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Derong Liu

Bio: Derong Liu is an academic researcher from Guangdong University of Technology. The author has contributed to research in topics: Optimal control & Artificial neural network. The author has an hindex of 77, co-authored 608 publications receiving 19399 citations. Previous affiliations of Derong Liu include University of Illinois at Chicago & University of Science and Technology Beijing.


Papers
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Journal ArticleDOI
TL;DR: Some recent research trends within the field of adaptive/approximate dynamic programming (ADP), including the variations on the structure of ADP schemes, the development of ADPs algorithms and applications, and many recent papers have provided convergence analysis associated with the algorithms developed.
Abstract: In this article, we introduce some recent research trends within the field of adaptive/approximate dynamic programming (ADP), including the variations on the structure of ADP schemes, the development of ADP algorithms and applications of ADP schemes. For ADP algorithms, the point of focus is that iterative algorithms of ADP can be sorted into two classes: one class is the iterative algorithm with initial stable policy; the other is the one without the requirement of initial stable policy. It is generally believed that the latter one has less computation at the cost of missing the guarantee of system stability during iteration process. In addition, many recent papers have provided convergence analysis associated with the algorithms developed. Furthermore, we point out some topics for future studies.

738 citations

Journal ArticleDOI
TL;DR: The near-optimal control problem for a class of nonlinear discrete-time systems with control constraints is solved by iterative adaptive dynamic programming algorithm.
Abstract: In this paper, the near-optimal control problem for a class of nonlinear discrete-time systems with control constraints is solved by iterative adaptive dynamic programming algorithm. First, a novel nonquadratic performance functional is introduced to overcome the control constraints, and then an iterative adaptive dynamic programming algorithm is developed to solve the optimal feedback control problem of the original constrained system with convergence analysis. In the present control scheme, there are three neural networks used as parametric structures for facilitating the implementation of the iterative algorithm. Two examples are given to demonstrate the convergence and feasibility of the proposed optimal control scheme.

574 citations

Journal ArticleDOI
TL;DR: It is shown that the iterative performance index function is nonincreasingly convergent to the optimal solution of the Hamilton-Jacobi-Bellman equation and it is proven that any of the iteratives control laws can stabilize the nonlinear systems.
Abstract: This paper is concerned with a new discrete-time policy iteration adaptive dynamic programming (ADP) method for solving the infinite horizon optimal control problem of nonlinear systems. The idea is to use an iterative ADP technique to obtain the iterative control law, which optimizes the iterative performance index function. The main contribution of this paper is to analyze the convergence and stability properties of policy iteration method for discrete-time nonlinear systems for the first time. It shows that the iterative performance index function is nonincreasingly convergent to the optimal solution of the Hamilton-Jacobi-Bellman equation. It is also proven that any of the iterative control laws can stabilize the nonlinear systems. Neural networks are used to approximate the performance index function and compute the optimal control law, respectively, for facilitating the implementation of the iterative ADP algorithm, where the convergence of the weight matrices is analyzed. Finally, the numerical results and analysis are presented to illustrate the performance of the developed method.

535 citations

Journal ArticleDOI
TL;DR: The purpose of this paper is to provide a comprehensive review of the research on stability of continuous-time recurrent Neural networks, including Hopfield neural networks, Cohen-Grossberg neural networks and related models.
Abstract: Stability problems of continuous-time recurrent neural networks have been extensively studied, and many papers have been published in the literature The purpose of this paper is to provide a comprehensive review of the research on stability of continuous-time recurrent neural networks, including Hopfield neural networks, Cohen-Grossberg neural networks, and related models Since time delay is inevitable in practice, stability results of recurrent neural networks with different classes of time delays are reviewed in detail For the case of delay-dependent stability, the results on how to deal with the constant/variable delay in recurrent neural networks are summarized The relationship among stability results in different forms, such as algebraic inequality forms, \(M\) -matrix forms, linear matrix inequality forms, and Lyapunov diagonal stability forms, is discussed and compared Some necessary and sufficient stability conditions for recurrent neural networks without time delays are also discussed Concluding remarks and future directions of stability analysis of recurrent neural networks are given

515 citations

BookDOI
17 Dec 2012
TL;DR: Feedback control of dynamic systems 6th solution PDF feedback control of Dynamic Systems as discussed by the authors 6th solutions PDF feedback feedback control dynamic systems 5th edition solutions PDF solutions manual feedback control Dynamic Systems 3rd edition solution PDF dynamic programming and optimal control and dynamic programming & optimal control solution manual PDF learning microsoft windows server 2012 dynamic access control PDF data-variant kernel analysis adaptive and cognitive dynamic systems signal processing learning communications and control PDF
Abstract: feedback control of dynamic systems 6th solution PDF feedback control of dynamic systems 6th solutions PDF feedback control of dynamic systems 5th edition pdf PDF feedback control of dynamic systems solution PDF feedback control of dynamic systems 7th edition PDF feedback control of dynamic systems 6th edition PDF feedback control of dynamic systems solutions PDF feedback control of dynamic systems solution manual PDF feedback control of dynamic systems solutions manual PDF feedback control dynamic systems 5th edition solutions PDF solutions manual feedback control of dynamic systems PDF feedback control of dynamic systems solution manual 6th PDF feedback control of dynamic systems solutions manual 5th PDF feedback control of dynamic systems franklin solutions PDF feedback control of dynamic systems solutions 6th edition PDF feedback control of dynamic systems 6th edition solutions PDF solutions feedback control dynamic systems 6th edition PDF feedback control of dynamic systems 6th solutions manual PDF feedback control of dynamic systems 6th edition solution manual PDF feedback control of dynamic systems franklin 5th edition solution PDF dynamic programming and optimal control PDF dynamic programming & optimal control vol i PDF dynamic programming and optimal control solution manual PDF learning microsoft windows server 2012 dynamic access control PDF data-variant kernel analysis adaptive and cognitive dynamic systems signal processing learning communications and control PDF

487 citations


Cited by
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Proceedings Article
01 Jan 1991
TL;DR: It is concluded that properly augmented and power-controlled multiple-cell CDMA (code division multiple access) promises a quantum increase in current cellular capacity.
Abstract: It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

2,951 citations

Journal ArticleDOI
TL;DR: This paper focuses on the stability analysis for switched linear systems under arbitrary switching, and highlights necessary and sufficient conditions for asymptotic stability.
Abstract: During the past several years, there have been increasing research activities in the field of stability analysis and switching stabilization for switched systems. This paper aims to briefly survey recent results in this field. First, the stability analysis for switched systems is reviewed. We focus on the stability analysis for switched linear systems under arbitrary switching, and we highlight necessary and sufficient conditions for asymptotic stability. After a brief review of the stability analysis under restricted switching and the multiple Lyapunov function theory, the switching stabilization problem is studied, and a variety of switching stabilization methods found in the literature are outlined. Then the switching stabilizability problem is investigated, that is under what condition it is possible to stabilize a switched system by properly designing switching control laws. Note that the switching stabilizability problem has been one of the most elusive problems in the switched systems literature. A necessary and sufficient condition for asymptotic stabilizability of switched linear systems is described here.

2,470 citations