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首页> 外文期刊>Nonlinear dynamics >Designing a terminal optimal control with an integral sliding mode component using a saddle point method approach: a Cartesian 3D-crane application
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Designing a terminal optimal control with an integral sliding mode component using a saddle point method approach: a Cartesian 3D-crane application

机译:使用鞍点方法设计带有积分滑模组件的终端最优控制:笛卡尔3D起重机应用

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摘要

This paper proposes a new approach for designing a nonlinear optimal controller with an integral sliding mode component employing a generalization of the saddle point method which consists on controlling a controllable nonlinear system. Based on the initial and final conditions of the dynamical system, we consider an open-loop control such that the state of the system can be moved to a neighborhood of the equilibrium state corresponding to the given final condition. The implementation of the method for solving the problem involves a two-step iterated procedure: (i) The first step consists of a "prediction" which calculates the preliminary position approximation to the steady-state point, and (ii) the second step is designed to find a "basic adjustment" of the previous prediction. We apply the controller to a Cartesian 3D-crane. The formulation of the 3D-crane is in terms of nonlinear programming problems implementing the Lagrange principle. We transform the problem in a system of equations where each equation is itself an optimization problem. For designing the controller we suggest to employ an integral sliding mode method which suppress the model uncertainties consequence of moving the trolley and the bridge, lifting the cargo as well as external forces. As a result, the optimal controller will be simultaneously able to lift the cargo, suppressing the payload vibration, tracking the trolley and moving the bridge. A numerical example involving the simulation of a 3D-crane shows the effectiveness of the controller.
机译:本文提出了一种新的方法来设计具有积分滑模分量的非线性最优控制器,该方法采用了基于控制可控制非线性系统的鞍点方法的推广。基于动力学系统的初始条件和最终条件,我们考虑进行开环控制,以使系统状态可以移动到与给定最终条件相对应的平衡状态附近。解决问题的方法的实现涉及两步迭代过程:(i)第一步由“预测”组成,该“预测”计算到稳态点的初始位置近似值,并且(ii)第二步是旨在找到先前预测的“基本调整”。我们将控制器应用于笛卡尔3D起重机。 3D起重机的制定是根据实现Lagrange原理的非线性编程问题进行的。我们在方程系统中转换问题,其中每个方程本身就是一个优化问题。为了设计控制器,我们建议采用整体滑模方法,该方法可以抑制由于移动小车和桥架,提起货物以及外力而导致的模型不确定性。结果,最佳控制器将能够同时提升货物,抑制有效载荷振动,跟踪手推车并移动桥。涉及3D起重机仿真的数值示例说明了控制器的有效性。

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