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Modelling, stability analysis and computational aspects of nonlinear fuzzy PID controllers using Mamdani minimum inference

机译:使用Mamdani最小推理的非线性模糊PID控制器的建模,稳定性分析和计算方面

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>This paper presents two new mathematical models of the simplest fuzzy PID controller which employ two fuzzy sets (negative and positive) on each of the three input variables (error, change in error and double change in error) and four fuzzy sets (-2, -1, +1, +2) on the output variable (incremental control). L-type, Γ-type and II-type membership functions are considered in fuzzification process of input and output variables. Controller modelling is done via algebraic product AND operation, maximum/bounded sum OR operation, Mamdani minimum inference method, and centre of sums (CoS) defuzzification. The new models obtained in this manner turn out to be nonlinear, and their properties are studied. Since digital controllers are implemented on the digital processors, the computational and memory requirements of the fuzzy controllers and conventional (non-fuzzy) controller are compared. Stability analysis of closed loop systems containing the fuzzy controller models is done using the small gain theorem.
机译:>本文提出了两个新的模糊PID控制器的新数学模型,其中三个输入变量中的每一个采用了两个模糊集(负极和正)(误差,误差的误差变化和双重变化)和四个模糊集( -2,-1,+1,+2)在输出变量上(增量控制)。 <斜视> L -TYPE,γ型和II型隶属函数在输入和输出变量的模糊过程中考虑。控制器建模通过代数产品和操作,最大/有界和或操作,Mamdani最小推理方法和总和(COS)Defuzzification的次数进行完成。以这种方式获得的新模型转向非线性,研究其性质。由于数字控制器在数字处理器上实现,因此比较了模糊控制器和传统(非模糊)控制器的计算和存储器要求。使用小增益定理完成了包含模糊控制器模型的闭环系统的稳定性分析。

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