• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.76.5-76
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• 2002

In this paper, we provide a Nash solution to predictive control problem for nonminimum phase singular nonlinear systems. Until now, there is no result on predictive control problem for this class of nonlinear systems. Chen's recent work considered predictive control problem for a class of nonlinear systems with ill-defined relative degree. Since his work is not a result considered in the feedback linearization framework, there is no a result on singular probem in his paper. In contrast to the existing predictive control result, our work considers two main obstacles (singularity and nonminimum phase) in the feedback linearization framework. For a generally formu...

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.42-49
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• 2000

This paper presents the application of a FARMA controller to stabilization of nonlinear Two-Generator Five-Bus power Systems. The control rules and the membership functions of the FARMA controller are generated automatically without using any plant model high complexity and severe nonlinearity of power systems are introduced and two-Machine Five -Bus Power system stabilization problem is formulated. The simulation results demonstrate the effectiveness and application possibility of the FARMA controller to the control problem of high order and nonlinear plants.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.915-927
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• 2008

Networked control systems(NCSs) have gained increasing attention in recent years due to their advantages and potential applications. The network Quality-of-Service(QoS) in NCSs always fluctuates due to changes of the traffic load and available network resources. To handle the network QoS variations problem, this paper presents an intelligent scheduling control method for NCSs, where the sampling period and the control parameters are simultaneously scheduled to compensate the effect of QoS variation on NCSs performance. For NCSs with network-induced delays and packet dropouts, a discrete-time switch model is proposed. By defining a sampling-period-dependent Lyapunov function and a common quadratic Lyapunov function, the stability conditions are derived for NCSs in terms of linear matrix inequalities(LMIs). Based on the obtained stability conditions, the corresponding controller design problem is solved and the performance optimization problem is also investigated. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.106-108
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• 1997

Many new office buildings are being built as intelligent buildings equipped with building automation(HA) systems, office automation(OA) systems, and telecommunication(TC) systems in order to provide pleasant building environment and the ease of maintenance and facility management. Building control systems which are employed in intelligent buildings require varieties of advanced control systems and network systems for efficient integrated management. Design and installation of these types of advanced building control systems take a lot of efforts and also they are costly. In order to design these systems, it is necessary for the designers to have the integrated simulator including proper network system simulation. In this paper, the integrated simulator that consist of HVAC system, lighting system, elevator system, parking system based on the network system is presented. For the development of integrated simulator, AHENA which is the general-purpose software tool for a simulation with reinforced GUI is used.

• Smart Structures and Systems
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• v.16 no.6
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• pp.1147-1167
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• 2015

Wireless smart sensors, which have become popular for monitoring applications, are an attractive option for implementing structural control systems, due to their onboard sensing, processing, and communication capabilities. However, wireless smart sensors pose inherent challenges for control, including delays from communication, acquisition hardware, and processing time. Previous research in wireless control, which focused on semi-active systems, has found that sampling rate along with time delays can significantly impact control performance. However, because semi-active systems are guaranteed stable, these issues are typically neglected in the control design. This work achieves active control with smart sensors in an experimental setting. Because active systems are not inherently stable, all the elements of the control loop must be addressed, including data acquisition hardware, processing performance, and control design at slow sampling rates. The sensing hardware is shown to have a significant impact on the control design and performance. Ultimately, the smart sensor active control system achieves comparable performance to the traditional tethered system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.351-351
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• 2000

Since the heat exchange system, such as the boiler of power plant, gas turbine, and radiator require an application of intelligent control system for a high rate heat efficiency and the efficiency of these systems is depended on the control methods it is important for operator to understand control system of these systems and intelligent control technologies. In order to properly apply control equipment and intelligent technology to these process control systems, it is necessary to understand fuzzy, neural network, genetics, and immune as well as the basic aspects and operation principle of the process that relate control, interrelationships of the process characteristics, and the dynamics that are involved. Generally, since PID controllers are used in these systems it is difficult far engineer to understand both the complex dynamics and the intelligent control method. In this paper, we design an effective experimental system for the intelligent control education and analyze its characteristics through experimental system and each intelligent method to study how they can learn intelligent control system by experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.929-938
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• 2009

This paper presents a novel control methodology for communication network based nonlinear systems with time delay nature. We construct a nominal nonlinear control law for representing a linear model and a reset control system which is aimed for corrective control strategy to compensate system error due to uncertain time delay through wireless communication network. Next, online neural control approach is proposed for overcoming nonstationary statistical nature in the network topology. Additionally, DBN (Dynamic Bayesian Network) technique is accomplished for modeling of its dynamics in terms of casuality, which is then utilized for estimating prediction of system output. We evaluate superiority and reliability of the proposed control approach through numerical simulation example in which a nonlinear inverted pendulum model is employed as a networked control system.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.182-188
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• 2004

This paper presents a design method of delay-dependent control for T-S fuzzy systems with time delays. Based on parallel distributed compensation (PDC) and a descriptor model transformation of the system, a delay-dependent control is utilized. An appropriate Lyapunov-Krasovskii functional is chosen for delay-dependent stability analysis. A sufficient condition for delay-dependent control is represented in terms of linear matrix inequalities (LMIs).

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.416-421
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• 1994

Electric Power system is a large scale nonlinear control one. Therefore, nonlinear control is desirable for the stabilizing, and it is thought that to establish an analytical method for optimal control inputs of AVR(automatic voltage regulator) and GOV(governor) is an important subject. In this paper, as a simple case, one-machine infinite-bus electric power model system with GOV is treated under the three kinds of control inputs; (i) fuzzy control input, (ii) linear control input and (iii) no control input. Next, the stability for each case is analyzed, and the three-dimensional stability regions and control responses are evaluated and compared. Finally, it is concluded that the linear control input does not necessarily give a good region and response, and the fuzzy one is better than others.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.756-762
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• 2006

Shape Memory Alloy(SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.