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Modeling and Stabilization Fuzzy Control Strategies of a Nonlinear Cart-Pendulum System: a Comparative Study

机译:非线性车-摆系统的建模与稳定模糊控制策略的比较研究

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摘要

In this paper, we propose and validate an unsimplified nonlinear state-space model of the cart-pendulum system. Then, we present several fuzzy control strategies in order to stabilize and control both the pendulum angle in upright position and the cart position into a desired position. These strategies are built upon two separate fuzzy logic controllers (FLC), having the same characteristics. To achieve this goal, we used various structures of two-input fuzzy controllers such as fuzzy proportional-derivative (FPD), fuzzy proportional-integral (FPI), FPI plus FPD and FPI derivative (FPID), designed by two basic fuzzy inference systems, i.e., Mamdani or zero-order Takagi-Sugeno. Then, the effectiveness of different strategies was tested and compared using several performance integration indices. Many tests were carried out and the obtained simulation results proved that the strategy, based on the zero-order Takagi-Sugeno FPID structures, could be applied to control the coupled variables of a nonlinear system. Furthermore, the proposed unsimplified nonlinear state-space model of the cart-pendulum system, might be used for validating new nonlinear control strategies.
机译:在本文中,我们提出并验证了一个简单的摆式系统的非线性状态空间模型。然后,我们提出几种模糊控制策略,以稳定和控制摆角在直立位置和手推车位置到所需位置。这些策略基于具有相同特性的两个独立的模糊逻辑控制器(FLC)。为了实现此目标,我们使用了由两种基本的模糊推理系统设计的二输入模糊控制器的各种结构,例如模糊比例微分(FPD),模糊比例积分(FPI),FPI加FPD和FPI导数(FPID) ,即Mamdani或零阶Takagi-Sugeno。然后,使用几种绩效整合指标对不同策略的有效性进行了测试和比较。进行了许多测试,获得的仿真结果证明,该策略基于零阶高木-Sugeno FPID结构,可以应用于控制非线性系统的耦合变量。此外,所提出的未简化的摆式系统的非线性状态空间模型可以用于验证新的非线性控制策略。

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