• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.35.1-35
• /
• 2002

$\textbullet$ Sliding mode control (SMC) with nonlinear interpolation in variable boundary layer (VBL) is proposed $\textbullet$ A sigmoid function is used for nonlinear interpolation in VBL. $\textbullet$ The Parameter of the sigmoid function is tuned by fuzzy controller $\textbullet$ The choice of parameter for the sigmoid function is guided by FC. $\textbullet$ The parameter is continuously updated as boundary layer thickness varies. $\textbullet$ The proposed method hasbetter tracking performance than the conventional linear interpolation $\textbullet$ To demonstrate its performance the proposed control algorithm is applied to a nonlinear system.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.164.2-164
• /
• 2001

Sliding mode control (SMC) with variable nonlinear boundary layer is proposed. Two Fuzzy logic controllers (FLCs) are used to decide both boundary layer thickness and nonlinear interpolation using sigmoid function in the boundary layer. The nonlinear interpolation in the boundary layer suing FLC reduces stead state error and chattering. Sigmoid function is used to nonlinear interpolation in the boundary layer sigmoid function parameter with FLC. To demonstrate its performance, the Proposed control algorithm is applied to a simple nonlinear system.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.4
• /
• pp.281-292
• /
• 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 the Korean Society for Precision Engineering
• /
• v.30 no.8
• /
• pp.824-830
• /
• 2013

We propose a tracking control system for butterfly valves. A sliding mode controller with a fuzzy-neural network algorithm was applied to the design of the tracking control system. The control scheme used the real-time update law for the unmodeled system dynamics using a fuzzy-neural network algorithm. The performance of the proposed control system was assessed through a range of experiments.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1193-1195
• /
• 1996

For an automatic steering problem of vehicles, the main task is to keep a reference path with assumption that the displacement from the guideline can be measured by a sensor. In this paper, a sliding mode fuzzy logic controller design method is introduced and it shows highly enhanced performance in comparison with the other results. The method can be relatively simply implemented.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.4
• /
• pp.499-505
• /
• 2011

In this paper, we proposed an adaptive fuzzy sliding mode control for nonlinear systems without parameter projection method. By modifying the controller structure, the parameters of the estimated input gain function are guaranteed not being identically zero and it is shown that the control scheme will not cause any implementation problem even if the estimated value of input gain function is zero at any moment during on-line operations. Except for the input gain function which an approximate estimate for its lower bound is needed, the proposed control scheme does not assume a priori the exact values of the bounding parameters. Based on Lyapunov synthesis methods, the overall control system guarantees that the tracking error asymptotically converges to zero and that all signals involved in controller are uniformly bounded. This can be illustrated by the simulation results for an inverted pendulum system.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2292-2295
• /
• 2001

In this paper, The control problem for a series DC motor is considered to adaptive fuzzy sliding-mode control scheme. Based on a nonlinear mathematical model of a series connected DC motor, instead of the combination of a nonlinear transformation and state feedback(feedback linearization) reduces the nonlinear control design. To demonstrate its effectiveness, an experimental study of this controller is presented. Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target. The membership functions of the THEN-part, which is used to construct a suitable equivalent control of SMC, are changed according to the adaptive law. With such a design scheme, we not only maintain the distribution of membership functions over state space but also reduce computing time considerably.

• Proceedings of the KIEE Conference
• /
• 1998.07g
• /
• pp.2351-2353
• /
• 1998

This paper suggests the wheel controller for PWS(Power Wheeled Steering) mobile robot. The proposed controller consists of two parts. To control each motor, the sliding mode controller implemented. This method has robustness about modeling error and disturbance, so the velocity tracking is well guaranteed in the presence of varying load. The design of a fuzzy cross-coupling controller for a PWS mobile robot is described here. Fuzzy cross-coupling control directly minimizes the tracking error by coordinating the motion of the two drive wheels. The fuzzy cross-coupling controller has excellent disturbance rejection and therefore is advantageous when the robot is not loaded symmetrically. The capability of the proposed controller was verified through the computer simulation.

• International Journal of Computer Science & Network Security
• /
• v.24 no.2
• /
• pp.169-177
• /
• 2024

Interacting Spherical tank has maximum storage capacity is broadly utilized in industries because of its high storage capacity. This two tank level system has the nonlinear characteristics due to its varying surface area of cross section of tank. The challenging tasks in industries is to manage the flow rate of liquid. This proposed work plays a major role in controlling the liquid level in avoidance of time delay and error. Several researchers studied and investigated about reducing the nonlinearity problem and their approaches do not provide better result. Different types of controllers with various techniques are implemented by the proposed system. Intelligent Adaptive Neuro Fuzzy Inference System (ANFIS) based Sliding Mode Controller (SMC) with Fractional order PID controller is a novel technique which is developed for a liquid level control in a interacting spherical tank system to avoid the external disturbances perform better result in terms of rise time, settling time and overshoot reduction. The performance of the proposed system is obtained by analyzing the simulation result obtained from the controller. The simulation results are obtained with the help of FOMCON toolbox with MATLAB 2018. Finally, the performance of the conventional controller (FOPID, PID-SMC) and proposed ANFIS based SMC-FOPID controllers are compared and analyzed the performance indices.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.382-386
• /
• 1992

In this paper, the author proposed FLVSC(Fuzzy Logic Variable Structure Controller), of which control rules are extracted from the concepts of VSC(Variable Structure Control). FLC(Fuzzy Logic Controller) based on linguistic rules has the advantages of not needing of some exact mathematical model for plant to be controlled. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbances, parameter variations and uncertainties in sliding mode. In addition, the method has the properties of FLC - noise rejection capability etc. The computer simulations have been carried out for a DC servo motor to show the usefulness of the proposed method and the effects of disturbances and parameter variations are considered.