Huyen Dinh | Searcharxiv

arXiv2013

Approximate Optimal Trajectory Tracking for Continuous Time Nonlinear Systems

Approximate dynamic programming has been investigated and used as a method to approximately solve optimal regulation problems. However, the extension of this technique to optimal tracking problems for continuous time nonlinear systems has remained a non-trivial open problem. The control development in this paper guarantees ultimately bounded tracking of a desired trajectory, while also ensuring that the controller converges to an approximate optimal policy.

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arXiv2013

Approximate optimal cooperative decentralized control for consensus in a topological network of agents with uncertain nonlinear dynamics

Efforts in this paper seek to combine graph theory with adaptive dynamic programming (ADP) as a reinforcement learning (RL) framework to determine forward-in-time, real-time, approximate optimal controllers for distributed multi-agent systems with uncertain nonlinear dynamics. A decentralized continuous time-varying control strategy is proposed, using only local communication feedback from two-hop neighbors on a communication topology that has a spanning tree. An actor-critic-identifier architecture is proposed that employs a nonlinear state derivative estimator to estimate the unknown dynamics online and uses the estimate thus obtained for value function approximation.

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