• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.12-18
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• 2011

This paper deals with a new adaptive fuzzy sliding mode controller and its application to an inverted pendulum. We propose a new method of adaptive fuzzy sliding mode control scheme that the fuzzy logic system is used to approximate the unknown system functions in designing the SMC of uncertain nonlinear systems. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. Sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.356-362
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• 2002

In this paper, well-known Takagi-Sugeno fuzzy model is used as the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. Based on the fuzzy models, a numerical robust stability analysis for the fuzzy feedback linearization regulator is presented using Linear Matrix Inequalities (LMI) Theory. For these structured uncertainty, the closed system can be cast into Lur'e system by simple transformation. From the LMI stability condition for Lur'e system, we can derive the robust stability condition for the fuzzy feedback linearization regulator based on Takagi-Sugeno fuzzy model. The effectiveness of the proposed analysis is illustrated by a simple example.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.407-414
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• 2000

This paper addresses the analysis and design of fuzzy control systems for a class of complex uncertain single-input single-output nonlinear systems. The proposed method represents the nonlinear system using a Takagi-Cugeno fuzzy model and construct a global fuzzy logic controller by blending all local state feedback controllers with a sliding mode controller. Unlike the commonly used parallel distributed compensation technique, we can design a global stable fuzzy controller without finding a common Lyapunov function for all local control systems, and can obtain good tracking performance by using sliding mode control theory. Furthermore, stability analysis is carried out not for the fuzzy model but for the real nonlinear system with uncertainties. Duffing forced oscillation sysmte is used as an example to show the effectiveness and feasibility of the proposed method.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.274-284
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• 2000

In this paper, the design methodology of digital fuzzy controller(DFC) for the systems with time-delay is presented and the qualitative effects of the quantizers in digital implementation of a fuzzy controllers are investigated. We propose the fuzzy feed-back controller whose output is delayed with unit sampling period and period and predicted. the analysis and the design problem considering time-delay become very easy because the proposed controller is syncronized with the sampling time. The stabilization problem of the digital fuzzy system with time-delay is solved by linear matrix inequality(LMI) theory. Furthermore, we analyze the stability of the quantized fuzzy system. Our results prove that when quantization os taken into account, one only has convergence to some small neighborhood about origin. We develop a fuzzy control system for backing up a computer-simulated truck-trailer with the consideration of time-delay and quantization effect. By using the proposed method, we analyze the quantization effect to the system and design a DFC which guarantees the stability of the control system in the presence of time-delay.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.572-577
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• 2005

This paper applies the fuzzy logic controller to a semiactive seat suspension system in order to obtain the better ride comfort in constraint of specific rattle space. The seat suspension system used for this research is a scissors-type one with the MR (Magneto Rheological) fluid damper. Since a seat suspension system with a driver can not be exactly modeled, it is effective to control with the fuzzy logic controller. The rule was carefully tuned to effectively reduce the vibration transmitted to a driver. The on-road ride was realized on a hydraulic excitor and the result shows that the fuzzy controller has reduced the vibration of a seat suspension system compared to the continuous skyhook controller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.644-649
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• 2006

This paper presents a robust and superior control performance of a quarter-vehicle electrorheological (ER) suspension system. In order to achieve this goal, a moving sliding mode control algorithm is adopted, and its moving strategy is tuned by fuzzy logic. As a first step, ER damper is designed and manufactured for a passenger vehicle suspension system, and its field-dependent damping force is experimentally evaluated. After formulating the governing equation of motion for the quarter-vehicle ER suspension system, a stable sliding surface and moving algorithm based on fuzzy logic are formulated. The fuzzy moving sliding mode controller is then constructed and experimentally implemented. Control performances of the ER suspension system are evaluated in both time and frequency domains.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.33-42
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• 1995

A practical application of a fuzzy-neuro controller is described for an air-conditioning system. Air-handing units are being widely used for improving the performance of central air-conditioning systems. The fuzzy-neuro control system has two controlled variables, temperature and humidity and three control elements, cooling, heating, and humidification. In order to achieve high efficiency and economical contorl, especially in large offices and industrial buildings, two controllable parameters, temperature and humidity, must be adequately controlled by the three final controlling elements. In this paper a fuzzy-neuro control system is described for controlling air-conditioning systems efficiently and economically. Simulation results confirmed that the fuzzy neuro control system is effective for this multivariable system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.8 s.113
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• pp.822-829
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• 2006

This paper presents a robust and superior control performance of a quarter-vehicle electrorheological (ER) suspension system. In order to achieve this goal, a moving sliding mode control algorithm is adopted, and its moving strategy is tuned by fuzzy logic. As a first step, ER damper is designed and manufactured for a passenger vehicle suspension system, and its field-dependent damping force is experimentally evaluated. After formulating the governing equation of motion for the quarter-vehicle ER suspension system, a stable sliding surface and moving algorithm based on fuzzy logic are formulated. The fuzzy moving sliding mode controller is then constructed and experimentally implemented. Control performances of the ER suspension system are evaluated in both time and frequency domains.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.344-351
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• 2007

In this paper, we propose an approach to design multi-fuzzy controllers for the superheat and the low pressure that have an influence on energy efficiency and stabilization of air conditioning system with multi-evaporators. Air conditioning system with multi-evaporators is composed of compressor, condenser, several evaporators and several expansion valves. It is quite difficult to control the air conditioning system because the change of the refrigerant condition give an impact on the overall air conditioning system. In order to solve the drawback, we design multi-fuzzy controllers which control simultaneously both three expansion valve and one compressor for the superheat and the low pressure of air conditioning system. The proposed multi fuzzy controllers are given as a kinds of controller types such as a simplified fuzzy inference type. Here the scaling factors of each fuzzy controller are efficiently adjusted by Hierarchical Fair Competition-based Genetic Algorithms. The values of performance index of the simulation results of the A company type compare with simulation results of simplified inference type.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.959-964
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• 1993

We developed fault diagnosis fuzzy expert system for ACS(Advanced Control System). ACS is a DCS(Distributed Control System) with advanced control algorithm fault tolerance capabilities, fault diagnosis functions, and so on. Fuzzy expert system developed for an ACS in this paper gives an operator alarm signal depending on the state of process value and manipulated value, and the cause of alarm in real time. Simple experiment result with several rules for the-fault-diagnosis of drum level loop in Seoul-Power-Plant.