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Robust Evolving Cloud-based Controller (RECCo)

机译:强大的基于云的控制器(RECCo)

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This paper presents an autonomous Robust Evolving Cloud-based Controller (RECCo). The control algorithm is a fuzzy type with non-parametric (cloud-based) antecedent part and adaptive PID-R consequent part. The procedure starts with zero clouds (fuzzy rules) and the structure evolves during performing the process control. The PID-R parameters of the first cloud are initialized with zeros and furthermore, they are adapted on-line with a stable adaptation mechanism based on Lyapunov approach. The RECCo controller does not require any mathematical model of the controlled process but just basic information such as input and output range and the estimated value of the dominant time constant. Due to the problem space normalization the design parameters are fixed. The proposed controller with the same initial design parameters was tested on two different simulation examples. The experimental results show the convergence of the adaptive parameters and the effectiveness of the proposed algorithm.
机译:本文提出了一种自主的基于云的鲁棒演进控制器(RECCo)。控制算法是具有非参数(基于云)的前部分和自适应PID-R后继部分的模糊类型。该过程从零个云(模糊规则)开始,并且在执行过程控制期间结构会演变。第一个云的PID-R参数用零初始化,并且通过基于Lyapunov方法的稳定自适应机制进行在线自适应。 RECCo控制器不需要任何受控过程的数学模型,而只需要基本信息,例如输入和输出范围以及主导时间常数的估计值。由于空间标准化的问题,设计参数是固定的。在两个不同的仿真示例上测试了具有相同初始设计参数的拟议控制器。实验结果表明自适应参数的收敛性和算法的有效性。

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