CAOC: Cooperative adaptive optimal control algorithm for networked direct current servo systems

What is it about?

This letter proposes a novel cooperative adaptive optimal control (CAOC) algorithm for networked direct current servo (DCS) systems to achieve tracking synchronization in a cooperative system, where the leader generates the desired speed and the DCS followers track its output and synchronize with their own neighbors according to the communication graph topology in real time.

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Why is it important?

As consensus tracking error dynamics is affected by the control inputs of the neighboring agents, the cost function for each agent includes not only its consensus tracking error and energy, but also the energies of the neighbors. Firstly, based on the Lyapunov theory and backstepping techniques, we design feedforward controllers that generate augmented control inputs to transform local consensus tracking dynamics in strict feedback form into affine form. Secondly, based on adaptive dynamic programming (ADP), we design the CAOC algorithm to minimize the performance index function. Finally, we conduct the simulation and experiment on the STM32F103 microcontrollers to validate the effectiveness of the proposed algorithm.