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Ehsan-Ghotb Razmjou,Seyed Kamal-Hosseini Sani,Seyed Jalil-Sadati 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.4
This paper develops a novel controller called iterative learning sliding mode (ILSM) to control linear and nonlinear fractional-order systems. This control applies a combination structures of continuous and discontinuous controller, conducts the system output to the desired output and achieve better control performance. This controller is designed in the way to be robust against the external disturbance. It also estimates unknown parameters of fractional-order systems. The proposed controller unlike the conventional iterative learning control for fractional systems does not need to apply direct control input to output of the system. It is shown that the controller perform well in partial and complete observable conditions. Simulation results demonstrate very good performance of the iterative learning sliding mode controller for achieving the desired control objective by increasing the number of iterations in the control loop.
Razmjou, Ehsan-Ghotb,Sani, Seyed Kamal-Hosseini,Jalil-Sadati, Seyed The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.4
This paper develops a novel controller called iterative learning sliding mode (ILSM) to control linear and nonlinear fractional-order systems. This control applies a combination structures of continuous and discontinuous controller, conducts the system output to the desired output and achieve better control performance. This controller is designed in the way to be robust against the external disturbance. It also estimates unknown parameters of fractional-order systems. The proposed controller unlike the conventional iterative learning control for fractional systems does not need to apply direct control input to output of the system. It is shown that the controller perform well in partial and complete observable conditions. Simulation results demonstrate very good performance of the iterative learning sliding mode controller for achieving the desired control objective by increasing the number of iterations in the control loop.
Dynamic Scheduling of FMS Using a Fuzzy Logic Approach to Minimize Mean Flow Time
Srinoi, Pramot,Shayan, Ebrahim,Ghotb, Fatemeh Korean Institute of Industrial Engineers 2008 Industrial Engineeering & Management Systems Vol.7 No.1
This paper is concerned with scheduling in Flexible Manufacturing Systems (FMS) using a Fuzzy Logic (FL) approach. Four fuzzy input variables: machine allocated processing time, machine priority, machine available time and transportation priority are defined. The job priority is the output fuzzy variable, showing the priority status of a job to be selected for the next operation on a machine. The model will first select the machines and then assign operations based on a multi-criteria scheduling scheme. System/machine utilization, minimizing mean flow time and balancing machine usage will be covered. Experimental and comparative tests indicate the superiority of this fuzzy based scheduling model over the existing approaches.
Dynamic Scheduling of FMS Using a Fuzzy Logic Approach to Minimize Mean Flow Time
Pramot Srinoi,Ebrahim Shayan,Fatemeh Ghotb 대한산업공학회 2008 Industrial Engineeering & Management Systems Vol.7 No.1
This paper is concerned with scheduling in Flexible Manufacturing Systems (FMS) using a Fuzzy Logic (FL) approach. Four fuzzy input variables: machine allocated processing time, machine priority, machine available time and transportation priority are defined. The job priority is the output fuzzy variable, showing the priority status of a job to be selected for the next operation on a machine. The model will first select the machines and then assign operations based on a multi-criteria scheduling scheme. System/machine utilization, minimizing mean flow time and balancing machine usage will be covered. Experimental and comparative tests indicate the superiority of this fuzzy based scheduling model over the existing approaches.