To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output err...To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.展开更多
By applying phase-only technique in array antenna pattern synthesis, antenna arrays can form desired patterns with the use of phase shifters only. A novel phase-only pattern synthesis algorithm is proposed for the pas...By applying phase-only technique in array antenna pattern synthesis, antenna arrays can form desired patterns with the use of phase shifters only. A novel phase-only pattern synthesis algorithm is proposed for the passive phased array seeker. This algorithm synthesizes the main beam of the antenna pattern through least-squares approximation, thus minimizing the errors between the actual and the desired main beams. The synthesis problem can be solved by applying gradient-descent optimization. The item for suppressing side lobes is added to the above synthesis problem. To obtain a side lobe level as low as possible, the algorithm assigns different weights to different directions in the side lobe region. The algorithm is run repeatedly and the weights are adjusted adaptively according to the normalized power in the side lobe directions. Detailed examples are presented to demonstrate the accuracy and effectiveness of the proposed approach.展开更多
This paper investigates the cooperative adaptive optimal output regulation problem of continuous-time linear multi-agent systems.As the multi-agent system dynamics are uncertain,solving regulator equations and the cor...This paper investigates the cooperative adaptive optimal output regulation problem of continuous-time linear multi-agent systems.As the multi-agent system dynamics are uncertain,solving regulator equations and the corresponding algebraic Riccati equations is challenging,especially for high-order systems.In this paper,a novel method is proposed to approximate the solution of regulator equations,i.e.,gradient descent method.It is worth noting that this method obtains gradients through online data rather than model information.A data-driven distributed adaptive suboptimal controller is developed by adaptive dynamic programming,so that each follower can achieve asymptotic tracking and disturbance rejection.Finally,the effectiveness of the proposed control method is validated by simulations.展开更多
文摘To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.
基金supported by the National Natural Science Foundation of China(1127301761471196)
文摘By applying phase-only technique in array antenna pattern synthesis, antenna arrays can form desired patterns with the use of phase shifters only. A novel phase-only pattern synthesis algorithm is proposed for the passive phased array seeker. This algorithm synthesizes the main beam of the antenna pattern through least-squares approximation, thus minimizing the errors between the actual and the desired main beams. The synthesis problem can be solved by applying gradient-descent optimization. The item for suppressing side lobes is added to the above synthesis problem. To obtain a side lobe level as low as possible, the algorithm assigns different weights to different directions in the side lobe region. The algorithm is run repeatedly and the weights are adjusted adaptively according to the normalized power in the side lobe directions. Detailed examples are presented to demonstrate the accuracy and effectiveness of the proposed approach.
基金Supported by the Science and Technology Innovation 2030 New Generation Artificial Intelligence Major Project(2018AAA0100902)the National Key Research and Development Program of China(2019YFB1705800)the National Natural Science Foundation of China(61973270)。
基金supported in part by the National Natural Science Foundation of China under Grant No.62373090the U.S.National Science Foundation under Grant No.CNS-2227153.
文摘This paper investigates the cooperative adaptive optimal output regulation problem of continuous-time linear multi-agent systems.As the multi-agent system dynamics are uncertain,solving regulator equations and the corresponding algebraic Riccati equations is challenging,especially for high-order systems.In this paper,a novel method is proposed to approximate the solution of regulator equations,i.e.,gradient descent method.It is worth noting that this method obtains gradients through online data rather than model information.A data-driven distributed adaptive suboptimal controller is developed by adaptive dynamic programming,so that each follower can achieve asymptotic tracking and disturbance rejection.Finally,the effectiveness of the proposed control method is validated by simulations.
