• Earthquakes and Structures
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• 제15권3호
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• pp.227-241
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• 2018

The present paper deals with the optimum performance of the passive hybrid control system for the benchmark highway bridge under the six earthquakes ground motion. The investigation is carried out on a simplified finite element model of the 91/5 highway overcrossing located in Southern California. A viscous fluid damper (known as VFD) or non-linear fluid viscous spring damper has been used as a passive supplement device associated with polynomial friction pendulum isolator (known as PFPI) to form a passive hybrid control system. A parametric study is considered to find out the optimum parameters of the PFPI system for the optimal response of the bridge. The effect of the velocity exponent of the VFD and non-linear FV spring damper on the response of the bridge is carried out by considering different values of velocity exponent. Further, the influences of damping coefficient and vibration period of the dampers are also examined on the response of the bridge. To study the effectiveness of the passive hybrid system on the response of the isolated bridge, it is compared with the corresponding PFPI isolated bridges. The investigation showed that passive supplement damper such as VFD or non-linear FV spring damper associated with PFPI system is significantly reducing the seismic response of the benchmark highway bridge. Further, it is also observed that non-linear FV spring damper hybrid system is a more promising strategy in reducing the response of the bridge compared to the VFD associated hybrid system.

• International Journal of Aeronautical and Space Sciences
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• 제14권3호
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• pp.256-263
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• 2013

The saturation of the actuator impairs the response performance of the near space interceptor control system. A control system based on the properties of linear tracking system is designed for this problem. The properties are that the maximum value of the pseudo-Lyapunov function of the linear tracking control system do not present at the initial state but at the steady state, based on which the bounded stability problem is converted into linear tracking problem. The pseudo-Lyapunov function of the linear tracking system contain the input variables; the amplitude and frequency of the input variables affect the stability of the nonlinear control system. Designate expected closed-loop poles area for different input commands and obtain a controller which is function of input variables. The coupling between variables and linear matrices make the control system design problem non-convex. The non-convex problem is converted into a convex LMI according to the Shur complement lemma and iterative algorithm. Finally the simulation shows that the designed optimal control system is quick and accurate; the rationality of the presented design techniques is validated.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권1호
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• pp.10-15
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• 2004

We present a state-space approach to make non-square linear systems strictly passive by using an input-dimensional parallel feedforward compensator. A necessary and sufficient condition for the existence of the parallel feedforward compensator is given by the static output feedback formulation, which enables to utilize linear matrix inequality. By modifying the structure of the compensator the additional technical assumption in the previous result [1] is removed. The effectiveness of the proposed method is illustrated by some numerical examples which can be stabilized by the proportional-derivative (PD) and proportional-derivative-integral (PID) control laws. The proposed control scheme can successfully replace the measurements of derivative terms in the control laws.

• 제어로봇시스템학회논문지
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• 제10권2호
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• pp.185-191
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• 2004

Partial least squares(PLS) is one of multiplicate statistical process methods and has been developed in various algorithms with the characteristics of principal component analysis, dimensionality reduction, and analysis of the relationship between input variables and output variables. But it has been limited somewhat by their dependency on linear mathematics. The algorithm is proposed to classify for the non-linear data using PLS and the residual compensator(RC) based on radial basis function network (RBFN). It compensates for the error of the non-linear data using the RC based on RBFN. The experimental result is given to verify its efficiency compared with those of previous works.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.215-218
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• 1997

A dynamic back-propagation neural network is addressed for adaptive neural control system to approximate non-linear control system rather than static networks. It has the capability to represent the approximation of nonlinear system without mathematical analysis and to carry out the on-line learning algorithm for real time application. The simulated results show fast tracking capability and adaptive response by using dynamic back-propagation neurons.

• Journal of applied mathematics & informatics
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• 제18권1_2호
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• pp.1-23
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• 2005

The decentralized static output feedback design problem is considered. A constrained trust region method is developed that solves this optimal control problem when a complete set of state variables is not available. The considered problem is interpreted as a non-linear (non-convex) constrained matrix optimization problem. Then, a decentralized constrained trust region method is developed for this problem class exploiting the diagonal structure of the problem and using inexact computations. Finally, numerical results are given for the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권2호
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• pp.151-157
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• 2008

A non-fragile guaranteed cost control (GCC) problem is presented for a class of discrete time-delay nonlinear systems described by Takagi-Sugeno (T-S) fuzzy model. The systems are assumed to have norm-bounded time-varying uncertainties in the matrices of state, delayed state and control gains. Sufficient conditions are first obtained which guarantee that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound. Then the design method of the non-fragile guaranteed cost controller is formulated in terms of the linear matrix inequality (LMI) approach. A numerical example is given to illustrate the effectiveness of the proposed design method.

• 제어로봇시스템학회논문지
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• 제22권7호
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• pp.496-501
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• 2016

This paper presents a design method of non-parallel distributed compensation (non-PDC) static output feedback controller for continuous- and discrete-time T-S fuzzy systems. The existence condition of static output feedback control law is represented in terms of linear matrix inequalities (LMIs). The proposed sufficient stabilizing condition does not need any transformation matrices and equality constraints and is less conservative than the previous result of [21].

• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• 전기의세계
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• 제20권4호
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• pp.12-16
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• 1971

The electrical detector and computer systems for traffic flow and speed measurement are demonstrated in this paper. For the best traffic control optimization, linear and non-linear equations in the transition state are dealing with the perturbation of the linear car-following. In the conclusions, we construct a realizable system for the central automatic traffic control with a computer. Furthermore, fixed periodic switching system by manual with the automatic traffic control system is recommended for emergency perturbation.