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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.
Daniel Zhang andColleen 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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Daniel Zhang, 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