• 제어로봇시스템학회논문지
• /
• 제5권3호
• /
• pp.257-266
• /
• 1999

The aim of this paper is to suggest a design method of the optimal multivariable $H_{\infty}$ control system using genetic algorithm (GA). This $H_{\infty}$ control system is designed by applying GA to the optimal determination of weighting functions and design parameter $\gamma$ that are given by Glover-Doyle algorithm which can design $H_{\infty}$ controller in the state space. The first method to do this is that the gains of weighting functions and $\gamma$ are optimized simultaneously by GA with tournament method. And the second method is that not only the gains and $\gamma$ but also the dynamics of weighting functions are optimized at the same time by eA with roulette-wheel method. The effectiveness of this $H_{\infty}$ control system is verified by computer simulation.

• Journal of Power Electronics
• /
• 제13권3호
• /
• pp.419-428
• /
• 2013

The modular multilevel cascade converter (MMCC) is a new family of multilevel power converters with modular realization and a cascaded pattern for submodules. The MMCC family can be classified by basic configurations and submodule types. One member of this family, the Hexverter, is configured as Double-Delta Full-Bridge (DDFB). It is a novel multilevel AC/AC converter with direct power conversion and comparatively fewer required components. It is appropriate for connecting two three-phase systems with different frequencies and driving an AC motor directly from a utility grid. This paper presents the dq model of a Hexverter with both of its AC systems by state-space representation, which then simplifies the continuous time-varying model into a periodic discrete time-invariant one. Then a generalized multivariable optimal control strategy for regulating the Hexverter's independent currents is developed. The resulting control structure can be adapted to other MMCCs and is flexible enough to include other control criterion while guaranteeing the original controller performance. The modeling method and control design are verified by simulation results.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 하계학술대회 논문집 B
• /
• pp.1002-1004
• /
• 1999

The aim of this paper is to suggest a design method of the optimal multivariable $H_{\infty}$ control system using genetic algorithm(GA). This $H_{\infty}$ control system is designed by applying GA to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design $H_{\infty}$ controller in the state space. The effectiveness of this $H_{\infty}$ control system is verified by nonlinear simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제3권1호
• /
• pp.78-86
• /
• 2003

Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

• 제어로봇시스템학회논문지
• /
• 제5권7호
• /
• pp.808-813
• /
• 1999

A fuzzy learning method to control an unstable and multivariable system is presented in this paper, Because the multivariable system has generally a coupling effect between the inputs and outputs, it is difficult to find its modeling equation or parameters. If the system is unstable, initial condition rules are needed to make it stable because learning is nearly impossible. Therefore, this learning method uses the initial rules and introduces a cost function composed of the actual error and error-rate of each output without the modeling equation. To minimize the cost function, we experimentally got the Jacobian matrix in the operating point of the system. From the Jacobian matrix, we can find the direction of the convergence in the learning, and the optimal control rules are finally acquired when the fuzzy rules are updated by changing the portion of the errors and error rates.

• International Journal of Control, Automation, and Systems
• /
• 제1권1호
• /
• pp.1-10
• /
• 2003

This paper presents a high-precision magnetically levitated (maglev) stage to meet demanding motion specifications in the next-generation precision manufacturing and nanotechnology. Characterization of dynamic behaviors of such a motion stage is a crucial task. In this paper, we address the issues related to the stochastic modeling of the stage including transfer function identification, and noise/disturbance analysis and prediction. Provided are test results on precision dynamics, such as fine settling, effect of optical table oscillation, and position ripple. To deal with the dynamic coupling in the platen, we designed and implemented a multivariable linear quadratic regulator, and performed time-optimal control. We demonstrated how the performance of the current maglev stage can be improved with these analyses and experimental results. The maglev stage operates with positioning noise of 5 nm rms in $\chi$ and y, acceleration capabilities in excess of 2g(20 $m/s^2$), and closed-loop crossover frequency of 100 Hz.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
• /
• pp.485-492
• /
• 1990

This paper propose a optimal design method for robust notion controllers of under-water vehicles using the combined technique between classical and modern theories. The proposed method is presented which utilizes classical control methods to obtain a good robustness and modern control methods to set optimal gains. LQ, SVD, multivariable frequency analysis and Bode-Root Locus (BRL) plot are used.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1994년도 추계학술대회 논문집
• /
• pp.449-454
• /
• 1994

The Stewart Platform is one example of a motion simulator which generater 6DOF motion in space by six actuators in parallel. The presented control methrol of 6DOF motion simulator is generally classified into two types, one is SISO and the other is MIMO control type. The SISO control can't compensate for external load variation and different dynamic behavior of 6DOF motion, trerefore this type don's control motion precisely. On the other hand, the MIMO control compensates for a interference of 6DOF motion because MIMO controller is designed with 6DOF motion simulator synamics. But MIMO control of motion simulator has a complexity of 6DOF displacement feedback, because in oder to obtain feedback value we must solve the forward kinematics using measurement of cylinder length or design a state estimator, unless measurement of 6DOF displacement is possible. In this paper, a multivariable controller using H .inf. optimal control theory is designed to consider a interference of 6DOF motion and to obtain robust,precise control of system. Also in order to solve the mentioned problem of MIMO control, this paper presents a modified MIMO control model which control 6DOF motion by using feedback of measurement od cylinder length.

• 한국정밀공학회지
• /
• 제24권12호
• /
• pp.57-64
• /
• 2007

There have been many researches for optimal controllers in multivariable systems, and they generally use accurate linear models of the plant dynamics. Real systems, however, contain nonlinearities and high-order dynamics that may be difficult to model using conventional techniques. Therefore, it is necessary a PID gain tuning method without explicit modeling for the multivariable plant dynamics. The PID tuning method utilizes the sign of Jacobian and gradient descent techniques to iteratively reduce the error-related objective function. This paper, especially, focuses on the role of I-controller when there is a steady state error. However, it is not easy to tune I-gain unlike P- and D-gain because I-controller is mainly operated in the steady state. Simulations for an overhead crane system with dynamic friction show that the proposed PID-LC algorithm improves controller performance, even in the steady state error.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.2258-2263
• /
• 2003

This paper presents the design and development of an optimal fuzzy logic controller (FLC) for a laser tracking system. An optimal intelligent fuzzy logic controller was founded on integral criterion of the fuzzy models and three-dimensional fuzzy control. Research had been also concentrated on the methods for multivariable fuzzy models for the purposes of real-time process. Simulation results have shown remarkable tracking performance of this fuzzy PID controller.