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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开发用于实时控制应用的通用和可配置模糊逻辑系统库

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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)可以在不了解系统数学模型的情况下处理复杂的系统,因此它们被广泛用于一系列机器人控制应用中。此外,FLC(尤其是2型FLC)有效捕获和适应不确定性的能力使其成为在不确定环境中实现机器人控制应用程序的合适选择之一。但是,为实时机器人控制应用开发类型1和类型2 FLC比开发传统的控制器(例如PID控制器)更具挑战性。原因是,所涉及的模糊逻辑计算更加复杂,并且尚未开发出太多工具来协助FLC应用程序开发人员。因此,在本文中,使用面向对象的方法和统一模型语言(UML),我们演示了一种系统方法,用于开发新的通用且可配置的模糊逻辑系统(FLS)库,该库可简化实时Type-1的实现基于Mamdani和Takagi-Sugeno-Kang(TSK)推理机制的区间类型2 FLC应用程序。为了评估开发的库,我们将其用于四轴无人机的间隔2型TSK模糊逻辑高度控制。然后将此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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