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A Multivariable Adaptive Control Approach for Stabilization of a Cart-Type Double Inverted Pendulum

机译:用于稳定推车型双倒立摆的多变量自适应控制方法

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摘要

This paper considers the design and practical implementation of linear-based controllers for a cart-type double inverted pendulum (DIPC). A constitution of two linked pendulums placed on a sliding cart, presenting a three Degrees of Freedom and single controlling input structure. The controller objective is to keep both pendulums in an up-up unstable equilibrium point. Modeling is based on the Euler-Lagrange equations, and the resulted nonlinear model is linearized around up-up position. First, the LQR method is used to stabilize DIPC by a feedback gain matrix in order to minimize a quadratic cost function. Without using an observer to estimate the unmeasured states, in the next step we make use of LQG controller which combines the Kalman-Bucy filter estimation and LQR feedback control to obtain a better steady-state performance, but poor robustness. Eventually, to overcome the unknown nonlinear model parameters, an adaptive controller is designed. This controller is based on Model Reference Adaptive System (MRAS) method, which uses the Lyapunov function to eliminate the defined state error. This controller improves both the steady-state and disturbance responses.
机译:本文考虑了用于推车型双倒立摆(DIPC)的基于线性控制器的设计和实践。将两个连接摆在滑动车上的构造,呈现三度的自由度和单控制输入结构。控制器目的是将两个摆锤保持在上升的不稳定平衡点中。建模基于Euler-Lagrange方程,所得到的非线性模型在上升位置围绕着线性化。首先,使用RQR方法通过反馈增益矩阵稳定DIPC,以最小化二次成本函数。在不使用观察者估算未测量状态的情况下,在下一步中,我们利用LQG控制器,将卡尔曼-Bucy滤波器估计和LQR反馈控制相结合,以获得更好的稳态性能,但鲁棒性差。最终,为了克服未知的非线性模型参数,设计了一种自适应控制器。该控制器基于模型参考自适应系统(MRAS)方法,它使用Lyapunov函数来消除定义的状态误差。该控制器可提高稳态和干扰响应。

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