• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.471-478
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• 2007

In this paper, an optimal Wiener-Hopf decoupling controller formula is obtained which is expressed in terms of rational matrices, thereby readily allowing the use of state-space algorithms. To this end, the characterization formula for the class of all realizable decoupling controller is formulated in terms of rational functions. The class of all stabilizing and decoupling controllers is parametrized via the free diagonal matrices and the optimal decoupling controller is determined from these free matrices.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.320.1-320
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• 2002

In a hard disk drive (HDD) control system, a state-space controller/observer design is popularly adopted fur its advantages such as effective filtering of position and velocity, use of estimation error to handle servo defects, etc. In this report, a systematic method is proposed to accommodate the transport delay in the plant dynamics into the state estimator. (omitted)

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.297-305
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• 1996

In this paper a novel robust adaptive fuzzy controller for the nonlinear system with state-dependent uncertainty is proposed. The conventional adaptive fuzzy controller determines the function of state variable bounding the state-dependent uncertain term in the system dynamics on the local state space by off-line calculation. Whereas the proposed method determines that function by the fuzzy inference so that it guarantees the stability of the closed loop system globally on the whole state space. In addition, the method is applicable to the multi-input system. We applied the proposed method to the Burn Control of the Tokamak fusion reactor whose dynamics contains the state-dependent uncertainty and proved the effectiveness of the scheme by using the simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.321-325
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• 1986

A new control scheme for the state space model of the robot system using the theory of optimal multi-variable structure is presented in this paper. It is proposed to optimize multi-dimensional variable structure systems for obtaining the required stabilizing signal by minimizing a performance index with respect to the state vector in the sliding mode. It is concluded the proposed variable structure controller yields better system dynamic performance than that obtained by using the only linear optimal controller inthat responses for a step disturbance have a shorter setting time, no matter what overshoot values and rising time.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.972-974
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• 1993

This paper presents a new method to automatically design fuzzy logic controller(FLC). The main problems of designing FLC are how to optimally and automatically select the control rules and the parameters of membership function (MF). Cell state space algorithms (CSS), differential competitive learning (DCL) and multialyer neural network are combined in this paper to solve the problems. When the dynamical model of a control process is known. CSS can be used to generate a group of optimal input output pairs(X, Y) used by a controller. The(X, Y) then can be used to determine the FLC rules by DCL and to determine the optimal parameters of MF by DCL and to determine the optimal parameters of MF by multilayer neural network trained by BP algorithm.

• Journal of Power Electronics
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• v.13 no.3
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• pp.400-408
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• 2013

This paper presents a discrete state-space controller using state feedback control and feed-forward decoupling to provide a desirable control bandwidth and control stability for dynamic voltage restorers (DVR). The paper initially discusses three typical applications of a DVR. The load-side capacitor DVR topology is preferred because of its better filtering capability. The proposed DVR controller offers almost full controllability because of the multi-feedback of state variables, including one-beat delay feedback. Feed-forward decoupling is usually employed to prevent disturbances of the load current and source voltage. Directly obtaining the feed-forward paths of the load current and source voltage in the discrete domain is a complicated process. Fortunately, the full feed-forward decoupling strategy can be easily applied to the discrete state-space controller by means of continuous transformation. Simulation and experimental results from a digital signal processor-based system are included to support theoretical analysis.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.1
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• pp.12-20
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• 2002

To control the noise of an enclosed sound field, we built a state space model using the acoustic modal parameter description. Using the state space model, we can investigate the controllability and observability, and find an appropriate position of control speaker and microphone to control sound field of the enclosed space. We implemented LQR(linear quadratic regulator) controller and reduced order observer to reduce the first acoustic mode. Experiments showed satisfactory results of 4∼10 dB reduction of magnitude of the first acoustic mode, and support the feasibility of the proposed scheme to lightly damped acoustic field.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.864-867
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• 1990

In this paper, a state space solution to the discete time H$_{\infty}$ control problem is presented. It is shown that there exist LQ game problem corresponding to H$_{\infty}$ control problems and the H$_{\infty}$ controller can be obtained by solving the LQ game problem. Explicit state space formulae are given for the state feedback H$_{\infty}$ controller and output feedback H$_{\infty}$ controllers.lers. state feedback $H_{\infty}$ controller and output feedback $H_{\infty}$ controllers.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.76-85
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• 2022

One of the most fundamental challenges when designing controllers for dynamic systems is the adjustment of controller parameters. Usually the system model is used to get the initial controller, but eventually the controller parameters must be manually adjusted in the real system to achieve the best performance. To avoid this manual tuning step, data-driven methods such as machine learning were used. Recently, reinforcement learning became one alternative of this problem to be considered as an agent learns policies in large state space with trial-and-error Markov Decision Process (MDP) which is widely used in the field of robotics. However, on initial training step, as an agent tries to explore to the new state space with random action and acts directly on the controller parameters in real systems, MDP can lead the system safety-critical system failures. Therefore, the issue of 'safe exploration' became important. In this paper we meet 'safe exploration' condition with Control Barrier Function (CBF) which converts direct constraints on the state space to the implicit constraint of the control inputs. Given an initial low-performance controller, it automatically optimizes the parameters of the control law while ensuring safety by the CBF so that the agent can learn how to predict and control unknown and often stochastic environments. Simulation results on a quadrotor UAV indicate that the proposed method can safely optimize controller parameters quickly and automatically.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1146-1155
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• 2017

Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.