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Go to Editorial ManagerIn this paper, an Adaptive Sliding Mode Controller (ASMC) is designed and applied for a magnetic levitation system (Maglev) where a steel ball is desired to be stabilized at a desired position with existence of uncertainty in system model. Additionally, a sliding mode differentiator (SMD) is used for estimating the ball velocity since it’s needed for the controller to work properly. The designed controller and differentiator are applied practically to an experimental laboratory size magnetic levitation system and the results were plotted to show the behavior of the system under the effect of the designed controller. The experimental results reveal clearly the effectiveness and ability of the suggested controller in forcing the steel ball to follow various desired position.
The heat exchanger is a device used to transfer heat energy between two fluids, hot and cold. In this work, an output feedback adaptive sliding mode controller is designed to control the temperature of the outlet cold water for plate heat exchanger. The discontinuous gain value of the sliding mode controller is adapted according to a certain adaptation law, where the only information required is the measurement of the outlet cold temperature. A sliding mode differentiator was design to estimate time derivative of outlet hot water temperature. Two constraints which imposed on the volumetric flow rate of the hot water (control input) were considered within the rules of the proposed adaptation law in this work. These are the control input is positive only and has a maximum value. For constructing the sliding variable, the outlet hot water temperature and its time derivative are required. The maximum allowable desired outlet cold water has been estimated as function of heat exchanger parameters and maximum control input. The simulation results demonstrate the performance of the proposed adaptive sliding mode control where the outlet cold water was forced to follow desired temperature equal to . Additionally, the robustness of the proposed controller was tested for the case where the cold inlet temperature is not constant. The results reveal the robustness of the proposed controller.
Diabetes is one of the most critical diseases in the world which requires measuring the concentration of glucose also the injection of insulin to control the glucose rate in the body. The proposed controller is applied to the Bergman’s three-state minimal patient model, where the model is considered certain but with unknown meal. In the present work, a nonlinear controller is designed to control the concentration of glucose based on the Backstepping approached with a sliding mode for observing the disturbance meal. So will have estimated the meal and have canceled the effect that the glucose concentration has regulating to the basal level._x000D_ The effectiveness of the proposed controller, which represent the insulin dose, is proved via simulating the Bergman’s model with designed controller via MATLAB Simulink software. The result clarify the ability and the robustness of the proposed controller.