We study the decentralized event-driven control problem of nonlinear dynamical systems with mismatched interconnections and asymmetric input constraints. To begin with, by introducing a discounted cost function for ea...
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We study the decentralized event-driven control problem of nonlinear dynamical systems with mismatched interconnections and asymmetric input constraints. To begin with, by introducing a discounted cost function for each auxiliary subsystem, we transform the decentralizedevent-driven constrained control problem into a group of nonlinear H-2-constrained optimal control problems. Then, we develop the event-driven Hamilton-Jacobi-Bellman equations (ED-HJBEs), which arise in the nonlinear H-2-constrained optimal control problems. Meanwhile, we demonstrate that all the solutions of the ED-HJBEs together keep the overall system stable in the sense of uniform ultimate boundedness (UUB). To solve the ED-HJBEs, we build a critic-only architecture under the framework of adaptive critic designs. The architecture only employs critic neural networks and updates their weight vectors via the gradient descent method. After that, based on the Lyapunov approach, we prove that the UUB stability of all signals in the closed-loop auxiliary subsystems is assured. Finally, simulations of an illustrated nonlinear interconnected plant are provided to validate the present designs.
In this work, based on the adaptive critic learning algorithms and fuzzy logic systems, the decentralized optimal control problem for interconnected nonlinear systems with unmodeled dynamics is investigated by applyin...
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In this work, based on the adaptive critic learning algorithms and fuzzy logic systems, the decentralized optimal control problem for interconnected nonlinear systems with unmodeled dynamics is investigated by applying a mixed data and eventdriven method. By introducing a modified performance index function for each auxiliary subsystem, the considered control problem of the whole interconnected system can be transformed into a group of event-driven optimal control problems of the auxiliary subsystems. Then, a three-layer neural network (NN) identifier is employed to reconstruct the completely unknown functions. Based on the obtained data-driven model, a single-critic NN is developed to solve the modified HJB equation. Meanwhile, a novel adaptive controller is designed by fuzzy logic systems to deal with the dynamical uncertainties cased by the unmodeled dynamics. Finally, a robot arm example is given to verify the effectiveness of the proposed control method.
This paper proposes a novel locomotion control scheme of centipede-like multi legged robot, which is called Follow-the-Contact-Point (FCP) gait control. A centipede-like multi-legged robot is composed of segmented tru...
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ISBN:
(纸本)9789814327978
This paper proposes a novel locomotion control scheme of centipede-like multi legged robot, which is called Follow-the-Contact-Point (FCP) gait control. A centipede-like multi-legged robot is composed of segmented trunks which have a pair of legs and are connected with fore and/or rear ones by joints. This control scheme realizes locomotion control of multi-legged robot on uneven terrain with perfectly decentralized mariner. The main concept of the control scheme is to relay the contact points from the fore leg to the rear leg. By creating contact points of the first legs on the environment adequately, the robot can climb over obstacles and be navigated successfully. Finally, the result of physical simulation of 20-legged robot shows the availability of the proposed method.
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