• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.520-525
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• 2003

This paper concerns a design methodology of observer-based output-feedback digital controller for Takagi-Sugeno(TS) fuzzy systems using intelligent digital redesign (IDR). The term of IDR involves converting an analog fuzzy-mode-based controller into an equivalent digital one in the sense of state-matching. The considered IDR problem is viewed as convex minimization problems of the norm distances between linear operators to be matched. The stability condition is easily embedded and the separations principle is explicitly shown.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.2
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• pp.68-73
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• 2000

This paper addresses the analysis and design of fuzzy control systems for a class of complex nonlinear systems. Firstly, the nonlinear system is represented by Takagi-Sugeno(TS) fuzzy model and the global controller is constructed by compensating each linear model in the rule of TS fuzzy model. The design of conventional TS fuzzy-model-based controller is composed of two processes. One is to determine the static state feedback gain of each local model and the other is to validate the stability of the designed fuzzy controller. In this paper, we propose an alternative methods for the design of TS fuzzy-model-based controller. The design scheme is based on the extension of conventional optimal control theory to the design of TS fuzzy-model-based controller. By using the proposed method, the design and stability analysis of the TS fuzzy model-based controller is reduced to the problem of finding the solution of a set of algebraic Riccati equations. And we use the recently developed interior point method to find the solution of AREs, where AREs are recast as the LMI formulation. A numerical simulation example is given to show the effectiveness and feasibiltiy of the proposed fuzzy controller design method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.12
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• pp.1994-2000
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• 1993

A new lattice structure using decision feedback and augmented prediction for estimating and suppressing the narrowband interference is presented. The performance of the proposed interference canceller is compared to the conventional interference cancellation filter. The reference signal of the interference canceller is formed by using the chip decisions, which is correlated with the narrowband interference components of the received signal. The decision feedback technique reduce the distortion of the desired signal which is introduced by the interference canceller through the use of feedback chip decisions. And by linear prediction of the error signal, the residual interference component of can be eliminated, Using this unconteminated error signal to update the adaptive filter coefficients, the performance of the rejection can be improved. In the simulation, it is assumed that the processing gains are 7 and 15, signal to interference ratio is -10[dB], and 5% interference band. The results show that the BER performance of the proposed filter structure is improved by 1~3dB.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.2
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• pp.153-160
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• 1999

Dual-stage servo system for super-high density HDD has the chances of being composed of the coarse actuator(VCM) for track-seeking control and the fine actuator(microactuator) for-following control in near future. This paper presents the concept design of dual-stage servo system and the track-following control using an electrostatic microactuator for super-high density HDD. The electrostatic microactuator is designed and fabricated by MEMS(micro-electro-mechanical system) process. Both the nonlinear plant(voltage/displacement-to-electrostatic force) and the linear plant(electrostatic force-to-displacement) of the microactuator are established. Inverse function of the nonlinear plant is employed for a feedforward nonlinear compensator design. And feedforward control effect of this compensator is shown by time-domain experiments. A track-following feedback controller is designed using the feedback nonlinear compensator which is derived from the feedforward nonlinear compensator. The track-following control experiment is done to show the control efficiency of the proposed control system. And, excellent track-following control performance(2.21kHz servo-bandwidth, 7.51dB gain margin, $50.98^{\circ}$phase margin) is achieved by the proposed control system.

• Earthquakes and Structures
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• v.12 no.4
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• pp.425-436
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• 2017

Vibration control using a tuned mass damper (TMD) is an effective technique that has been verified using analytical methods and experiments. It has been applied in mechanical, automotive, and structural applications. However, the damping of a TMD cannot be adjusted in real time. An excessive mass damper stroke may be introduced when the mass damper is subjected to a seismic excitation whose frequency content is within its operation range. The semi-active tuned mass damper (SATMD) has been proposed to solve this problem. The parameters of an SATMD can be adjusted in real time based on the measured structural responses and an appropriate control law. In this study, a stiffness-controllable TMD, called a leverage-type stiffness-controllable mass damper (LSCMD), is proposed and fabricated to verify its feasibility. The LSCMD contains a simple leverage mechanism and its stiffness can be altered by adjusting the pivot position. To determine the pivot position of the LSCMD in real time, a discrete-time direct output-feedback active control law that considers delay time is implemented. Moreover, an identification test for the transfer function of the pivot driving and control systems is proposed. The identification results demonstrate the target displacement can be achieved by the pivot displacement in 0-2 Hz range and the control delay time is about 0.1 s. A shaking-table test has been conducted to verify the theory and feasibility of the LSCMD. The comparisons of experimental and theoretical results of the LSCMD system show good consistency. It is shown that dynamic behavior of the LSCMD can be simulated correctly by the theoretical model and that the stiffness can be properly adjusted by the pivot position. Comparisons of experimental results of the LSCMD and passive TMD show the LSCMD with less demand on the mass damper stroke than that for the passive TMD.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.6
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• pp.135-146
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• 2013

This paper presents a feedforward control algorithm for the EGR and VGT systems of passenger car diesel engines. The air-to-fuel ratio and boost pressure are selected as control indicators and the positions of EGR valve and VGT vane are used as control inputs of the EGR and VGT controller. In order to compensate the non-linearity and coupled dynamics of the EGR and VGT systems, we have proposed a non-linear model-based feedforward control algorithm which is obtained from static model inversion approach. It is observed that the average modeling errors of the feedforward algorithm is about 2% using stationary engine experiment data of 225 operating conditions. Using a feedback controller including proportional-integral, the modeling error is compensated. Furthermore, it is validated that the proposed feedforward algorithm generates physically acceptable trajectories of the actuator and successfully tracks the desired values through engine experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.337-342
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• 2009

This paper concerns delay-range-dependent robust stability and stabilization for time-delay nonliner system via T-S fuzzy model approach. The time delay is assumed to be a time-varying continuous function belonging to a given range. On the basis of a novel Lyapunov-Krasovskii functional, which includes the information of the range, delay-range-dependent stability criteria are established in terms of linear matrix inequality. It is shown that the new criteria can provide less conservative results than some existing ones. Moreover, the stability criteria are also used to design the stabilizing state-feedback controllers. Numerical examples are given to demonstrate the applicability of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.631-634
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• 2004

In this paper, the Bayesian recurrent neural network (BRNN) is proposed to predict time series data. Among the various traditional prediction methodologies, a neural network method is considered to be more effective in case of non-linear and non-stationary time series data. A neural network predictor requests proper learning strategy to adjust the network weights, and one need to prepare for non-linear and non-stationary evolution of network weights. The Bayesian neural network in this paper estimates not the single set of weights but the probability distributions of weights. In other words, we sets the weight vector as a state vector of state space method, and estimates its probability distributions in accordance with the Bayesian inference. This approach makes it possible to obtain more exact estimation of the weights. Moreover, in the aspect of network architecture, it is known that the recurrent feedback structure is superior to the feedforward structure for the problem of time series prediction. Therefore, the recurrent network with Bayesian inference, what we call BRNN, is expected to show higher performance than the normal neural network. To verify the performance of the proposed method, the time series data are numerically generated and a neural network predictor is applied on it. As a result, BRNN is proved to show better prediction result than common feedforward Bayesian neural network.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.