• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.207-214
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• 2010

This paper proposes about decentralized control approach based Leader-Follower formation control using LOS (Line of Sight) algorithm and unknown input observer. The position of robots which is a basic information in multi-robot or single robot motion control is determined by localization algorithm fusing UPS (Ultrasonic Position System) and kinematics model. For formation control, a decentralized control approach individually installing a local controller in leader and follower robot is adopted. Leader robot is controlled to track a specified trajectory by LOS algorithm, and the other robots follow the leader by local controller based on tracking platoon level function, self-sensing data and estimated information from unknown input observer. The performance of proposed method is proven through the formation experiment of two vehicle models.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.201-204
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• 1998

This paper presents a new construction method of candidate controllers using Multi-modal Neural Network(MNN). To improve a control performance of multiple controller, we construct, candidate controllers which consist of MNN. MNN can learn more complicated function than multilayer neural network. MNN consists of preprocessing module and neural network module. The preprocessing module transforms input signals into spectra which are used as input of the following neural network module. We apply the proposed method to multiple control system which controls the cart-pole balancing system and show the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3120-3122
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• 1999

In this paper we have designed the signal processing system for driving the Poly-Si TFT LCD of EWS. The signal processing system consist of timing controller, ramp signal generator and video signal processing system. Timing controller includes the top-down inversion. left right inversion, left-right shifting and control signal generator according to multi-source signal. The video signal processing system generates sawtooth-shaped waveform by using PROM and DAC for multi-gray scales and implements gamma correction function for compensating the TFT-LCD nonlinear charcteristic of the TFT-LCD. Finally we have discussed the experiment results and its application according to the designed TFT-LCD driving system.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.4
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• pp.349-358
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• 2013

In this paper, the sensorless MPPT algorithm is proposed where the performance of varied duty ratio change has been improved using multi-layer neuro-fuzzy that aligns with neuro-fuzzy based optimized membership function. Since the change of duty ratio of sensorless MPPT is varied by using the neuro-fuzzy, the MPPT response speed is faster than the convectional method and is able to reduce the steady-state ripple. The neuro fuzzy controller has the response characteristics which is superior to the existing fuzzy controller, because of the usage of the optimal width of the fuzzy membership function. The effectiveness of the proposed method has been verified by simulations and experimental results.

• Journal of Power Electronics
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• v.7 no.1
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• pp.1-12
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• 2007

Novel nonlinear backstepping control with integrated adaptive control function is developed for high-performance positioning control systems. The proposed schemes are synthesized by a systematic approach and implemented based on a modern low-cost DSP controller, TMS320C32. A baseline backstepping control scheme is derived first, and is then extended to include a nonlinear adaptive control against the system parameter changes and load variations. The backstepping control utilizes Lyapunov function to guarantee the convergence of the position tracking error. The final control algorithm is a convenient in the implementation of a practical 32-bit DSP controller. The new control system can achieve superior performance over the conventional nested PI controllers, with improved position tracking, control bandwidth, and robustness against external disturbances, which is demonstrated by experimental results.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.657-660
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• 2003

Control of multi-link robot arms is a very difficult problem because of the highly nonlinear dynamics. Decentralized control scheme is developed for control of robot manipulators based on RBF(Radial Basis Function) Neural Networks. RBF Neural Networks is used to approximate the coupling forces among the joints, coriolis force, centrifugal force, gravitational force, and frictional force. The compensation controller is also proposed to estimate the bound of approximation error so that the chattering effect of the control effort can be reduced. The proposed scheme does not require an accurate manipulator dynamic, and it is proved that closed-loop system is asymptotic stable despite the gross robot parameter variations. Numerical simulations for two-link robot manipulator are included to show the effectiveness of controller.

• Journal of Power Electronics
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• v.12 no.1
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• pp.104-112
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• 2012

In this paper a new method for the design of a simple PI controller is presented and it has been applied in the control of a Boost based PFC rectifier. The Strength Pareto evolutionary algorithm, which is based on the Pareto Optimality concept, used in Game theory literature is implemented as a multi-objective optimization approach to gain a good transient response and a high quality input current. In the proposed method, the input current harmonics and the dynamic response have been assumed as objective functions, while the PI controller's gains of the PFC rectifier (Kpi, Tpi) are design variables. The proposed algorithm generates a set of optimal gains called a Pareto Set corresponding to a Pareto Front, which is a set of optimal results for the objective functions. All of the Pareto Front points are optimum, but according to the design priority objective function, each one can be selected. Simulation and experimental results are presented to prove the superiority of the proposed design methodology over other methods.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.339-349
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• 2017

In this paper, we present a finite-time sliding mode control (FSMC) with an integral finite-time sliding surface for applying the concept of graph theory to a distributed wheeled mobile robot (WMR) system. The kinematic and dynamic property of the WMR system are considered simultaneously to design a finite-time sliding mode controller. Next, consensus and formation control laws for distributed WMR systems are derived by using the graph theory. The kinematic and dynamic controllers are applied simultaneously to compensate the dynamic effect of the WMR system. Compared to the conventional sliding mode control (SMC), fast convergence is assured and the finite-time performance index is derived using extended Lyapunov function with adaptive law to describe the uncertainty. Numerical simulation results of formation control for WMR systems shows the efficacy of the proposed controller.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.273-280
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• 2001

In this study, a driver model based on the lead-lag controller for stable maneuver of a highly nonlinear, multi-dimensional, numerically stiff multibody vehicle model according to the various handling test requirements such as steady-state cornering, double lange change, etc. is presented The lead-lag controller is developed with lead and lag compensation. which use the transfer function with cross-over frequency by frequency response method. The proposed driver model is applied to a vehicle model in steady-state and slalom maneuver to verify its effectiveness and validity. The results show that the proposed path control strategy is excellent both in pursuing the desired course and stability of the vehicle.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.351-359
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• 2007

In this study, a hierarchical switching control scheme based on robust control theory is proposed for tracking control of vehicle longitudinal acceleration in the presence of large uncertainties. A model set consisting of four multiplicative-uncertainty models is set up, and its corresponding controller set is designed by the LMI approach, which can ensures the robust performance of the closed loop system under arbitray switching. Based on the model set and the controller set, a switching index function by estimating the system gain of the uncertainties between the plant and the nominal model is designed to determine when and which controller should be switched into the closed loop. After theoretical analyses, experiments have also been carried out to validate the proposed control algorithm. The results show that the control system has good performance of robust stability and tracking ability in the presence of large uncertainties. The response time is smaller than 1.5s and the max tracking error is about $0.05\;m/S^2$ with the step input.