H.3.9. Problem Solving, Control Methods, and Search
Zahra Jahan; Abbas Dideban; Farzaneh Tatari
Abstract
This paper introduces an adaptive optimal distributed algorithm based on event-triggered control to solve multi-agent discrete-time zero-sum graphical games for unknown nonlinear constrained-input systems with external disturbances. Based on the value iteration heuristic dynamic programming, the proposed ...
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This paper introduces an adaptive optimal distributed algorithm based on event-triggered control to solve multi-agent discrete-time zero-sum graphical games for unknown nonlinear constrained-input systems with external disturbances. Based on the value iteration heuristic dynamic programming, the proposed algorithm solves the event-triggered coupled Hamilton-Jacobi-Isaacs equations assuming unknown dynamics to develop distributed optimal controllers and satisfy leader-follower consensus for agents interacting on a communication graph. The algorithm is implemented using the actor-critic neural network, and unknown system dynamics are approximated using the identifier network. Introducing and solving nonlinear zero-sum discrete-time graphical games in the presence of unknown dynamics, control input constraints and external disturbances, differentiate this paper from the previously published works. Also, the control input, external disturbance, and the neural network's weights are updated aperiodic and only at the triggering instants to simplify the computational process. The closed-loop system stability and convergence to the Nash equilibrium are proven. Finally, simulation results are presented to confirm theoretical findings.
H.3.9. Problem Solving, Control Methods, and Search
Heydar Toossian Shandiz; Mohsen Erfan Hajipour; Amir Ali Bagheri
Abstract
The aim of this paper is to create an efficient controller that can precisely track the position of autonomous surface vessels by utilizing the dynamic inversion control technique. One of the key objectives of this controller is to mitigate or eliminate the effects of environmental disturbances like ...
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The aim of this paper is to create an efficient controller that can precisely track the position of autonomous surface vessels by utilizing the dynamic inversion control technique. One of the key objectives of this controller is to mitigate or eliminate the effects of environmental disturbances like wind, waves, and water flow. On the other hand, intelligent methods are used to remove disturbances and fixing modeling errors. These methods include the use of fuzzy methods to adjust the control parameters in the linear controller used in the dynamic inversion controller and the use of perceptron neural network along with the dynamic inversion controller. The effectiveness of the proposed methods is evaluated not only based on the step response but also on their ability to track a complex path. Finally, the proposed methods have been compared with one of the classic methods, namely the PID control. This evaluation provides insights into how the proposed methods fare in terms of both step response and trajectory tracking when compared to the traditional PID control approach.