• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.577-582
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• 1999

Using a sole input variable simplifies the design process for the fuzzy logic controller(FLC). This is called single-input fuzzy logic controller(SFLC). However it is still deficient in the capability of adapting to the varying operating conditions. We here design a single-input adaptive fuzzy logic controller(AFLC) using a switching function of the sliding mode control. The AFLC can directly incorporate linguistic fuzzy control rules into the controller. Hence some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules can be adjusted by an adaptive law. In the proposed AFLC center values of fuzzy sets are directly adjusted by a fuzzy logic system. We prove that 1) its closed-loop system is globally stable in the sense that all signals involved are bounded and 2)its tracking error converges to zero asymptotically. We perform computer simulation using a nonlinear plant.

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

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.146-152
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• 2002

Mold level control has been a major control task for continuous casting plants. The system involves nonlinearities such as stick-slip friction in the sliding gate, time-delay, friction force variations between molten steel and the inner wall of mold, and nozzle logging/unclogging. These complex problems should be solved to control mold level for steel cast. In this paper, we propose a neural fuzzy mold level control technique for solving these complex problems and give experiment studies to show the mold level control in continuous casting process.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.202-213
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• 1999

Adaptive Cruise Control (ACC) is one of key features on intelligent Transportation System(ITS). In ACC, the steering is done by a driver, but the engine throttle valve and the brake are controlled electronically. The relative velocity and distance from the preceeding vehicle are measured by radars or image processing units and relevant vehicular spacing is maintained in ACC control systems. In this study, vehicle longitudinal dynamics are modeled to simulate vehicle longitudinal maneuver and to design longtitudinal controllers for ACC vehicles. The control algorithm is designed based on the modeled vehicle longitudinal dynamics using a non-linear sliding mode control method. To verity the performance of the control algorithm, a real time numerical simulation program is developed on a Silicon Graphics workstation using C-language . A real time graphic program is alos develpe and integrated with the numerical simulation program.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.524-530
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• 2002

This note suggests a stepwise fuzzy moving sliding surface using Sugeno-type fuzzy system and presents a sliding mode control scheme using it. The fuzzy system has the angle of state error vector and the distance from the origin in the phase plane as inputs and a first-order linear differential equation as output. The surface initially passes arbitrary initial states and subsequently moves towards a predetermined surface via rotating or shifting. This method reduces the reaching and tracking time and improves robustness. Conceptually the slope of the Proposed fuzzy moving sliding surface increases stepwise in the stable region of the phase plane. The surface, however, rotates continuously because the surface is a fuzzy system. The asymptotic stability of the fuzzy sliding surface is proved. The validity of the proposed control scheme is shown in computer simulation for a second-order nonlinear system.

• Journal of Power Electronics
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• v.17 no.4
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• pp.1048-1057
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• 2017

An indirect matrix converter (IMC) is a modern power generation system that enables a direct ac/ac conversion without the need for any bulky and limited lifetime electrolytic capacitor. This system also allows four-quadrant operation, generation of sinusoidal output voltage waveforms with variable frequency and amplitude, and control of input power factor. This study proposes a pulse-width modulation-based sliding-mode controller to achieve unity input-power factor operation of the IMC independently of the active power exchanged with the grid, as well as a fast dynamic response. The designed equivalent control law determines, at each sampling period, the appropriate q-axis component of the modulated input current to be injected into the grid through the LC input filter. An integral term of the error is included in the expression of the sliding surface to increase the accuracy of the control method. A double space vector modulation method is used to synthesize the direction of the space vector of the input currents as required by the sliding-mode controller and the space vectors of the target output voltages. Simulation and experimental results are provided to show the effectiveness and evaluate the performance of the proposed control method.

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

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.93-99
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• 2003

One of the methods to simplify the design process for a fuzzy logic controller (FLC) is to reduce the number of variables representing the rule antecedent. This in turn decreases the number of control rules, membership functions, and scaling factors. For this purpose, we designed a single-input FLC that uses a sole fuzzy input variable. However, it is still deficient in the capability of adapting some varying operating conditions although it provides a simple method for the design of FLC's. We here design two simple-structured adaptive fuzzy logic controllers (SAFLC's) using the concept of the single-input FLC. Linguistic fuzzy control rules are directly incorporated into the controller by a fuzzy basis function. Thus some parameters of the membership functions characterizing the linguistic terms of the fuzzy control rules can be adjusted by an adaptive law. In our controllers, center values of fuzzy sets are directly adjusted by an adaptive law. Two SAFLC's are designed. One of them uses a Hurwitz error dynamics and the other a switching function of the sliding mode control (SMC). We also prove that 1） their closed-loop systems are globally stable in the sense that all signals involved are bounded and 2） their tracking errors converge to zero asymptotically. We perform computer simulations using a nonlinear plant.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.605-614
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• 1999

This paper addresses analysis and design of a class of complex single-input single-output fuzzy control systems. In the proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Therefore, the globally stable fuzzy controller is designed without finding a common Lyapunov matrix. and shows improved perfonnance and tracking results by taking the advantages of fuzzy-model-based control theory and sliding mode control theory. Furthennore, stability analysis is conducted not Ibr the fuzzy model but for the real underlying nonlinear system. Two numerical examples are included to show the effcctiveness and feasibility of the proposed fuzzy control method.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.788-792
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• 2001

Although the general sliding model control has the robust property, bounds on the disturbances and parameter variations should be known a prior to the designer of the control system. However, these bounds may not be easily obtained. Fuzzy logic provides an effective way to design a controller of the system with disturbances and parameter variations. Therefore, combination of the best feature of the fuzzy logic control and the sliding mode control is considered. In this paper, the adaptive fuzzy variable structure controller developed for variables of fuzzy logic. A variable length pendulum system is used to demonstrate the availability of the proposed algorithm.