• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.281-292
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• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.

• Journal of Power Electronics
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• v.18 no.3
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• pp.766-777
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• 2018

In this paper, a sliding mode and proportional plus integral (SM-PI) control combined with self-sustained phase shift modulation (SSPSM) for LLC resonant converters is presented. The proposed control scheme improves the transient response while preserving good steady-state performance. An averaged large signal model of an LLC converter with the ZVS modulation technique is developed for the SM control design. The sliding surface is obtained based on the input-output linearization concept. A system identification method is adopted to obtain the transform function of the LLC resonant converter, which is used to design the PI control. In order to reduce the inherent chattering problem in the steady state, the combined SM-PI control strategy is derived with fuzzy control, where the SM control is responsive during the transient state while the PI control prevails in the steady state. The combination of SSPSM and the SM-PI control provides ZVS operation, robustness and a fast transient response against step load variations. Simulation and experimental results validate the theoretical analysis and the attractive features of the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.399-405
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• 2007

This paper deals with the controller for a stable walking of a humanoid robot using genetic algorithm. A humanoid robot has instability during walking because it isn't fixed on the ground, and its nonlinearities of the joints increase its instability. If controller isn't robust, the robot may fall down at the ground during walking because of its nonlinearities. To solve this problem, robust controller is required to reduce the effect of nonlinearities and to gain the good tracking performance. In this paper, motion controller that is based on fuzzy-sliding mode controller is proposed. This controller can remove the effect of the saturation by limitation of the input voltage. It also includes compensator for reducing the effect of the nonlinearity by backlash and PI controller improving the tracking performance. In here, genetic algorithm is used for searching the optimal gains of the controller. From the given controller, a humanoid robot can moved more preciously. All the processes are investigated through simulations and are verified experimentally in a real joint system for a humanoid robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.4
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• pp.77-86
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• 1995

The new architecture that fuzzy logic control(FLC) with difficulties for tuning membership function (MF) is parallel with neural networks(NN) to be learned from the output of FLC is proposed. Therefore proposed scheme has the characteristics to utilize the expert knowledge in design process, to be learned during the operation without any learning mode. In this architecture, the function of the FLC is to supply the sliding surface which is constructed on the phase plane by rule base for giving the desired control characteristics and learning criterion of NN and the stabilization of the control performance before NN is learned, The function of the NN is to let the system trajectory be tracked to the sliding surface and reached to the stable point.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.246-250
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• 2000

A distinctive feature in vibration control of a large civil infrastructure is the existence of large disturbances, such as wind, earthquake, and sea wave forces. Those disturbances govern the behavior of the structure, however, they cannot be precisely measured, especially for the case of wind-induced vibration control. The sliding mode fuzzy control (SMFC), which is of interest in this study, may use not only the structural response measurement but also the wind force measurement. Hence, an adaptive disturbance estimation filter is introduced to generate a wind force vector at each time instance based on the measured structural response and the stochastic information of the wind force. The structure of the filter is constructed based on an auto-regressive with auxiliary input model. A numerical simulation is carried out on a benchmark problem of a wind-excited building. The results indicate that the overall performance of the proposed SMFC is as good as the other methods and that most of the performance indices improve as the adaptive disturbance estimation filter is introduced.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.591-597
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• 2017

This study is to develop a vehicle Integrated Dynamics Control System(IDCB) that can stabilize the lateral dynamics and maintain steerability. To accomplish this task, an eight degree of freedom vehicle model and a nonlinear observer are designed. The IDCB independently controls the brake systems of four wheels with a fuzzy logic control and a sliding model control. The result shows that the nonlinear observer produced satisfactory results. IDCB tracked the reference yaw rate and reduced the body slip angle under all tested conditions. It indicates that the IDCB enhanced lateral stability and preserved steerability.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.428-433
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• 1997

This paper presents a new control strategy for the position and force control of flexible manipulators. The governing equation of motion of a two-link flexible manipulator which features piezoceramic actuators bonded on each flexible beam is derived via Hamilton's principle. The control torque of the motor to command desired position and force is determined by a sliding mode controller on the basis of the rigid-mode dynamics. In the controller formulation, the sliding mode controller with perturbation estimation(SMCPE) is adopted to determine appropriate control gains. The SMCPE is then incorporated with the fuzzy technique to mitigate inherent chattering problem while maintaining the stability of the system. A set of fuzzy parameters and control rules are obtained from a relation between estimated perturbation and actual perturbation. During the commanded motion, undesirable oscillation is actively suppressed by applying feedback control voltages to the piezoceramic actuators. These feedback voltages are also determined by the SMCPE. Consequently, accurate force and position control of a two-link flexible manipulator are achieved. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control methodology.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2192-2195
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• 2002

Even though, tanks are used at the many industry plants, it is very difficult to control the tank level without any overflow and shortage; moreover, cause of its complication of dynamics and nonlinearity, it's impossible to realize the accurate control using the mathematical model which can be applied to the various operation modes. However, the sliding mode controller(SMC) is known as having the robust variable structures for the nonlinear control systems with the parametric perturbations and with the sudden disturbances. It's difficult to find SMC's parameters, and SMC is bring chattering which injures actuator and increases error. In this paper, Genetic Aloglism based Fuzzy Sliding Mode Controller(GA-FSMC) for the precise control of the coupled tank level was proposed. Genetic Algolism and Fuzzy logic are adapted to find SMC's parameters and reduce the chattering. The simulation result is shown that the tank level could be satisfactorily controlled with less overshoot and steady-state error by the proposed GA-FSMC.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.275-284
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• 2012

This paper proposes an attitude and direction control of a single wheel balanced robot. A unicycle robot is controlled by two independent control laws: the mobile inverted pendulum control method for pitch axis and the reaction wheel pendulum control method for roll axis. It is assumed that both roll dynamics and pitch dynamics are decoupled. Therefore the roll and pitch dynamics are obtained independently considering the interaction as disturbances to each other. Each control law is implemented by a controller separately. The unicycle robot has two DC motors to drive the disk for roll and to drive the wheel for pitch. Since there is no force to change the yaw direction, the present paper proposes a method for changing the yaw direction. The angle data are obtained by a fusion of a gyro sensor and an accelerometer. Experimental results show the performance of the controller and verify the effectiveness of the proposed control algorithm.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.421-437
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• 2015

This paper aims to present a supervised classification algorithm based on data fusion for the segmentation of the textured images. The feature extraction method we used is based on discrete wavelet transform (DWT). In the segmentation stage, the estimated feature vector of each pixel is sent to the support vector machine (SVM) classifier for initial labeling. To obtain a more accurate segmentation result, two strategies based on information fusion were used. We first integrated decision-level fusion strategies by combining decisions made by the SVM classifier within a sliding window. In the second strategy, the fuzzy set theory and rules based on probability theory were used to combine the scores obtained by SVM over a sliding window. Finally, the performance of the proposed segmentation algorithm was demonstrated on a variety of synthetic and real images and showed that the proposed data fusion method improved the classification accuracy compared to applying a SVM classifier. The results revealed that the overall accuracies of SVM classification of textured images is 88%, while our fusion methodology obtained an accuracy of up to 96%, depending on the size of the data base.