• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.158-160
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• 2005

This paper presents a new approach to the problem of designing a cascaded three-parameters controller for a given linear time invariant (LTD plant in unity feedback system. We consider a proportional-integral-derivative (PID) and a first-order controller with specified overshoot and settling time. This problem is difficult to solve because there may be no analytical solution due to the use of low-order controller and furthermore. the zeros of controller just appear in the zeros of feedback system. The key idea of our method is to impose a constraint on the controller parameters so that the zeros of resulting controller are distant from the dominant pole of closed-loop system to the left as far as the given interval. Two methods realizing the idea are suggested. We have employed the characteristic ratio assignment (CRA) in order to deal with the time response specifications. It is noted that the proposed methods are accomplished only in parameter space. Several illustrative examples are given.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.1
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• pp.20-23
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• 2006

This paper presents a new approach to the problem of designing a cascaded three-parameters controller for a given linear time invariant (LTI) plant in unity feedback system. We consider a proportional-integral-derivative (PID) and a first-order controller with the specified overshoot and settling time. This problem is difficult to solve because there may be no analytical solution due to the use of low-order controller. Furthermore, the zeros of controller just appear in the zeros of feedback system. The key idea of our method is to impose a constraint on the controller parameters so that the zeros of resulting controller are distant from the dominant pole of closed-loop system to the left as far as the given interval. Two methods realizing the idea are suggested. We have employed the characteristic ratio assignment (CRA) in order to deal with the time response specifications. It is noted that the proposed methods are accomplished only in parameter space. Several illustrative examples are given.

• Journal of Power Electronics
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• v.15 no.3
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• pp.763-774
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• 2015

This study investigates the inherent influence of a DC-link voltage controller on both DC-link voltage control and the compensation performance of a three-phase, four-wire shunt active power filter (APF). A nonlinear variable-parameter DC-link voltage controller is proposed to satisfy both the dynamic characteristic of DC-link voltage control and steady-state compensation performance. Unlike in the conventional fixed-parameter controller, the parameters in the proposed controller vary according to the difference between the actual and the reference DC-link voltages. The design procedures for the nonlinear voltage controller with variable parameters are determined and analyzed so that the proposed voltage controller can be designed accordingly. Representative simulation and experimental results for the three-phase, four-wire, center-spilt shunt APF verify the analysis findings, as well as the feasibility and effectiveness of the proposed DC-link voltage controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.11
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• pp.599-609
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.228-231
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• 2000

A hybrid fuzzy controller by means of the genetic algorithms is presented. The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PlD's output in steady state by a fuzzy variable. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller. A auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller using genetic algorithms. The algorithms estimates automatical Iy the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA three kinds of estimation modes are effectively utilized. The HFCs are applied to the second process with time-delay. Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed in ITAE(Integral of the Time multiplied by the Absolute value of Error ) and other ways.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.126-132
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• 2016

The root-locus method is often employed when a controller is designed to find controller gain. It is usually used to determine one parameter gain while most controllers for industrial applications have more than one controller gain. For example PID controller has three controller gains, i.e. P, I, and D gains. Thus the conventional root-locus technique cannot complete the design of a controller with more than one controller gain. One way to overcome this drawback has been to apply the root-locus technique for one parameter while other parameters are assumed to be proportional to the parameter or to be constant. However this approach could lead to limited performance of the controller and if we try to adjust the proportional ratio or constants then it could be a long and tedious process of trial and error. Thus it is required to find an effective method for the root-locus technique to design controllers with more than one parameter. To this end this paper proposes an extended root-locus method for controllers with two parameters. In this paper Matlab is used as a computation tool to show the effectiveness of our method by solving examples numerically. As a result we obtained an extended root-locus illustrated in two-dimensional space for a control system with two parameters. The paper then presents how to find two controller gains based on this result of the extended root-locus. The main idea is that we can find the parameters by approaching the desired poles. It is expected that the proposed idea will help control engineers to easily design control systems using the root-locus technique, resulting in more accurate and faster control systems. Note that the extended root-locus idea can be applied to controller design problems with multiple parameters.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.161-166
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• 1990

In this paper, Proposed the robust controller for robot manipulator plus actuator with dynamic parameter uncertainties. In general, errors and uncertainties system parameters exist more or less between the actual system and mathematical model. To reduce these trems, used Lyapunov stability theorem. The performance of the controller is evaluated for the three degree of freedom robot manipulator plus actuator model with uncertainties of parameters and model errors.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.184-189
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• 2014

In this paper, a new design method of vibration suppression controller for multi-inertia (especially, 3-ineritia) resonance systems is proposed. The controller consists of a digital fuzzy controller for speed loop and a digital PI controller for current minor loop. The three scaling factor of the fuzzy controller and two PI controller gains are determined by Differential Evolution (DE). The DE is one of optimization techniques and a kind of evolutionary computation technique. In this paper, we have applied the DE/rand/1/bin strategy to design the optimal controller parameters. Comparing with the conventional design algorithm, the proposed method is able to shorten the time of the controller design to a large extent and to obtain accurate results. Finally, we confirmed the effectiveness of the proposal method by the computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.263-269
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• 1999

In this paper, an unifying design algorithm is presented for efficient digital implementation of continuous PID controller using general discrete orthogonal functions. The proposed algorithm is an algebraic method to determine controller parameters, which can unify controller design procedures divided into three ways. A set of linear equations for the controller design are derived from simple algebraic transformation based on general discrete orthogonal functions. By solving these equations, all of the controller parameters can be determined directly and simultaneously, which thus makes the design procedure systematic and straightforward. It does not involve any trial and error procedure, hence the difficulty of conventional approach can be avoided. The simulation results and discussions are given to demonstrate the efficiency of the proposed method.

• Journal of Power Electronics
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• v.16 no.2
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• pp.610-620
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• 2016

The compound active clamp zero voltage soft switching (CACZVS) three-phase power factor correction (PFC) converter has many advantages, such as high efficiency, high power factor, bi-directional energy flow, and soft switching of all the switches. Triple closed-loop PI controllers are used for the three-phase power factor correction converter. The control objectives of the converter include a fast transient response, high accuracy, and unity power factor. There are six parameters of the controllers that need to be tuned in order to obtain multi-objective optimization. However, six of the parameters are mutually dependent for the objectives. This is beyond the scope of the traditional experience based PI parameters tuning method. In this paper, an improved chaotic particle swarm optimization (CPSO) method has been proposed to optimize the controller parameters. In the proposed method, multi-dimensional chaotic sequences generated by spatiotemporal chaos map are used as initial particles to get a better initial distribution and to avoid local minimums. Pareto optimal solutions are also used to avoid the weight selection difficulty of the multi-objectives. Simulation and experiment results show the effectiveness and superiority of the proposed method.