The most widely applied doubly-fed induction generator (DFIG) leads to insufficient frequency regulation ability of power system. The virtual inertia control can adjust the active power of DFIG according to frequency ...
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The most widely applied doubly-fed induction generator (DFIG) leads to insufficient frequency regulation ability of power system. The virtual inertia control can adjust the active power of DFIG according to frequency fluctuation. However, the frequent changes in power flow and operating point bring great challenges to traditional virtual inertia controller with fixed parameters. direct heuristic dynamic programming (direct HDP) based control parameter regulator is proposed in this paper to obtain the optimal control parameters when the operation condition changes. Compared with the initial parameters, the response has been significantly improved after adaptive optimization by the proposed method when the system operating point changes. (C) 2022 Published by Elsevier Ltd.
In this paper, we aim to solve the optimal tracking control problem for the Henon Mapping chaotic system using the direct heuristic dynamic programming (DHDP) setting with filtered tracking error. The fuzzy logic syst...
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In this paper, we aim to solve the optimal tracking control problem for the Henon Mapping chaotic system using the direct heuristic dynamic programming (DHDP) setting with filtered tracking error. The fuzzy logic system is used to approximate the long-term utility function. Compared with the results for chaotic discrete-time system, the cost of the controller is reduced. The Lyapunov analysis approach is utilized to prove the stability of the chaotic system. It is shown that the tracking error, the adaptation law and the control input retain the property of uniformly ultimate boundedness. A simulation example is given to demonstrate the effectiveness of the proposed approach.
For discrete-time unknown nonlinear dynamic systems, an online optimal tracking control scheme is developed in this paper, which is implemented by direct heuristic dynamic programming (HDP). To start with, a solution ...
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ISBN:
(纸本)9798331540845;9789887581598
For discrete-time unknown nonlinear dynamic systems, an online optimal tracking control scheme is developed in this paper, which is implemented by direct heuristic dynamic programming (HDP). To start with, a solution procedure is presented for tracking problems of discrete-time nonlinear systems. Then, the basic structure and mechanism of the direct HDP algorithm are described in detail, including the critic network and the action network. Moreover, based on the direct HDP algorithm, the implementation process of neural networks is provided. Finally, the direct HDP algorithm is applied to enable the original system to track the reference trajectory. The effectiveness of the algorithm is proved in solving tracking problems and online optimal tracking control is achieved.
In this paper a neural network-based approximate dynamicprogramming method, namely direct heuristic dynamic programming (direct HDP), is applied to power system stability control. direct HDP makes use of learning and...
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ISBN:
(纸本)9781424413799
In this paper a neural network-based approximate dynamicprogramming method, namely direct heuristic dynamic programming (direct HDP), is applied to power system stability control. direct HDP makes use of learning and approximation to address nonlinear system control problems under uncertainty. The contribution of the paper includes a convergence proof of the direct HDP algorithm using an LQR framework. Under this setting, the paper proposes a direct HDP learning control algorithm for a static var compensator (SVC) supplementary damping control in a standard benchmark power system. The results are used to evaluate the online learning ability of the proposed direct HDP controller, and also to demonstrate that the learning controller does converge to the theoretical limit as derived.
There has been a growing interest in the study of adaptive/approximate dynamicprogramming (ADP) in recent years. The ADP technique provides a powerful tool to understand and improve the principled technologies of mac...
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ISBN:
(纸本)9781467359252
There has been a growing interest in the study of adaptive/approximate dynamicprogramming (ADP) in recent years. The ADP technique provides a powerful tool to understand and improve the principled technologies of machine intelligence system. As one of the ADP algorithms based on adaptive critic neural networks (NNs), the direct heuristic dynamic programming (direct HDP) has demonstrated some successful applications in solving realistic engineering control problems. In this study, based on a three-network architecture in which the reinforcement signal is approximated by an additional NN, a novel integrated design method for intensified direct HDP is developed. The new design approach is implemented by using multiple PID neural networks (PIDNNs), which effectively takes into account structural knowledge of system states and control that are usually present in a physical system. By using a Lyapunov stability approach, a uniformly ultimately boundedness (UUB) result is proved for our PIDNNs-based intensified direct HDP learning controller. Furthermore, the learning and control performances of the proposed design is tested using the popular cart-pole example to illustrate the key ideas of this paper.
As an important class of approximate dynamicprogramming, the direct heuristic dynamic programming (DHDP) is discussed in this *** performs well due to its model-free online learning *** the classical DHDP is implemen...
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As an important class of approximate dynamicprogramming, the direct heuristic dynamic programming (DHDP) is discussed in this *** performs well due to its model-free online learning *** the classical DHDP is implemented with gradient-based adaptation learning algorithm of neural network, in this paper we present a design strategy of DHDP with a novel hybrid estimation of distribution algorithm for online learning and control, and the proposed design optimization method achieves the weight training of neural networks with faster convergence *** proposed approach can be viewed as an improvement for *** simulation is conducted on a practical system plant to test the online learning performance by using our ***, the simulation results show the effectiveness of our approach.
The direct heuristic dynamic programming (HDP) is used to handle the optimal tracking control for the Henon Mapping chaotic system. The fuzzy logic system (FLS) is applied to measure the long-term utility function. Ly...
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ISBN:
(纸本)9781479925384
The direct heuristic dynamic programming (HDP) is used to handle the optimal tracking control for the Henon Mapping chaotic system. The fuzzy logic system (FLS) is applied to measure the long-term utility function. Lyapunov analysis approach is utilized to assure the stability of the chaotic system. Results have proven that the tracking error, the adaptation law and the control input of the system retain uniform ultimate boundedness.
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