基于区间二型模糊神经网络反演控制抑制二惯量系统的机械振动

Vibration Suppression for Two-Inertia System Based on Backstepping and Interval Type-2 Fuzzy Neural Networks

  • 摘要: 针对带有不确定性和扰动的二惯量伺服系统,提出了一种基于区间二型模糊神经网络的自适应反演控制策略抑制系统的机械振动.首先建立了二惯量系统的动力学模型,设计了反演自适应控制律;其次系统中负载和电机两端未知的扰动变量定义为待估计项,采用区间二型模糊神经网络对其进行估计,给出了基于区间二型模糊神经网络的参数自适应律.基于李雅普诺夫稳定性理论,证明了闭环系统输出跟踪的收敛性,并且跟踪误差可以通过调节控制参数达到任意小.仿真结果表明该方法具有较好的控制性能.

     

    Abstract: This paper proposed an adaptive backstepping controller based on interval type-2 fuzzy neural networks for the nonlinear two-inertia system with uncertainty and disturbance. First, a mathematic model of the two-inertia system was presented, and the control law was designed based on adaptive backstepping method with regard of uncertainty. Next, the uncertainty and disturbance of the control system were defined as a total disturbance to be estimated by using interval type-2 fuzzy neural networks, the parameter adaptive law was given based on interval type-2 fuzzy neural networks, and the convergence of output tracking was proved via Lyapunov stability theory. Finally, simulations demonstrate the effectiveness and applicability of the proposed control scheme.

     

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