• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.103.1-103
• /
• 2002

In variable structure control algorithms, The control law used to realized the desired sliding mode dynamics is discontinuous on the switching manifold. However, due to imperfections in switching, such as time delays, the system trajectory chatters instead of sliding along the switching manifold. This chattering is undesirable because it may excite unmodeled high frequency dynamics in the physical system. In this paper, to overcome this drawback a self-organizing fuzzy sliding mode control algorithm using gradient descent method is proposed. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties ill the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.

• Proceedings of the KIEE Conference
• /
• 1995.11a
• /
• pp.293-295
• /
• 1995

In this article a fuzzy controller and neural network adaptive observer is proposed and applied to the case of induction motor control. The proposed observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subjected to further on-line training by means of a backpropagation algorithm. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.351-351
• /
• 2000

Since the heat exchange system, such as the boiler of power plant, gas turbine, and radiator require an application of intelligent control system for a high rate heat efficiency and the efficiency of these systems is depended on the control methods it is important for operator to understand control system of these systems and intelligent control technologies. In order to properly apply control equipment and intelligent technology to these process control systems, it is necessary to understand fuzzy, neural network, genetics, and immune as well as the basic aspects and operation principle of the process that relate control, interrelationships of the process characteristics, and the dynamics that are involved. Generally, since PID controllers are used in these systems it is difficult far engineer to understand both the complex dynamics and the intelligent control method. In this paper, we design an effective experimental system for the intelligent control education and analyze its characteristics through experimental system and each intelligent method to study how they can learn intelligent control system by experiments.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.20 no.2
• /
• pp.15-20
• /
• 2012

This study is to propose and develop an integrated dynamics control system to improve and enhance the lateral stability and handling performance. To achieve this target, we integrate an AFS and a 4WS systems with a fuzzy logic controller. The IDCS determines active additional steering angle of front wheel and controls the steering angle of rear wheel. The results show that the IDCS improves the lateral stability and controllability on dry asphalt and snow paved road when double lane change and step steering inputs are applied. Yaw rate of the IDCS vehicle tracks reference yaw rate very well and body slip angle is reduced about by 50%. Response time of the IDCS vehicle is also decreased.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.17 no.4
• /
• pp.70-75
• /
• 2018

This paper describes an Integrate Dynamic Control system with Brake System (IDCB) for SUV vehicles. The system was developed to stabilize the lateral dynamics, maintain the steerability and improve the ride comfort on various roads. A fuzzy logic control method is used to design the IDCB. The performance of the IDCB is validated under different road and driving conditions. The results show that the IDCB tracks the reference yaw rate under all tested conditions; in addition, it reduces the body slip angle and roll angle. When a vehicle runs on a split-${\mu}$ road and a brake input is applied, the IDCB virtually eliminates the lateral dynamics. Thus, the IDCB improves the lateral stability, preserves the steerability and enhances the ride comfort of vehicles.

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

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.3
• /
• pp.275-284
• /
• 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 Institute of Control, Robotics and Systems
• /
• v.2 no.4
• /
• pp.279-286
• /
• 1996

In this paper, variable structure control(VSC) based on reaching law method with fuzzy inference for nonlinear systems is proposed. The reaching law means the reaching condition which forces an initial state of system to reach switching surface in finite time, and specifies the dynamics of a desired switching function. Since the conventional reaching law has fixed coefficients, the chattering can be existed largely in sliding mode. In the design of a proposed fuzzy reaching law, we fuzzify RP(representative point)'s orthogonal distance to switching surface and RP's distance the origin of the 2-dimensional space whose coordinates are the error and the error rate. The coefficients of the reaching law are varied appropriately by the fuzzy inference. Hence the state of system in reaching mode reaches fastly switching surface by the large values of reaching coefficients and the chattering is reduced in sliding mode by the small values of those. And the effectiveness of the proposed fuzzy reaching law method is showen by the simulation results of the control of a two link robot manipulator.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.2
• /
• pp.151-156
• /
• 2008

This paper presents the stability analysis and design for a sampled-data fuzzy control system with neutral type of time delay, which is formed by a nonlinear plant and a sampled-data fuzzy controller connected in a closed loop. The sampling activity and neutral type of time delay will complicate the system dynamics and make the stability analysis much more difficult than that for a pure continuous-time fuzzy control system. Based on the fuzzy-model-based control approach, LMI(linear matrix inequality)-based stability conditions are derived to guarantee the nonlinear networked system stability. An application example will be given to show the merits and design a procedure of the proposed approach.

• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2002.03a
• /
• pp.459-466
• /
• 2002

In this study magneto-rheological damper, a kind of semi-active device, is used to reduce the response of pier and girder of bridge structure subjected to seismic excitation and as a effective semi-active control method fuzzy control technique considering nonlinear behavior of the damper dynamics. By Numerical simulations of a nine span continuous bridge system subjected to various earthquakes, fuzzy control technique is compared with existing clipped optimal control technique in control performance which reduces displacement of pier and girder simultaneously. In the comparison of the control performance within a control force limit, it is confirmed that presented fuzzy control technique more efficiently reduce the pier and girder displacement than clipped optimal control technique based on optimal control theory.