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Evolutionary Design on-line Sliding Fuzzy Gain Scheduling Sliding Mode Algorithm: Applied to Internal Combustion Engine

机译:进化设计在线滑行模糊增益调度滑模算法:应用于内燃机

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Refer to this research, a position on-line fuzzy sliding gain scheduling sliding mode control (AFSGSMC) design and application to internal combustion engine has proposed in order to design high performance nonlinear controller in the presence of uncertainties and external disturbance. Even though, sliding mode controller (SMC) is used in wide range areas but it has the following disadvantages: chattering and equivalent dynamic formulation. The fuzzy on-line tuneable sliding function in fuzzy sliding mode controller is based on Mamdanis fuzzy inference system (FIS) and it has one input and one output. The input represents the function between sliding function, error and the rate of error. The outputs represent the dynamic estimator to estimate the nonlinear dynamic equivalent in supervisory fuzzy sliding mode algorithm. The fuzzy sliding mode methodology is on-line tune the sliding function based on self tuning coefficient methodology. The performance of the AFSGSMC is validated through comparison with previously developed IC engine controller based on sliding mode control theory (SMC). Simulation results signify good performance of fuel ratio in presence of uncertainty and external disturbance.
机译:参照该研究,提出了一种位置在线模糊滑行增益调度滑模控制(AFSGSMC)设计方法并应用于内燃机,以在存在不确定性和外部干扰的情况下设计出高性能的非线性控制器。尽管滑模控制器(SMC)在广泛的领域中使用,但它具有以下缺点:颤振和等效的动态公式化。模糊滑模控制器中的模糊在线可调节滑移函数基于Mamdanis模糊推理系统(FIS),具有一个输入和一个输出。输入表示滑动功能,误差和误差率之间的函数。输出表示动态估计器,用于估计监督模糊滑模算法中的非线性动态等效项。模糊滑模方法是基于自整定系数方法在线调整滑模函数。通过与以前基于滑模控制理论(SMC)开发的IC发动机控制器进行比较,可以验证AFSGSMC的性能。仿真结果表明,在存在不确定性和外部干扰的情况下,燃油比具有良好的性能。

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