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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 53797 (06)
- University: Sharif University of Technology
- Department: Chemical and Petroleum Engineering
- Advisor(s): Shahrokhi, Mohammad
- Abstract:
- Considering input constraints is an essential task in the controller design. In this thesis, a controller has been designed for incommensurate fractional order nonlinear systems in the nonstrict feedback form subject to unknown dynamics, input nonlinearity and actuator failures. The Lyapunov direct method and the backstepping technique have been used to design the controller and stability analysis. The number of actuator faults can be infinite. In addition, the proposed control algorithm can cope with different types of input nonlinearities namely, saturation, dead zone, dead zone-saturation, backlash and hysteresis. To estimate the system uncertainties, neural networks have been employed and the nonstrict feedback form has been handled utilizing the structural characteristic of Gaussian radial basis functions neural networks. The proposed adaptive controller guarantees that all the close-loop signals are bounded and the tracking error converges to a sufficiently small neighborhood of the origin. Finally, the effectiveness of the designed controller has been studied by simulating three examples. Simulation results demonstrate the effectiveness of the proposed approach
- Keywords:
- Fractional Order System ; Neural Network ; Actuator Failure ; Input Nonlinearity ; Backstepping Algorithm ; Lyapunov Function
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