Papers by Keyword: Sliding Mode Controller

Abstract: This paper describes a comparative performance analysis of sliding mode and fuzzy sliding mode controllers for climate control application of a greenhouse flower garden. Various internal and external climate related factors affect the overall growth and health of flowers that needs robust controllers to control the humidity and temperature of the greenhouse flower garden. Review of related works show that for non-linear systems, sliding mode controllers can provide robust performance even though chattering is a major drawback of the controller. A number of approaches are used to solve the chattering problem of sliding mode controllers such as hybrid uses of other controllers along with sliding mode controller. In this paper, sliding mode controller and fuzzy sliding mode controllers are designed and implemented for the specified control application based on the linearized and decoupled model of the system. The performance evaluation has been done for the control problems of reference tracking and disturbance rejection with time domain performance measures of percentage overshoot, settling time and rise time. Accordingly, the overall system has been implemented in MATLAB/Simulink and the simulations for the control problems have been done. Thus, FSMC has got rise time of 5.89min, 10.59min settling time and almost negligible percentage overshoot for indoor temperature at 27°C and humidity at 22g/m³. And for humidity control, the FSMC has got 5.44min settling time and nearly zero percentage overshoot for set point tracking problem. For the disturbance of solar radiation, decrease in outside temperature and fixed set point of 27°C and humidity of 22g/m³, FSMC outperforms SMC. In summary, both quantitative and qualitative results analysis results reveal that fuzzy sliding mode controller (FSMC) outperforms sliding mode controller (SMC) for the indoor temperature and humidity control tasks of both set point tracking and disturbance rejection problems.

Abstract: This paper proposesd am adaptive sliding mode fuzzy neural network estimation (ASFNE) in the magnetic bearing system (MBS). The fuzzy neural network estimator has fuzzy rules base and neural network weights which the stability is proved by Lyapunov theorem in ASFNE. Therefore, ASFNE estimates system lump uncertainty to improve steady-state error and reduced chattering phenomenon. Finally, we compared ASFNE and sliding mode controller in MBS which ASFNE has better output responses.

Abstract: This paper presents an online Artificial Fuzzy sliding Gain Scheduling Sliding Mode Control (AFSGSMC) design and its application to internal combustion (IC) engine high performance nonlinear controller in the presence of uncertainties and external disturbance. The fuzzy online tune sliding function in fuzzy sliding mode controller is based on Mamdanis fuzzy inference system (FIS) and it has multi input and multi output. The input represents the function between sliding function, error and the rate of error. The output represents the dynamic estimator to estimate the nonlinear dynamic equivalent in supervisory fuzzy sliding mode algorithm. The performance of the AFSGSMC was compared with the 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

Abstract: To cope with the problem of the degradation of actuation effectiveness caused by actuator deflection or fault in the attitude and orbit control system (AOCS) of spacecraft on-orbit, an attitude fault-tolerant and anti-disturbance control scheme is proposed based on a sliding mode iterative learning law, in which the pseudo control input is applied to design the sliding mode controller to ensure the AOCS tracks a reference trajectory precisely after some fault occurred; By analyzing the Lyapunov stability, a novel adaptive iterative learning law is developed, which in term of the tracking error, determine some parameters in controller on-line to address the actuator failure and external disturbance. Numerical simulation experiments show that the fault-tolerant and anti-disturbance controller can ameliorate actuation malfunction and compensate the influence of external disturbance effectively.

Abstract: Motors of Independent Drive Electric Vehicle can be controlled independently, which can enrich the method of stability control for vehicle. In order to fully take use of the advantage，The man-vehicle system with eight degrees of freedom ,which includes Magic Formula tire model and driver model based on Preview Follower Theory, was set up by using MATLAB/SIMULINK. Considering the complexity of the driving condition and the nonlinear time-varying characteristics of the vehicle system, a Sliding mode controller based on transient reference model was set up, which selected Yaw rate as Control variable and two motors as actuators. The simulation results show that handling and stability of vehicle can be improved greatly by the Sliding mode controller.

Abstract: Two motors of Dual-Motor Independent Drive Electric Vehicle can be controlled independently, which can enrich the method of stability control for vehicle. In order to fully take use of the advantage，The man-vehicle system with eight degrees of freedom ,which includes Magic Formula tire model and driver model based on Preview Follower Theory, was set up by using MATLAB/SIMULINK. Considering the complexity of the driving condition and the nonlinear time-varying characteristics of the vehicle systems, a controller based on Sliding mode variable structure control theory was set up, which selected Yaw rate as Control variable and two motors as actuators. The simulation results show that handling and stability of vehicle can be improved greatly by the Sliding mode controller.

Abstract: A sliding mode controller for flux-switching permanent magnet (FSPM) motor is investigated in this paper, in which direct torque control (DTC) concept, variable structure control are integrated to achieve high performance. Then, an FNN is investigated to optimize the control gain matrix of sliding mode controller. The theoretical analyses for the proposed FNN sliding-mode controller are described in detail. Simulation results show that the proposed FNN sliding-mode controller provides low torque ripple and the chattering phenomenon is much reduced.

Abstract: In this paper, vibration control performance of piezostack active engine mount system for unmanned aero vehicle (UAV) is evaluated via computer simulation. As a first step, the dynamic model of engine mount system which is supported at three points is derived. In the configuration of engine mount system, the inertia type of piezostack based active mount is installed for active vibration control. Then, the vibration level of UAV engine is measured. To attenuate the vibration which is transmitted from engine, a sliding mode controller which is robust to uncertain parameters is designed. Vibration control performances of active engine mount system are evaluated at each mount and center of gravity. Effective Control results are presented in both time and frequency domains.

Abstract: This paper presents temperature control of engine cooling system using a controllable magnetorheological (MR) fan clutch. An appropriate size of MR fan clutch is devised and modeled on the basis of Bingham model. Subsequently, an optimization to determine design parameters such as width of housing is undertaken by choosing the reciprocal of the controllable torque as an objective function. This has been performed using a finite element analysis. A sliding mode controller is then designed to control the angular velocity of the MR fan clutch using experimentally determined parameters. The designed controller is implemented and control performances of the MR fan clutch system are evaluated.

Abstract: The problem of precise control of the air – gap of magnetic levitation vehicles is considered in this paper. A sliding mode controller is designed for the levitation control task. Robustness of the controller was investigated using computer simulations. The results show that the controller is robust to parameter variations of up to ±13% and can tolerate disturbances up to ±400N/Kg.