• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.506-515
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• 2006

This paper studies an intelligent digital control for nonlinear systems with multirate sampling. It is worth noting that the multirate control design is addressed for a given nonlinear system represented by Takagi-Sugeno (T-S) fuzzy models. The main features of the proposed method are that i) it is provided that the sufficient conditions for stabilization of the discrete-time T-S fuzzy system in the sense of Lyapunov stability criterion, which is can be formulated in the linear matrix inequalities (LMIs); and ii) the stability properties of the trivial solution of the digital control system can be deduced from that of the solution of its discretized versions. An example is provided for showing the feasibility of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.1-5
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• 2002

A common way to design a digital control system is to design an analog controller first and discretize it for digital implemention. In this paper, optimal digital controller design is studied within the framework of sampled -data control theory. In particular, multirate discretization of analog controller is considered using an Η$_2$optimality criterion. Solutions are obtained via multirate H2 optimization with a causality constraint due to the multirate structure. In design example, the comparison of the proposed methods is made with the conventional discretization methods, and demonstrate the superiority of the multirate design method.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.12
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• pp.1004-1013
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• 2002

A multirate state feedback control (MRSFC) method is proposed for systems sensitive to disturbance and noise based on the multirate estimator design using current estimator. MRSFC updates the controller output slower than the measurement sampling fiequency of system output by a lifting factor $R=T_c/T_s$ The closed-loop MRSFC system is less sensitive to disturbance and noise due to filtering effect than the conventional single-rate control system The multirate estimator gain can be obtained by solving a conventional pole placement problem such that MRSFC has the same spectrum of eigenvalues in the s-plane as the single-rate control. We applied the proposed multirate state feedback controller to a galvanometer servo system Simulation and experimental results show that settling and tracking performances are improved compared with a conventional single-rate pole placement control (PPC).

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.190-190
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• 2000

This paper presents a multirate state feedback control (MRSFC) method for systems sensitive to disturbance and noise based on the multirate estimator design using the current estimator. MRSFC updates the controller output slower than the measurement sampling frequency of system output by a lifting factor R=T$\sub$c//T$\sub$s/. The closed-loop MRSFC system is less sensitive to disturbance and noise due to filtering effect than the conventional single-rate control system. The multirate estimator gain is obtained from solving a conventional pole placement problem such that MRSFC has the same spectrum of eigenvalues in the s-plane as the single-rate control. We applied the proposed multirate state feedback controller to a galvanometer servo system. Simulation and experimental results show that settling and tracking performances are improved compared with a conventional single-rate pole placement control (PPC).

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.54-59
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• 2006

The smart space is composed of the wire and/or wireless network, multi-sensor-based environment, and many various controllers. For the smart space, this paper presents a new design method of multirate digital decentralized controller using the intelligent digital redesign technique. In specific, the proposed method is based on the delta-operator and the multirate sampling and takes the form of the LMIs. To shows the feasibility of the suggested method, the computer simulations for Heating, ventilating, and ai. conditioning (HVAC) system are provided.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.708-710
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• 2004

This paper studies a multirate sampled-data control for LTI systems by using the digital redesign (DR) method. In this note, to well tackle the problem associated with both the state matching and the stabilization, our nobel strategy is to minimize the linear quadratic cost function. The main features of the proposed method are that i) the delta-operator-based descretization method is applied to improve the state-matching performance in the fast sampling limit and/or the large input multiplicity; ii) the proposed multirate control scheme can improve the state-matching performance in the long sampling limit; iii) some sufficient conditions that guarantee the stability of the closed-loop discrete-time system and provide a guarantee cost for the cost function can be formulated in the LMIs format; and iv) an optimal sampled-data controller in the sense of minimizing the upper bound of the cost function is also given by means of an LMI optimization procedure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.271-274
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• 2001

In this paper, optimal digital design is studied within the framework of sampled-data control theory. In particular, multirate discretization of analog controller is considered using an H$_2$optimality criterion. Solutions are obtained via multirate H$_2$optimization with a causality constraint due to the multirate structure. In design example, the comparison of the proposed methods is made with the conventional discretization methods, and demonstrate the superiority of the multirate design method.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.765-770
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• 2005

This paper presents a new intelligent digital redesign (IDR) method via the compensated bilinear transformation to design the digital controller such that the digital fuzzy system is equivalent to the analog fuzzy system in the sense of the state-matching. This paper especially consider a multirate control scheme with a predictive feature, where the digital control input is held constant N times between the sampling points. More precisely, the multirate control scheme is proposed that utilizes a numerical integration scheme to approximately predict the current state from the state measured at the sampling points, the delayed measurements. For this system, the IDR conditions incorporated with stabilizability in the format of the linear matrix inequalities (LMIs) are derived. The superiority of the proposed technique is convincingly visualized through a numerical example.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.47-51
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• 2003

Due to the asymptotic property, deadbeat control which is well used in digital control system can not be applied to the continuous time system. But recently by use of the finite Laplace Transform to transfer function and establishment of some settling conditions, CDBC(Continuous time Deadbeat Control) is studied. For CDBC design, transfer function is constituted with delay elements and then order and interpolation conditions are derived. In other way, digital deadbeat controller is implemented and it's output is changed to continuous type by smoothing elements. In this paper multirate sampling is used and so inner controller is sampled faster than output feedback loop. And End order smoothing elements is placed to the output of digital deadbeat controller. By the multirate sampling overall output response is improved. The controller is impleneted as a serial integral compensator in the forward path and a local feedback compensator introduced into the outpute feedback loop. Matlab Simulink is used for simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.91-94
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• 2005

This paper presents a new linear- matrix- inequality- basedintelligent digital redesign (LMI-based IDR) technique to match he states of the analog and the digital control systems at the intersampling instants as well as the sampling ones. The main features of the proposed technique are: 1) the multirate control is employed, and the control input is changed N times during one sampling period; 2) The proposed IDR technique is based on the compensated bilinear transformation.