Jun Xu

Publications (6)0.75 Total impact

• Article: Parameters estimation of hinging hyperplanes using median squared error criterion

  Xiaolin Huang, Jun Xu, Shuning Wang
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  ABSTRACT: This paper considers parameter estimation for nonlinear model using median squared error (MSE) criterion, which is limited to linear model in the past. It is shown that applying MSE, the essence of estimating parameters for hinging hyperplanes (HH) and linear model are the same. Motivated by this fact, MSE estimation is discussed for HH. A local optimality condition is given and based on this condition, an algorithm using linear programming technique is proposed. Numerical experiments show the good performance of the proposed estimation strategy and algorithm. KeywordsHinging hyperplane–identification methods–piecewise-linear–robust estimation
  International Journal of Control Automation and Systems 05/2012; 9(4):627-635. · 0.75 Impact Factor
• Article: Nonlinear system identification with continuous piecewise linear neural network.

  Xiaolin Huang, Jun Xu, Shuning Wang
  Neurocomputing. 01/2012; 77:167-177.
• Article: The hill detouring method for minimizing hinging hyperplanes functions.

  Xiaolin Huang, Jun Xu, Xiaomu Mu, Shuning Wang
  Computers & OR. 01/2012; 39:1763-1770.
• Conference Proceeding: Operation optimization for centrifugal chiller plants using continuous piecewise linear programming

  Xiaolin Huang, Jun Xu, Shuning Wang
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  ABSTRACT: Centrifugal chiller plants (CCP) are widely used in air conditioning systems, its operation optimization can save lots of energy and has great significance in environmental protection. The optimization is a large-scale nonlinear problem and there is no practical algorithm until now. This paper proposes a new method to do this operation optimization using continuous piecewise linear programming (CPWLP). The main idea is transforming the nonlinear problem into a series of linear programmings by approximating the original system using piecewise linear representation. For CPWLP, some properties are discussed and an algorithm is given. Using CPWLP, CCP system is optimized and its energy performance is improved significantly.
  Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on; 11/2010
• Source

  Available from: ntnu.no

  Conference Proceeding: Nonlinear model predictive control using adaptive hinging hyperplanes model.

  Jun Xu, Xiaolin Huang, Shuning Wang
  Proceedings of the 48th IEEE Conference on Decision and Control, CDC 2009, combined withe the 28th Chinese Control Conference, December 16-18, 2009, Shanghai, China; 01/2009
• Article: Adaptive hinging hyperplanes and its applications in dynamic system identification

  Jun Xu, Xiaolin Huang, Shuning Wang
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  ABSTRACT: The model of adaptive hinging hyperplanes (AHH) is proposed in this paper. It is based on multivariate adaptive regression splines (MARS) and generalized hinging hyperplanes (GHH) and shares attractive properties of the two. By making a modification to the basis function of MARS, AHH shows linear property in each subregion. The AHH model is actually a special case of the GHH model, which has a universal representation capability for continuous piecewise linear functions. The approximation ability of the AHH model is proved. The AHH algorithm is developed similar to the MARS algorithm. It is adaptive and can be executed efficiently, hence has power and flexibility to model unknown relationships. The AHH procedure is applied to identifying two dynamic systems and its potential is illustrated.
  Automatica.