• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.199-204
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• 2002

This paper is concerned with H$_{\infty}$ controller design methods for descriptor systems with and without time-varying delays in state and control input. The sufficient condition for the existence of an H$_{\infty}$ controller and the controller design method are presented by linear matrix inequality (LMI), singular value decomposition, Schur complements, and changes of variables. Since the obtained sufficient condition can be changed to an LMI form by proper manipulations, all solutions including controller gain can be obtained at the same time. Moreover, it is shown that robust H$_{\infty}$ controller design problem for parameter uncertain descriptor systems with time-varying delays in state and control input can be solvable using the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.58-58
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• 2000

As many sensors and actuators are used in various automated systems, the application of network system to real-time distributed control is gaining acceptance in many industries. In order to take advantages of the network technique. however, network implementation should be carefully designed to satisfy real-time constraints and to consider network delays. This paper presents the implementation of feedback control system in Profibus-DP. Profibus-DP is a type of fieldbus protocols that are specifically designed to interconnect simple devices with fast I/O data exchange. As feedback control in profibus-DP is implemented, Network delays is found with influence of system performance. We analyze network delays in Profibus-DP into 3 reasons - dead time in Profibus interface, protocol delay, delay by asynchronization. In order to compensate the network delays, we introduce control algorithms with time delay concept. The results show that network delay can be compensated.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.1
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• pp.26-32
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• 2000

In this paper, we consider to robust controller design problem for the linear large scale systems with the uncertainties and the time-delays. The considered time-delays are that exist in the state and the input of the subsystems and the interconnected subsystems. And the considered uncertainties are two general types that exist in the system, input and interconnected matrices. Based on the linear matrix inequality(LMI) and Lyapunov theorem, we present sufficient conditions for the existence of a controller that guarantees the asymptotic stability of systems regardless of the uncertainties and the time-delays. Also, the controller can be easily obtained by checking the feasibility of the LMI's. Finally, we show the usefulness of our results by an example.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.976-986
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• 2014

In this paper, the problem of reliable control of linear systems with time-varying delays, randomly occurring disturbances, and actuator failures is investigated. It is assumed that actuator failures occur when disturbances affect to the systems. Firstly, by using a suitable Lyapunov-Krasovskii functional and some recent techniques such as Wirtinger-based integral inequality and reciprocally convex approach, stabilization criterion for nominal systems with time-varying delays is derived. Secondly, the proposed method is extended to the reliable $H_{\infty}$ controller design for linear dynamic systems with time-varying delays, randomly occurring disturbances, and actuator failures. Since nonlinear matrix inequalities (NLMIs) are involved in proposed results, the cone complementarity algorithm will be introduced. Finally, two numerical examples are included to show the effectiveness of the proposed criteria.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.181-186
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• 2009

In this paper, the stability analysis for uncertain dynamic systems with time-varying delays is considered. By constructing a new Lyapunov functional, a novel stability criterion is established in terms of linear matrix inequalities (LMIs). Two numerical examples are carried out to support the effectiveness of the proposed method.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.1051-1065
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• 2012

In this paper, the global stability and almost periodicity are investigated for generalized Hopfield neural networks with time-varying neutral delays. Some sufficient conditions are obtained for the existence and globally exponential stability of almost periodic solution by employing fixed point theorem and differential inequality techniques. The results of this paper are new and complement previously known results. Finally, an example is given to demonstrate the effectiveness of our results.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.209-221
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• 1994

Timers are commonly used in hardware design for time delays that are to be much longer than the system clock period. In this paper, we present a method by which we can synthesie a hardware containing timers that implement long time delays described in VHDL. Because, in general, timers require high hardware cost, they must be utilized as efficiently as possible. To solve this problem we define a graph model and propose an algorithm that uses the graph model to minimize number of timers. A preliminary experimental result show that the algorithm implements all required time delays using minimum number of timers.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.713-722
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• 2011

In the present paper, the problem of stability analysis for linear systems with interval time-varying delays is considered. By introducing a new Lyapunov-Krasovskii functional, new stability criteria are derived in terms of linear matrix inequalities (LMIs). Two numerical examples are given to show the superiority of the proposed method.

• Advances in aircraft and spacecraft science
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• v.9 no.4
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• pp.335-347
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• 2022

Airport operations are well-known as a bottleneck in the air traffic system, putting growing pressure on the world's busiest airports to schedule arrivals and departures as efficiently as possible. Effective planning and control are essential for increasing airport efficiency and reducing aircraft delays. Many algorithms for controlling the arrival/departure queuing area are handled, considering it as first in first out queues, where any available aircraft can take off regardless of its relative sequence with other aircraft. In the suggested system, this problem was compared to the problem of scheduling n tasks (plane takeoffs and landings) on a multiple machine (runways). The proposed technique decreases delays (via efficient runway allocation or allowing aircraft to be expedited to reach a scheduled time) to enhance runway capacity and decrease delays. The aircraft scheduling problem entails arranging aircraft on available runways and scheduling their landings and departures while considering any operational constraints. The topic of this work is the scheduling of aircraft landings and takeoffs on multiple runways. Each aircraft's takeoff and landing schedules have time windows, as well as minimum separation intervals between landings and takeoffs. We present and evaluate a variety of comprehensive concepts and solutions for scheduling aircraft arrival and departure times, intending to reduce delays relative to scheduled times. When compared to First Come First Serve scheduling algorithm, the suggested strategy is usually successful in reducing the average waiting time and average tardiness while optimizing runway use.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.534-540
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• 1996

This paper presents an Adaptive Time-Delay Recurrent Neural Network (ATRN) for learning and recognition of temporal correlations of temporal patterns. The ATRN employs adaptive time-delays and recurrent connections, which are inspired from neurobiology. In the ATRN, the adaptive time-delays make the ATRN choose the optimal values of time-delays for the temporal location of the important information in the input parrerns, and the recurrent connections enable the network to encode and integrate temporal information of sequences which have arbitrary interval time and arbitrary length of temporal context. The ATRN described in this paper, ATNN proposed by Lin, and TDNN introduced by Waibel were simulated and applied to the chaotic time series preditcion of Mackey-Glass delay-differential equation. The simulation results show that the normalized mean square error (NMSE) of ATRN is 0.0026, while the NMSE values of ATNN and TDNN are 0.014, 0.0117, respectively, and in temporal learning, employing recurrent links in the network is more effective than putting multiple time-delays into the neurons. The best performance is attained bythe ATRN. This ATRN will be sell applicable for temporally continuous domains, such as speech recognition, moving object recognition, motor control, and time-series prediction.