• Journal of Power Electronics
• /
• v.19 no.2
• /
• pp.549-559
• /
• 2019

This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2000.04b
• /
• pp.365-370
• /
• 2000

A sliding mode fuzzy control (SMFC) algorithm is applied to design a controller for a benchmark problem on a wind- excited building. The structure is a 76-story concrete office tower with a height of 306 meters, hence the wind resistance characteristics are very important for the serviceability as well as the safety. A control system with an active tuned mass damper is assumed to be installed on the top floor. Since the structural acceleration is measured only at ,limited number of locations without measurement of the wind force, the structure of the conventional continuous sliding mode control may have the feed-back loop only. So, an adaptive least mean squares (LMS) filter is employed in the SMFC algorithm to generate a fictitious feed-forward loop. The adaptive LMS filter is designed based on the information of the stochastic characteristics of the wind velocity along the structure. A numerical study is carried out. and the performance of the present SMFC with the ,adaptive LMS filter is investigated in comparison with those of' other control, of algorithms such as linear quadratic Gaussian control, frequency domain optimal control, quadratic stability control, continuous sliding mode control, and H/sub ∞///sub μ/, control, which were reported by other researchers. The effectiveness of the adaptive LMS filter is also examined. The results indicate that the present algorithm is very efficient .

• Journal of Aerospace System Engineering
• /
• v.14 no.2
• /
• pp.20-27
• /
• 2020

Several uncertainties in the landing environment of an aircraft are not considered, such as the falling speed, ambient temperature, and sensor noise. These uncertainties negatively affect the performance of the controller applied to a landing gear. The sliding mode control (SMC) method, which maintains the optimal performance of a controller under uncertainties, is used in this study. The landing gear is equipped with a magnetorheological damper that changes the yield shear stress according to the applied magnetic field. The applied controller employs a hybrid control combining Skyhook control and force control. The SMC maintains the optimal performance of the hybrid control by minimizing the tracking error of the damper force, even in various landing environments where parameter uncertainties are applied. The effect of SMC is verified through co-simulation results from Simscape and Simulink.

• Journal of information and communication convergence engineering
• /
• v.4 no.3
• /
• pp.118-122
• /
• 2006

In this paper, a sliding mode control method with uncertainty adaptation is proposed by introducing the virtual state. Because upper bound of the uncertainty is very difficult to know, we estimate this by using the simple adaptation law and design the sliding surface which has dynamic of nominal system. An optimal controller is used by nominal controller. And if initial values of the virtual state are chosen properly, the reaching phase is removed.

• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2003.09a
• /
• pp.419-426
• /
• 2003

An efficient procedure using LQR method for determining optimal sliding surfaces appropriate for different controller types is provided. The parametric evaluation of the dynamic characteristics of sliding surfaces is peformed in terms of SMC controller performance of single-degree-of-freedom(SDOF) systems. The control force limit is considered in this procedure. Numerical simulations for multi-degree-of-freedom(MDOF) systems verify the effectiveness of proposed method.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.8
• /
• pp.1985-1996
• /
• 1994

A new design method of sliding hyperplanes is proposed in the synthesis of a variable structure controller for robust tracking of general nonlinear multi-input-output(MIMO) uncertain systems of relative degree higher than two. Input/ output(I/O) linearzation is firstly undertaken by employing the concept of relative degree and minimum phase followed by the construction of sliding mode controllers. Sliding hyperplanes are then derived from the inherent properties of companion matrix and ideal sliding mode characterized in I/O linearized system. Subsequently, the gradient magnitudes of the sling hyperplanes are determined in an optimal manner by considering a quadratic performance index to be evaluated at two phases; a reaching phase and a sliding phase. The proposed design methodology is relatively straightforward and systematic compared with conventional strategies such as geometric approach or pole assignment technique. A nonlinear governor and exciter control problem for a power system is adopted herein in order to demonstrate the design efficiency and also favorable and robust control performances.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.182-182
• /
• 2000

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that the selected solution become the global optimal solution by optimizing the Akaike's information criterion. The trajectory trucking experiment of the polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding model controller provides reliable tracking performance during the polishing process.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.19 no.8
• /
• pp.795-801
• /
• 2009

This paper presents an optimal design of a magnetorheological(MR) fan clutch based on finite element analysis and also presents torque control of engine cooling fan using a sliding mode control. The MR fan clutch is constrained in a specific volume and the optimization problem identifies the geometric dimension of the fan clutch that minimizes an objective function. The objective function for the optimization problem is determined based on the solution of the magnetic circuit of the initially designed clutch. Under consideration of spatial limitation, design parameters are optimally determined using finite element analysis. After describing the configuration of the MR fan clutch, the viscous torque and controllable torque are obtained on the basis of the Bingham model of MR fluid. Then, a sliding mode controller is designed to control the torque of the fan clutch according to engine room temperature and control performance is evaluated through computer simulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2009.04a
• /
• pp.633-638
• /
• 2009

This paper presents an optimal design of a magnetorheological(MR) fan clutch based on finite element analysis and also presents torque control of engine cooling fan using a sliding mode control. The MR fan clutch is constrained in a specific volume and the optimization problem identifies the geometric dimension of the fan clutch that minimizes an objective function. The objective function for the optimization problem is determined based on the solution of the magnetic circuit of the initially designed clutch. Under consideration of spatial limitation, design parameters are optimally determined using finite element analysis. After describing the configuration of the MR fan clutch, the viscous torque and controllable torque are obtained on the basis of the Bingham model of MR fluid. Then, a sliding mode controller is designed to control the torque of the fan clutch according to engine room temperature and control performance is evaluated through computer simulation.

• Journal of Mechanical Science and Technology
• /
• v.15 no.2
• /
• pp.143-151
• /
• 2001

In the paper, a robust control mechanism is presented to maneuver a flexible spacecraft with the deflection reduction during large slewing operation at the same time. For deflection reduction and maneuvering of the flexible spacecraft, a control mechanism is developed with the application of stochastic optimal sliding-mode control, a linear tracking model and input shaping technique. A start-coast-stop maneuver is employed as a slewing strategy. It is shown that the control mechanism with he strategic maneuver results in better performance and is more efficient than rigid-body-like maneuver, by applying to the Spacecraft Control Laboratory Experiment (SCOLE) system in a space environment.