• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.503-507
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• 1989

A new decentralized adaptive controller design is proposed. In large scale interconnected system with unknown parameters, nonlinearities and bounded disturbances, even though the interconnection is weak, the controller parameter drifts due to the interconnection, so the decentralized adaptive controller comes to be unstable. The proposed new decentralized adaptive controller guarantees exponential convergence of tracking and parameter errors to residual sets which depend on the bound for the local disturbances and interconnections as well as on some arbitrary design parameters.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.526-538
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• 2007

This paper presents a neural network based decentralized excitation controller design for large-scale power systems. The proposed controller design considers not only the dynamics of generators but also the algebraic constraints of the power flow equations. The control signals are calculated using only local signals. The transient stability and the coordination of the subsystem control activities are guaranteed through rigorous stability analysis. Neural networks in the controller design are used to approximate the unknown/imprecise dynamics of the local power system and the interconnections. All signals in the closed loop system are guaranteed to be uniformly ultimately bounded. To evaluate its performance, the proposed controller design is compared with conventional controllers optimized using particle swarm optimization. Simulations with a three-machine power system under different disturbances demonstrate the effectiveness of the proposed controller design.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.459-464
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• 1998

In this paper, we propose a stable fuzzy logic controller architecture for inverted pendulum,. In the design procedure, we represent the fuzzy system as a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller by considering each local state feedback controller and a supervisory controller, Unlike usual parallel distributed controller, one can design a global stable fuzzy controller without finding a common Lyapunov function by the proposed method. A simulation is performed to control the inverted pendulum to show the effectiveness and feasibility of the proposed fuzzy controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.3-10
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• 1995

This paper proposedan on-line learning controller which can be applied to nonlinear systems. The proposed on-line learning controller is based on the universal approximation by the local affine mapping-based neural networks. It has self-organizing and learning capability to adapt itself to the new environment arising from the variation of operating point of the nonlinear system. Since the learning controller retains the knowledge of trained dynamics, it can promptly adapt itself to situations similar to the previously experienced one. This prompt adaptability of the proposed control system is illustrated through simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.387-392
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• 1992

This paper presents a local trajectory generation method which is based on a sequence of reference posture-velocities and the efficient low level control algorithm which constructs the complete smooth curve from the trajectory specification. The reference trajectory generator(RTG) which is in between the local path planner(LPP) and the robot motion controller(RMC) generates a sequence of set-points for each path segments from the LPP and pass it to the RMC. The RMC controls the motions of vehicle which should follow the sequence. In the feedback controller of VMC, the method which compensates robot posture-velocity error correctly is used. These methods are implemented on indoor autonomous vehicle, 'ALIVE' mobile robot. The ALIVE mobile robot system is implemented on the 32bit VME bus system: the two VME CPU's are used for RTG and RMC, while the 80C196KC-based VME board is used for motor controller.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.380-385
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• 2001

In this paper, in order to get rid of danger trapped Local minimum point, disadvantage of General Back-propagation and simultaneously obtain fast teaming-speed. We propose PID Back-Propagation with Momentum Term(PID-BPMT) and Design PID Controller by Neural Network with Momentum term. Consider to apply for that Controller in position control system by driven D.C servo motor. its useful performance is verified by computer simulation

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2408-2410
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• 2001

This paper presents the control of an underactuated two-link robot called the Pendubot. Combining linearized state feedback control with Takagi-Sugeno(T-S) fuzzy controller wide-range stabilization of Pendulum is achieved. The local stabilization controler is designed by linearinzing the dynamic equations about the several desired set point and using LQR(Linear Quadratic Regulator) techniques. Takagi-Sugeno methodology is used to control the nonlinear models near different operation points. Fuzzy controller is obtained by the fuzzy blending of the local controllers. The paper includes a description of the algorithm as well as real time experimental results for the Pendubot.

• Journal of Power Electronics
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• v.14 no.4
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• pp.733-741
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• 2014

The integration of photovoltaic (PV) energy sources into DC grid has gained considerable attention because of its enhanced conversion efficiency with reduced number of power conversion stages. During the integration process, a local control unit is normally included with every power conversion stage of the PV source to accomplish the process of maximum power point tracking. A centralized monitoring and supervisory control unit is required for monitoring, power management, and protection of the entire system. Therefore, we propose a field-programmable gate array (FPGA) based centralized control unit that integrates all local controllers with the centralized monitoring unit. The main focus of this study is on the process of integrating many local control units into a single central unit. In this paper, we present design and optimization procedures for the hardware implementation of FPGA architecture. Furthermore, we propose a transient analysis and control design methodology with consideration of the nonlinear characteristics of the PV source. Hardware experiment results verify the efficiency of the central control unit and controller design.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.6
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• pp.638-645
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• 2002

This paper presents a scheme for integrating PID control, gain scheduling and emerging techniques in the field of artificial intelligence, such as fuzzy logic and genetic algorithms for the speed control of a marine diesel engine. At first, local PID controllers are designed based on a local model obtained at each speed mode, whose parameters are optimally tuned using a real-coded genetic algorithm. Then, fuzzy "if-then" rules combine the local controllers as a consequence part to implement fuzzy gain scheduling. To demonstrate the performance of the proposed fuzzy PID controller on overall operating conditions, a set of simulation works on B'||'&'||'W's 4L80MC diesel engine are carried out.t.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.152-160
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• 2000

This paper addresses the analysis and design of fuzzy-model-based controller for nonlinear systems using extended PDC and optimal pole-placement schemes. In the design procedure, we represent the nonlinear system using a Takagi-Sugeno fkzy model and formulate the controller rules by using the extended parallel distributed compensator (EPDC) and construct an overall fuzzy logic controller by blending all local state feedback controllers with an optimal pole-placement scheme. Unlike the commonly used parallel distributed compensation technique, by blending a newly extended parallel distributed compensator and the optimal poleplacement schemes, we can design not only a local stable k z y controller but also an overall stable fuzzy controller to perform the tacking control objective. Furthermore, a stability analysis is carried out not only for the fuzzy model but also for a real nonlinear system. Finally. the effectiveness and feasibility of the proposed fizzy model-based controller design method has been shown through a simulation example.