International Journal of Control, Automation and Systems 2020; 18(10): 2492-2508
Published online May 18, 2020
https://doi.org/10.1007/s12555-019-0650-z
© The International Journal of Control, Automation, and Systems
Using state observer has attracted a notable interest of researchers in the control community to provide an on-line state estimator for control systems instead of measuring them physically by sensors which is costly, inaccurate, and easy to contaminate by noise. Some challenges ahead to design state observer in control systems are using estimated data by an observer in the designed controller as well as the system stability analysis by using controller and observer simultaneously. This paper proposes the Fuzzy Adaptive Fixed-time Sliding Mode Control (FAFSMC) technique for trajectory tracking of a class of high-order nonlinear systems with mismatched external disturbances and uncertainties. Meanwhile, the fixed-time state observer is proposed to incorporate with the controller for estimating the unmeasured even states (velocity) and providing on-line data in the controller. A proper candidate Lyapunov function is defined to verify the system’s global fixed-time stability by considering designed control law, state observer term, and adaptive law, simultaneously. The simulation results of three simulation examples, ship course system, two-link robotic manipulator, and three-link robotic manipulator, are carried out in Simulink/MATLAB to reveal the effectiveness of the proposed FAFSMC scheme compared with the other three conventional methods for solving trajectory tracking problem. Two performance criteria, Integral of the Square Value (ISV) and Integral of the Absolute value of the Error (IAE), are used to make a comprehensive comparison among the proposed FAFSMC method with state observer and the other three methods.
Download: http://link.springer.com/article/10.1007/s12555-019-0650-z
Keywords Adaptive, fixed-time, fuzzy, mismatched uncertainties, sliding mode, state observer.
International Journal of Control, Automation and Systems 2020; 18(10): 2492-2508
Published online October 1, 2020 https://doi.org/10.1007/s12555-019-0650-z
Copyright © The International Journal of Control, Automation, and Systems.
Ali Soltani Sharif Abadi*, Pooyan Alinaghi Hosseinabadi, and Saad Mekhilef
Yazd University
Using state observer has attracted a notable interest of researchers in the control community to provide an on-line state estimator for control systems instead of measuring them physically by sensors which is costly, inaccurate, and easy to contaminate by noise. Some challenges ahead to design state observer in control systems are using estimated data by an observer in the designed controller as well as the system stability analysis by using controller and observer simultaneously. This paper proposes the Fuzzy Adaptive Fixed-time Sliding Mode Control (FAFSMC) technique for trajectory tracking of a class of high-order nonlinear systems with mismatched external disturbances and uncertainties. Meanwhile, the fixed-time state observer is proposed to incorporate with the controller for estimating the unmeasured even states (velocity) and providing on-line data in the controller. A proper candidate Lyapunov function is defined to verify the system’s global fixed-time stability by considering designed control law, state observer term, and adaptive law, simultaneously. The simulation results of three simulation examples, ship course system, two-link robotic manipulator, and three-link robotic manipulator, are carried out in Simulink/MATLAB to reveal the effectiveness of the proposed FAFSMC scheme compared with the other three conventional methods for solving trajectory tracking problem. Two performance criteria, Integral of the Square Value (ISV) and Integral of the Absolute value of the Error (IAE), are used to make a comprehensive comparison among the proposed FAFSMC method with state observer and the other three methods.
Download: http://link.springer.com/article/10.1007/s12555-019-0650-z
Keywords: Adaptive, fixed-time, fuzzy, mismatched uncertainties, sliding mode, state observer.
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