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Development of a Generic and Configurable Fuzzy Logic Systems Library for Real-Time Control Applications Using an Object-Oriented Approach

机译:使用面向对象的方法进行实时控制应用的通用和可配置模糊逻辑系统库的开发

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Since fuzzy logic controllers (FLCs) can handle complex systems without knowing much about the systems' mathematical model, they are widely used for a range of robotic control applications. Further, the ability of FLCs (particularly, type-2 FLCs) to effectively capture and accommodate uncertainties has made them one of the suitable choices for implementing robotic control applications in uncertain environments. However, developing type-1 and type-2 FLCs for real-time robotic control applications is relatively more challenging than developing traditional controllers such as PID controllers. The reason is, the fuzzy logic calculations involved are more complex and not much tools have been developed to assist FLC application developers. In this paper, therefore, using an object-oriented approach and unified model language (UML), we demonstrate a systematic approach for developing a new generic and configurable fuzzy logic system (FLS) library that eases the implementation of real-time type-1 and interval type-2 FLC applications based on both Mamdani and Takagi-Sugeno-Kang (TSK) inference mechanisms. To evaluate the developed library, we have implemented it for the interval type-2 TSK fuzzy logic altitude control of a quadcopter unmanned aerial vehicle (UAV). The response of this fuzzy logic controller is then compared with the response of a classical PD controller.
机译:由于模糊逻辑控制器(FLC)可以处理复杂的系统而不知道系统的数学模型,它们广泛用于一系列机器人控制应用。此外,FLC(特别是2 FLC)能够有效地捕获和适应不确定性的能力使它们成为在不确定环境中实现机器人控制应用的合适选择之一。然而,用于实时机器人控制应用的Type-1和类型-2 FLC比开发传统控制器,例如PID控制器等传统控制器相对更具挑战性。原因是,所涉及的模糊逻辑计算更加复杂,而且已经开发出的工具而不是协助FLC应用程序开发商。因此,在本文中,使用面向对象的方法和统一模型语言(UML),我们展示了开发新的通用和可配置模糊逻辑系统(FLS)库的系统方法,可以减轻实时类型1的实现基于Mamdani和Takagi-Sugeno-kang(TSK)推理机制的间隔类型-2 FLC应用。为了评估开发的库,我们已经为Quadcopter无人机(UAV)的间隔类型-2 TSK模糊逻辑高度控制实施了。然后将该模糊逻辑控制器的响应与经典PD控制器的响应进行比较。

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