizing a global cost function through the sum of local cost functions by using local information exchange. By utilizing a newly developed optimization technique, we propose a novel algorithm to solve the distributed LQR problem in a first order (gradient descent based) manner. Moreover, we adopt the key idea of virtualizing an extra node for each agent to store information from the previous step and create a fully distributed optimization algorithm. Extensive simulations demonstrate the efficacy and robustness of the proposed solution.

Conference Presentation

Citation Download Citation

Daniel Zhang and Colleen P. Bailey "Optimal control under communication constraints for multi-agent unmanned vehicles", Proc. SPIE 11543, Artificial Intelligence and Machine Learning in Defense Applications II, 115430J (20 September 2020); https://doi.org/10.1117/12.2574176

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