Operation and maintenance have their own impact in every field. Maintenance strategy is followed to provide unwavering quality and security for a healthy transportation system. Therefore, the transportation system requires an appropriate maintenance schedule of the vehicles. The classical analysis of the present and future performance of systems tries to assure that the safety and operational condition of the system so as to enhance the ability of credentials of proactive malfunction circumstances. Condition-based maintenance identifies the vehicle status based on wire or wireless monitored data and predicts malfunction to carry out suitable maintenance actions like repair and replacement before it happens. Different uncertainties like terrain, mileage of the vehicle and applied load on the vehicles have been utilized as the constraints of fuzzy-based vehicle maintenance scheduling. The response of vehicle maintenance scheduling (VMS) provides the details regarding the type of maintenance and time period in weeks for proposed maintenance plan. Probability values of constraints acquired by the hidden Markov model have been utilized as input of VMS. The response of vehicle maintenance scheduling has been compared with input obtained by Monte Carlo simulation. Reliability of the methodology corroborates the effectiveness of the proposed methodology in the field of maintenance scheduling for healthy transportation system.
In this paper, twin rotor multi input multi output system (TRMS) is considered as a prototype laboratory set-up of helicopter. The aim of studying the model of TRMS and designing the controller for it is to provide a platform for controlling the flight of helicopter. An optimal state feedback controller based on linear quadratic regulator (LQR) technique has been designed for twin rotor multi input multi output system. TRMS is a nonlinear system with two degrees of freedom and cross couplings. The mathematical modeling of TRMS has been done using MATLAB/SIMULINK. The linearised model of TRMS is obtained from the nonlinear model. The simulation results of optimal controller are compared with the results of conventional PID controller. The appropriateness of proposed controller has been shown both in terms of transient and steady state response.
This paper aims at the development of a proportional integral derivative (PID) controller with a derivative filter coefficient for a magnetic levitation system (MLS), which is a highly nonlinear open loop system. The mathematical modeling of MLS is done using MATLAB/Simulink. The proposed controller simulation results are evaluated with sine wave and step response. The results obtained are also compared with PID controller. The response of the proposed PID controller with derivative filter show better response in comparison to that of conventional PID controller.
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