International Journal of Control, Automation and Systems 2017; 15(2): 883-891
Published online March 8, 2017
https://doi.org/10.1007/s12555-015-1432-1
© The International Journal of Control, Automation, and Systems
This research work proposes a full state systematic feedback control design method for some classes of non-linear systems which are forced to follow a specific desired trajectory, such as robotic systems, using uncertain polytopic linear parameter-varying (LPV) modelling approach. An LPV representation of the system is generated from linearization of its usual Lagrangian equation about a desired state trajectory and is reduced to an uncertain polytopic one. A vector of scheduling signals from the desired trajectory information is produced to construct the LPV model. The control gain matrix is derived by solving a set of linear matrix inequalities (LMIs) that returns the sufficiently small value of the time derivative of the Lyapunov function. A sufficient condition is proposed to guarantee the asymptotic stability of the closed-loop LPV systems against the uncertainties on the vertices. The proposed scheme is applied to controller synthesis of a two-degree-of-freedom robotic manipulator trajectory tracking problem."
Keywords LMI, LPV system, nonlinear systems, polytopic representation, robot manipulator, robust design.
International Journal of Control, Automation and Systems 2017; 15(2): 883-891
Published online April 1, 2017 https://doi.org/10.1007/s12555-015-1432-1
Copyright © The International Journal of Control, Automation, and Systems.
Mohammad Bagher Abolhasani Jabali and Mohammad Hosein Kazemi*
Shahed University
This research work proposes a full state systematic feedback control design method for some classes of non-linear systems which are forced to follow a specific desired trajectory, such as robotic systems, using uncertain polytopic linear parameter-varying (LPV) modelling approach. An LPV representation of the system is generated from linearization of its usual Lagrangian equation about a desired state trajectory and is reduced to an uncertain polytopic one. A vector of scheduling signals from the desired trajectory information is produced to construct the LPV model. The control gain matrix is derived by solving a set of linear matrix inequalities (LMIs) that returns the sufficiently small value of the time derivative of the Lyapunov function. A sufficient condition is proposed to guarantee the asymptotic stability of the closed-loop LPV systems against the uncertainties on the vertices. The proposed scheme is applied to controller synthesis of a two-degree-of-freedom robotic manipulator trajectory tracking problem."
Keywords: LMI, LPV system, nonlinear systems, polytopic representation, robot manipulator, robust design.
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