• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.308-315
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• 2016

This paper addresses a formation control problem for a phugoid model-based multi-agent system in discrete time by using a Takagi-Sugeno (T-S) fuzzy model-based controller design technique. The concerned discrete-time model is obtained by Euler's method. A T-S fuzzy model is constructed through a feedback linearization. A fuzzy controller is then designed to stabilize the T-S fuzzy model. Design condition is presented in the linear matrix inequality format.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.121-127
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• 1999

In this paper, we present robust reliable H$\infty$ controller design methods of continuous and discrete uncertain time delay systems using LMI (linear matrix inequality) technique, respectively. Also the existence conditions of state feedback control are proposed . Using some changes of variables and Schur complements, the obtained sufficient conditions are transformed into an LMI form. The closed loop system by the obtained controller is quadratically stable with H$\infty$ norm bound for all admissible uncertainties, time delay, and all actuator failures occurred within the prespecified set. We show the validity of the proposed method through numerical example.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1056-1059
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• 1996

In this study, a new OSA controller is proposed for controlling discrete-time chaotic systems efficiently. A new OSA controller uses NARMAX models, and its feedback gain is designed on the basis of conventional linear control theory. In order to evaluate the performance of a new OSA controller, a new OSA controller is applied to Henon system which is a discrete-time chaotic system, and then the control performance of a new OSA controller are compared with that of the previous model-base controller through computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.729-733
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• 1988

In this paper, a new procedure for selecting weighting matrices in linear discrete time quadratic optimal control problems (LQ-problem) is proposed. In LQ problems, the quadratic weighting matrices are usually decided on trial and error in order to get a good response. But using the proposed method, the quadratic weights are decided in such a way that all poles of the closed loop system are located in a desired area for good responses as well as for stability and values of the quadratic cost functional are kept less then a specified value. The closed loop systems constructed by this method have merits of LQ problems as well as those of pole assignment problems. Taking into consideration that little is known about the relationship among the quadratic weights, the poles and the values of cost functional, this procedure is also interesting from the theoretical point of view.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.645-652
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• 2006

In this paper a new type of filter, called the $H_2/H_{\infty}$ FIR filter, is proposed for discrete-time state space signal models. The proposed filter requires linearity, unbiased property, FIR structure, and independence of the initial state information in addition to the performance criteria in both $H_2$ and $H_{infty}$ sense. It is shown that $H_2,\;H_{\infty}$, and $H_2/H_{\infty}$ FIR filter design problems can be converted into convex programming problems via linear matrix inequalities (LMIs) with a linear equality constraint. Simulation studies illustrate that the proposed FIR filter is more robust against temporary uncertainties and has faster convergence than the conventional IIR filters.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.625-631
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• 2011

This paper presents a discrete-time output feedback consensus algorithm for Multi-Agent Systems (MAS). Under the assumption that an agent is aware of the relative state information about its neighbors, a state feedback consensus algorithm is designed based on Linear Matrix Inequality (LMI) method. In general, however, it is possible to obtain its relative output information rather than the relative state information. To reconcile this problem, an Unknown Input Observer (UIO) is employed in this paper. To this end, first it is shown that the relative state information can be estimated using the UIO and the measured relative output information. Then a certainty-equivalence type output feedback consensus algorithm is proposed by combining the LMI-based state feedback consensus algorithm with the UIO. Finally, simulation results are given to illustrate that the proposed method successfully achieves the state consensus.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.3
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• pp.89-96
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• 1985

This paper presents a decentralized adaptive scheme to stabilize a class of large-scale discrete-time linear systems subject to system parameter uncertainties. The scheme combines an adaptive nonlinear feedback control for compensating some effects by unknown system parameters and the exact model-based linear feedback control for overriding the unfavorable effects by interconnections. A condition of stability is derived, under which the overall adaptive system is assured to be globally stable. Also, a numerical example is provided to illustrate the feasibility of the scheme.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.296-298
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• 1993

In this paper, a new design procedure is proposed for constructing the observer for linear discrete-time systems with unknown inputs. An existence condition for the suggested observer is also presented. The observer design procedure does not use any transformation technique, augmentation technique and has a clear physical meaning, so it is easy to understand and to design the observer. It directly estimates the unknown inputs from that outputs only, so it is different from other pre-works in which the reconstruction of the unknown inputs arc performed with the additional output derivatives.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.489-494
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• 2013

This paper tackles the problem of designing a dynamic output-feedback control for linear discrete-time norm-bounded uncertain systems with input saturation. By employing a LPV (Linear Parameter Varying) instead of LTI (Linear Time-Invariant) control, the useful information on interpolation parameters appearing in the procedure of representing saturation nonlinearity as a convex polytope is additionally applied in the control design procedure. By solving the addressed problem that can be recast into a convex optimization problem characterized by LMIs (Linear Matrix Inequalities) with one prescribed scalar, the vertices of convex set containing an LPV output-feedback control gain and the associated maximal invariant set of initial states are simultaneously obtained.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.372-378
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• 2007

This paper discusses Robust $H{\infty}$ control problems for networked control systems (NCSs) with time delays and subject to norm-bounded parameter uncertainties. Based on a new discrete-time model, two approaches of robust controller design are proposed. A numerical example and experimental verification with an NCS test bed are given to illustrate the feasibility and effectiveness of proposed design methodologies.