Brief paper: Optimal probability density function control for NARMAX stochastic systems
Automatica (Journal of IFAC)
Adaptive Tracking Control for the Output PDFs Based on Dynamic Neural Networks
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Brief paper: Observer-based networked control for continuous-time systems with random sensor delays
Automatica (Journal of IFAC)
International Journal of Systems Science
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IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Circuits and Systems Part I: Regular Papers
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IEEE Transactions on Neural Networks
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CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
International Journal of Systems, Control and Communications
International Journal of Systems, Control and Communications
Statistic tracking control: a multi-objective optimization algorithm
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
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ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Output PDF shaping of singular weights system: monotonical performance design
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
An entropy approach to filtering for networked control systems
International Journal of Computer Applications in Technology
Integrated Computer-Aided Engineering
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This paper presents a pseudo proportional-integral-derivative (PID) tracking control strategy for general non-Gaussian stochastic systems based on a linear B-spline model for the output probability density functions (PDFs). The objective is to control the conditional PDFs of the system output to follow a given target function. Different from existing methods, the control structure (i.e., the PID) is imposed before the output PDF controller design. Following the linear B-spline approximation on the measured output PDFs, the concerned problem is transferred into the tracking of given weights which correspond to the desired PDF. For systems with or without model uncertainties, it is shown that the solvability can be casted into a group of matrix inequalities. Furthermore, an improved controller design procedure based on the convex optimization is proposed which can guarantee the required tracking convergence with an enhanced robustness. Simulations are given to demonstrate the efficiency of the proposed approach and encouraging results have been obtained.