• Proceedings of the KSME Conference
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• 2001.06b
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• pp.253-258
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• 2001

This paper introduces a simple nonlinear adaptive control method for pipeline inspection gauge (PIG) flow in natural gas pipeline. The dynamic behavior of the PIG depends on the different pressure across its body and the bypass flow through it. The system dynamics includes: dynamics of driving gas flow behind the PIG, dynamics of expelled gas in front of the PIG, and dynamics of the PIG. The method of characteristics (MOC) and Runger-Kuta method are used to solve the dynamics of flow. The PIG velocity is controlled through the amount of bypass flow across its body. A simple nonlinear adaptive controller based on the backstepping method is introduced. To derive the controller, three system parameters should be measured: the PIG position, its velocity and the velocity of bypass flow across the PIG body. The simulation has been done with a pipeline segment in the KOGAS low pressure system, Ueijungboo-Sangye line to verify the effectiveness of the proposed controller. Three cases of interest are considered: the PIG starts to move at its launcher, the PIG arrives at its receiver and the PIG restarts after stopping in the pipeline by obstruction. The simulation results show that the proposed nonlinear adaptive controller attained good performance and can be used for controlling the PIG velocity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.701-704
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• 2005

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They are difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.1
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• pp.14-21
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• 2001

This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. In indirect adaptive fuzzy control, based on the proved approximation capability of fuzzy systems, they are used to capture the unknown nonlinearities of the plant. Until now, most of the papers in the field of controller design for nonlinear system considers the affine system using fuzzy systems which have fixed grid-rule structure. We proposes a dynamic fuzzy rule insertion scheme where fuzzy rule-base grows as time goes on. With this method, the dynamic order of the controller reduces dramatically and an appropriate number of fuzzy rules are found on-line. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed-loop system is guaranteed.

• Proceedings of the KIPE Conference
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• 2008.10a
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• pp.199-201
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• 2008

In this paper proposed the solar tracking system to use direct fuzzy control order to increase an output of the PV (Photovoltaic) array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studied. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up, nonlinear altitude and azimuth. In this paper designed a DFC(Direct Fuzzy Control)controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.280-284
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• 1997

In this paper, Nonlinear VSS control based on bang-bang control concept is derived under the assumption that the control input is bounded. We try to derive control algorithm which has almost same performance as the time optimal control. We focus this control scheme on the real implementation of DC motor position controller of flexible link, i.e. we obtain the switching curves from the real data of DC motor system operating under the full maximum and minimum applied voltages. State space is separated into several regions and we set different switching surfaces in each region to reduce chattering problem. The efficiency of the proposed controller is compared with PID controller and it is shown that the controller converges fast than PID controller without chattering. The hybrid controller scheme is also proposed not only to control the position of hub but also to reduce the vibration of end tip of flexible link.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.390-393
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• 2007

In this paper, applications of self recurrent neuro-fuzzy controller to stabilization of nonlinear system are considered. The architecture of self recurrent neuro-fuzzy controller is fix layer, and the hidden layer is comprised of self recurrent architecture. Also, generalized dynamic error-backpropagation algorithm is used for the learning of the self recurrent neuro-fuzzy controller. To demonstrate the efficiency of the self recurrent neuro-fuzzy control algorithm presented in this study, a self recurrent neuro-fuzzy controller was designed and then a comparative analysis was made with LQR controller through an simulation.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.123-129
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• 1996

Computed torque method has been used for precise trajectory control of the robotic system that involves nonlinear dynamics. It is hard to know exact values of robot system parameters, and the robot arm receives umpredictable interference from the working environment. These disturbances, especially in a direct drive robot, are directly transmitted to actuating motor without reduction. Modelling error and distrubance can cause significant errors in a trajectory tracking problem. In this paper, we propose a new controller that $H_{\infty}$controller is conbined to robot system linearized by computed torque. Simula- tions are made for comparing the performance of the proposed controller with that of a nonlinear $H_{\infty}$ controller proposed by Chen and also computed torque method.hod.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.85-86
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• 2006

In this paper, a nonlinear controller based on adaptive sliding-mode method which has a sliding surface vector including new boundary function is proposed and applied to a two-wheeled voiding mobile robot (WMR). This controller makes the welding point of WMR achieve tracking a reference point which is moving on a smooth curved welding path with a desired constant velocity. The mobile robot is considered in view of a kinematic model and a dynamic model in Cartesian coordinates. The proposed controller can overcome uncertainties and external disturbances by adaptive sliding-mode technique. To design the controller, the tracking error vector is defined, and then the new sliding is proposed to guarantee that the error vector converges to zero asymptotically. The stability of the dynamic system will be shown through the Lyapunov method. The simulations is shown to prove the effectiveness of the proposed controller.

• Journal of Industrial Technology
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• v.16
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• pp.231-237
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• 1996

In this paper, the nonlinear I/O characteristic of fuzzy logic controller is analyzed by using cell concept. Sources of the nonlinearity in a fuzzy logic controller include the fuzzification, the fuzzy reasoning and the defuzzification. A closed form expression for the defuzzified output is derived in case of a fuzzy logic controller with two inputs, triangular memberships, MacVicar-Whelan type linguistic rules, and direct fuzzy reasoning. As a result, it is shown that fuzzy logic controller is a nonlinear controller. Also its nonlinearity is analyzed with respect to the conventional PID control and the sliding mode control.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.138-138
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• 2000

In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a prefilter, the inverse dynamic model of a system and a fuzzy logic controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system is characterized by a nonlinear equation with coulomb friction. The fuzzy logic controller regulates the error between the set-point and the system output which may be caused by disturbances and it simultaneously traces the change o( the reference input. The parameters of the model are estimated by a genetic a]gorithm. An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller