Changyin Sun

Publications (38)11.27 Total impact

• Article: Data-based intelligent modeling and control for nonlinear systems

  Chaoxu Mu, Changyin Sun
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  ABSTRACT: With the ever increasing complexity of industrial systems, model-based control has encountered difficulties and is facing problems, while the interest in data-based control has been booming. This paper gives an overview of data-based control, which divides it into two subfields, intelligent modeling and direct controller design. In the two subfields, some important methods concerning data-based control are intensively investigated. Within the framework of data-based modeling, main modeling technologies and control strategies are discussed, and then fundamental concepts and various algorithms are presented for the design of a data-based controller. Finally, some remaining challenges are suggested. Keywordsoffline and online data–intelligent modeling–data-based control–perspective
  Frontiers of Electrical and Electronic Engineering in China 04/2012; 6(2):291-299.
• Article: Delay-dependent robust stability criteria for delay neural networks with linear fractional uncertainties

  Tao Li, Lei Guo, Lingyao Wu, Changyin Sun
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  ABSTRACT: This article investigates the problem of robust stability for neural networks with time-varying delays and parameter uncertainties of linear fractional form. By introducing a new Lyapunov-Krasovskii functional and a tighter inequality, delay-dependent stability criteria are established in term of linear matrix inequalities (LMIs). It is shown that the obtained criteria can provide less conservative results than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed approach.
  International Journal of Control Automation and Systems 04/2012; 7(2):281-287. · 0.75 Impact Factor
• Article: Impulsive controller design for singular networked control systems with packet dropouts

  Xianlin Zhao, Shumin Fei, Changyin Sun
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  ABSTRACT: This paper considers the problem of impulsive time-delay control for singular networked impulsive control systems(SNICSs) and uncertain SNICSs both with network-induced delay and packet dropouts. The parameter uncertainty is assumed to be norm bounded. The problem to be addressed is the design of robust impulsive time-delay feedback controllers such that the exponential stability of the resulting closed-loop system is guaranteed for admissible uncertainties. By applying Lyapunov function theory and Halanay Lemma, impulsive time-delay controller is derived through solving LMIs. Numerical examples are provided to demonstrate the application of the proposed method.
  International Journal of Control Automation and Systems 04/2012; 7(6):1020-1025. · 0.75 Impact Factor
• Article: An Analysis of a Neural Dynamical Approach to Solving Optimization Problems

  Changyin Sun, Youshen Xia
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  ABSTRACT: Recently, a neural dynamical approach to solving linearly constrained variational inequality problems is presented, and its stability and convergence are conjectured by simulation. This technical note analyzes the global stability and convergence of the neural dynamical approach. Theoretically, it is shown that the neural dynamical approach is convergent globally to a solution when the nonlinear mapping is monotone at the solution. Unlike existing convergence results of neural dynamical methods for solving linearly or nonlinearly variational inequalities, our main results don't assume the differentiability condition of the nonlinear mapping. Therefore, the neural dynamical approach can be further guaranteed to solve linearly constrained monotone variational inequality problems with a non-smooth mapping. Comparsions and examples illustrative significance of the obtained results on non-smooth mapping.
  IEEE Transactions on Automatic Control 09/2009; · 2.11 Impact Factor
• Article: A novel neural dynamical approach to convex quadratic program and its efficient applications.

  Youshen Xia, Changyin Sun
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  ABSTRACT: This paper proposes a novel neural dynamical approach to a class of convex quadratic programming problems where the number of variables is larger than the number of equality constraints. The proposed continuous-time and proposed discrete-time neural dynamical approach are guaranteed to be globally convergent to an optimal solution. Moreover, the number of its neurons is equal to the number of equality constraints. In contrast, the number of neurons in existing neural dynamical methods is at least the number of the variables. Therefore, the proposed neural dynamical approach has a low computational complexity. Compared with conventional numerical optimization methods, the proposed discrete-time neural dynamical approach reduces multiplication operation per iteration and has a large computational step length. Computational examples and two efficient applications to signal processing and robot control further confirm the good performance of the proposed approach.
  Neural networks: the official journal of the International Neural Network Society 05/2009; 22(10):1463-70. · 1.88 Impact Factor
• Conference Proceeding: Improved delay-dependent stability criteria for neural networks with time-varying delay

  Jianjiang Yu, Tao Li, Changyin Sun
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  ABSTRACT: In this paper, an augmented Lyapunov functional, which takes an integral term of state vector into account, is introduced. Owing to the functional, an improved delay-dependent asymptotic stability criterion for delay neural networks is derived in term of LMIs. Moreover, the result is also extended to rate-independent stability criteria for unknown time-varying delay. Finally, numerical examples are given to illustrate the effectiveness of our methods and improvement over the existing ones.
  Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on; 07/2008
• Article: LMI-based asymptotic stability analysis of neural networks with time-varying delays.

  Tao Li, Changyin Sun, Xianlin Zhao, Chong Lin
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  ABSTRACT: The problem of the global asymptotic stability for a class of neural networks with time-varying delays is investigated in this paper, where the activation functions are assumed to be neither monotonic, nor differentiable, nor bounded. By constructing suitable Lyapunov functionals and combining with linear matrix inequality (LMI) technique, new global asymptotic stability criteria about different types of time-varying delays are obtained. It is shown that the criteria can provide less conservative result than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed approach.
  International Journal of Neural Systems 07/2008; 18(3):257-65. · 4.28 Impact Factor
• Conference Proceeding: Inverse system identification of nonlinear systems using least square support vector machine based on FCM clustering.

  Chaoxu Mu, Hua Liang, Changyin Sun
  Proceedings of the International Joint Conference on Neural Networks, IJCNN 2008, part of the IEEE World Congress on Computational Intelligence, WCCI 2008, Hong Kong, China, June 1-6, 2008; 01/2008
• Article: Implementation of hybrid short-term load forecasting system with analysis of temperature sensitivities.

  Changyin Sun, Jinya Song, Linfeng Li, Ping Ju
  Soft Comput. 01/2008; 12:633-638.
• Conference Proceeding: Inverse System Identification of Nonlinear Systems Using LSSVM Based on Clustering.

  Changyin Sun, Chaoxu Mu, Hua Liang
  Advances in Neural Networks - ISNN 2008, 5th International Symposium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part I; 01/2008
• Conference Proceeding: Clustering with a Weighted Sum Validity Function Using a Niching PSO Algorithm

  Changyin Sun, Hua Liang, Linfeng Li, Derong Liu
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  ABSTRACT: In this paper, we will consider an objective function called the weighted sum validity function (WSVF), which is a weighted sum of several normalized cluster validity functions. In contrast to optimization techniques intended to find a single, global solution in a problem domain, niching techniques have the ability to locate multiple solutions in multimodal domains. Hence, a niching binary particle swarm optimization (NBPSO) approach is developed for automatically constructing the proper number of clusters as well as appropriate partitioning of the data set. We also hybridize the NBPSO method with the k-means algorithm to optimize the WSVF automatically. In experiments, we show the effectiveness of the WSVF and the validity of the NBPSO. In comparison with other related PSO, the NBPSO can consistently and efficiently converge to the optimum corresponding to the given data in concurrence with the convergence result. The WSVF is found generally able to improve the confidence of clustering solutions and achieve more accurate and robust results.
  Networking, Sensing and Control, 2007 IEEE International Conference on; 05/2007
• Conference Proceeding: Exponential Stability of Discrete-Time Cohen-Grossberg Neural Networks with Delays.

  Changyin Sun, Liang Ju, Hua Liang, Shoulin Wang
  Advances in Neural Networks - ISNN 2007, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part I; 01/2007
• Conference Proceeding: Nonlinear Systems Modeling Using LS-SVM with SMO-Based Pruning Methods.

  Changyin Sun, Jinya Song, Guofang Lv, Hua Liang
  Advances in Neural Networks - ISNN 2007, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part I; 01/2007
• Chapter: Dynamics of General Neural Networks with Distributed Delays

  Changyin Sun, Linfeng Li
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  ABSTRACT: The paper introduces a general class of neural networks with periodic inputs. By constructing a Lyapunov functional and the Halanay-type inequality separately, we obtain easily verifiable sufficient conditions ensuring that every solutions of the delayed neural networks converge exponentially to the unique periodic solutions. The results obtained can be regarded as a generalization to the discrete case of previous results.
  05/2006: pages 135-140;
• Conference Proceeding: Fuzzy Modeling Technique with PSO Algorithm for Short-Term Load Forecasting.

  Changyin Sun, Ping Ju, Linfeng Li
  Fuzzy Systems and Knowledge Discovery, Third International Conference, FSKD 2006, Xi'an, China, September 24-28, 2006, Proceedings; 01/2006
• Chapter: Globally Attractive Periodic Solutions of Continuous-Time Neural Networks and Their Discrete-Time Counterparts

  Changyin Sun, Liangzhen Xia, Chunbo Feng
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  ABSTRACT: In this paper, discrete-time analogues of continuous-time neural networks with continuously distributed delays and periodic inputs are investigated without assuming Lipschitz conditions on the activation functions. The discrete-time analogues are considered to be numerical discretizations of the continuous-time networks and we study their dynamical characteristics. By employing Halanay-type inequality, we obtain easily verifiable sufficient conditions ensuring that every solutions of the discrete-time analogue converge exponentially to the unique periodic solutions. It is shown that the discrete-time analogues inherit the periodicity of the continuous-time networks. The results obtained can be regarded as a generalization to the discontinuous case of previous results established for delayed neural networks possessing smooth neuron activation.
  05/2005: pages 277-286;
• Conference Proceeding: Neural Networks for Nonconvex Nonlinear Programming Problems: A Switching Control Approach.

  Changyin Sun, Chun-Bo Feng
  Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30 - June 1, 2005, Proceedings, Part I; 01/2005
• Conference Proceeding: Globally Attractive Periodic Solutions of Continuous-Time Neural Networks and Their Discrete-Time Counterparts.

  Changyin Sun, Liangzhen Xia, Chun-Bo Feng
  Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30 - June 1, 2005, Proceedings, Part I; 01/2005
• Conference Proceeding: Next Day Load Forecasting Using SVM.

  Xunming Li, Dengcai Gong, Linfeng Li, Changyin Sun
  Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30 - June 1, 2005, Proceedings, Part III; 01/2005
• Conference Proceeding: A new condition for the global robust exponential periodicity of interval neural networks with delays

  Changyin Sun, Derong Liu, Chun-Bo Feng
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  ABSTRACT: We study the robust exponential periodicity of a class of interval-delayed neural networks. A new condition ensuring the existence, uniqueness and global robust exponential stability of the periodic solution of interval-delayed neural networks with periodic input is established.
  Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on; 08/2004