Sliding Mode Control for Two-Degree-Of-Freedom Fractional Zener Oscillator

Author(s):  
Jian Yuan ◽  
Song Gao ◽  
Liying Wang ◽  
Guozhong Xiu

Abstract Fractional-order derivatives provide a powerful tool for the characterization of mechanical properties of viscoelastic materials. A fractional oscillator refers to mechanical model of viscoelastically damped structures, of which the viscoelastic damping is described by constitutive equations involving fractional-order derivatives. This paper proposes active control of vibration in a two-degree-of-freedom fractional Zener oscillator utilizing sliding mode technique. Firstly, with a state transformation, the fractional differential equations of motion are equivalently transformed into a relatively simple form. Meanwhile, a virtual fractional oscillator is generated, which is further used to analyze the original oscillator. Then, the stored energy in the two fractional derivative terms is derived based on the diffusive model of fractional integrator. Thus, the total mechanical energy in the virtual oscillator is determined as the sum of the kinetic energy, the potential energy and the fractional energy. Furthermore, sliding mode control of vibration in the fractional Zener oscillator is designed, of which the Lyapunov function is chosen as the total mechanical energy. Finally, numerical simulations are conducted to validate the effectiveness of the proposed controllers.

Author(s):  
Majid Parvizian ◽  
Khosro Khandani

This article proposes a new [Formula: see text] sliding mode control strategy for stabilizing controller design for fractional-order Markovian jump systems. The suggested approach is based on the diffusive representation of fractional-order Markovian jump systems which transforms the fractional-order system into an integer-order one. Using a new Lyapunov–Krasovskii functional, the problem of [Formula: see text] sliding mode control of uncertain fractional-order Markovian jump systems with exogenous noise is investigated. We propose a sliding surface and prove its reachability. Moreover, the linear matrix inequality conditions for stochastic stability of the resultant sliding motion with a given [Formula: see text] disturbance attenuation level are derived. Eventually, the theoretical results are verified through a simulation example.


2021 ◽  
pp. 002029402110211
Author(s):  
Tao Chen ◽  
Damin Cao ◽  
Jiaxin Yuan ◽  
Hui Yang

This paper proposes an observer-based adaptive neural network backstepping sliding mode controller to ensure the stability of switched fractional order strict-feedback nonlinear systems in the presence of arbitrary switchings and unmeasured states. To avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously, the fractional order dynamic surface control (DSC) technology is introduced into the controller. An observer is used for states estimation of the fractional order systems. The sliding mode control technology is introduced to enhance robustness. The unknown nonlinear functions and uncertain disturbances are approximated by the radial basis function neural networks (RBFNNs). The stability of system is ensured by the constructed Lyapunov functions. The fractional adaptive laws are proposed to update uncertain parameters. The proposed controller can ensure convergence of the tracking error and all the states remain bounded in the closed-loop systems. Lastly, the feasibility of the proposed control method is proved by giving two examples.


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