• Journal of Advanced Marine Engineering and Technology
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• v.34 no.1
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• pp.92-101
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• 2010

Recently, the magnetic bearings which have many advantages such as no noise, less mechanical friction are widely applied to the suspension of rotors on the rotary machineries. However, the magnetic bearing system is inherently unstable, nonlinear and MIMO(multi-input-multi-output) system as well. In this paper, we design a state feedback controller using linear matrix inequality(LMI) to the multi-objective synthesis, for the magnetic bearing system with integral type servo system. The design objectives include $H_{\infty}$ performance, asymptotic disturbance rejection, and time-domain constraints on the closed-loop pole location. The results of computer simulation show the validity of the designed controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.459-464
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• 2001

This paper discusses a stochastic stabilization of Takagi-Sugeno(TS) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delary of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time TS fuzzy system with the Markovian input delay is discretized for easy handling delay, according, the discretized TS fuzzy system is represented by a discrete-time TS fuzzy system with jumping parameters. The stochastic stabilizibility of the jump TS fuzzy system is derived and formulated in terms of linear matrix inequalities (LNIS)

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.117-123
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• 2003

Rotational machines such as optical disk drives, hard disk drives, and so on are subject to periodic disturbances caused by their mechanical characteristics. In the meanwhile, it is well known that repetitive control rejects periodic disturbance effectively. This paper presents a practical application of repetitive control to the track-following servo of an optical disk drive. The repetitive control system is composed of two repetitive controllers which compensate for periodic disturbances generated by track geometry and eccentric rotation of disk and a feedback controller stabilizing the feedback loop. A robust stability for all plant uncertainties is proved using linear matrix inequalities (LMIs). In the controller design, a weighting function is introduced for the feedback controller to ensure a minimum loop gain and a sufficient phase margin. The repetitive controllers and the feedback controller are designed by solving an optimization problem which can consider the robust stability condition and the system performance. The developed repetitive control system is implemented in the digital control system with a 16-bit fixed-point digital signal processor (DSP). Through simulation and experiment. The feasibility of the proposed repetitive control system is verified.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.4
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• pp.1-10
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• 2001

In this paper, we propose the stability analysis and design methodology for the discrete-time affine Type III fuzzy system via the convex optimization technique. First, the stability condition is derived under which the discrete-time affine Type III fuzzy system is quadratically stable in the large. Next, the derived condition is reformulated into the convex optimization problem called Linear Matrix Inequalities (LMI) and numerically addressed. Finally, the effectiveness and the feasibility of the proposed analysis and design methodology is highlighted via an example and its computer simulation result.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.321-324
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• 2003

This paper discusses a robust stochastic stabilization of uncertain Takagi-Sugeno (T-S) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretixzd T-S fuzzy system is represented by a uncertain discrete-time T-S fuzy system with jumping parameters. The robust stochastic stabilizibility of the uncertain jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs).

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.464-469
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• 2009

This paper discusses a robust observer-based output-feedback stabilization of an uncertain Takagi-Sugeno (T-S) fuzzy system in a network. In the networked control system, the input delay occurs inevitably and it is expressed by the Markovian stochastic process. To design robust sampled-data observer-based output-feedback controller, we discretize the T-S fuzzy system and represent as a jump system. Stochastic robust stabilization condition is formulated in terms of linear matrix inequalities.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.80-84
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• 2002

This paper proposes a decentralized control technique for 2-dimensional experimental helicopter systems. The decentralized control technique is especially suitable in large-scale control systems. We derive the stabilization condition for the interconnected Takagi-Sugeno (TS) fuzzy system using the rigorous tool-Lyapunov stability criterion and formulate the controller design condition in terms of linear matrix inequality (LMI). To demonstrate the feasibility of the proposed method, we include the experiment result as well as a computer simulation one, which strongly convinces us the applicability to the industry.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.793-800
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• 2001

This paper deals with a new design methodology for a switching-type fuzzy-model-based controller in continuous and discrete-time system. Takagi-Sugeno (TS) fuzzy model is employed to design the switching-type fuzzy-model-based controller. A switching-type fuzzy-model-based controller is constructed based on the spirit of “divide and conquer”. The global system which has several rules in divided into several subsystems and then, a solution is found at each subsystem. The global solution is determined by a conjunction of the solutions of each subsystem. The design conditions are formulated in terns of linear matrix inequalities (LMIs), which guarantee the stabilization of a given TS fuzzy system. Simulation examples are included for ensuring the proposed control method.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.293-299
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• 2003

This paper discusses a design of intelligent controller with time delay for Internet-based remote control. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The Takagi-Sugeno (T-S) fuzzy system with uncertain input delay is utilized to represent nonlinear plant. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The robust stochastic stabilizibility of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). An experimental results is provided to visualize the feasibility of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.298-303
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• 2004

This paper deals with a stochastic stabilization of observer-based output-feedback control Takagi-Sugeno (T-S) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The stochastic stabilizability of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). The usefulness of the proposed algorithm is also certificated by simulation of 2 degree of freedom helicopter model.