• Smart Structures and Systems
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• 제25권1호
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• pp.65-80
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• 2020

In order to protect a structure over its full life cycle, a novel tuned mass damper (TMD), the so-called semi-active eddy current pendulum tuned mass damper (SAEC-PTMD), which can retune its frequency and damping ratio in real-time, is proposed in this study. The structural instantaneous frequency is identified through a Hilbert-Huang transformation (HHT), and the SAEC-PTMD pendulum is adjusted through an HHT-based control algorithm. The eddy current damping parameters are discussed, and the relationship between effective damping coefficients and air gaps is fitted through a polynomial function. The semi-active eddy current damping can be adjusted in real-time by adjusting the air gap based on the linear-quadratic-Gaussian (LQG)-based control algorithm. To verify the vibration control effect of the SAEC-PTMD, an idealized linear primary structure equipped with an SAEC-PTMD excited by harmonic excitations and near-fault pulse-like earthquake excitations is proposed as one of the two case studies. Under strong earthquakes, structures may go into the nonlinear state, while the Bouc-Wen model has a wild application in simulating the hysteretic characteristic. Therefore, in the other case study, a nonlinear primary structure based on the Bouc-Wen model is proposed. An optimal passive TMD is used for comparison and the detuning effect, which results from the cumulative damage to primary structures, is considered. The maximum and root-mean-square (RMS) values of structural acceleration and displacement time history response, structural acceleration, and displacement response spectra are used as evaluation indices. Power analyses for one earthquake excitation are presented as an example to further study the energy dissipation effect of an SAECPTMD. The results indicate that an SAEC-PTMD performs better than an optimized passive TMD, both before and after damage occurs to the primary structure.

• 대한전기학회논문지:전력기술부문A
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• 제48권2호
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• pp.97-106
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• 1999

This paper proposes the structure and the algorithm of the Fuzzy-Neural Controller(FNNC) which is able to adapt itself to unknown plant and the change of circumstances at the Fuzzy Logic Controller(FLC) with the Neural Network. This Learning Fuzzy Logic Controller is made up of Fuzzy Logic controller in charge of a main role and Neural Network of an adaptation in variable circumstances. This construct optimal fuzzy controller applied to the 2-area load frequency control of power system, and then it would examine fitness about parameter variation of plant or variation of circumstances. And it proposes the optimal Scale factor method wsint three preformance functions( E, , U) of system dynamics of load frequency control with error back-propagation learning algorithm. Applying the controller to the model of load frequency control, it is shown that the FNNC method has better rapidity for load disturbance, reduces load frequency maximum deviation and tie line power flow deviation and minimizes reaching and settling time compared to the Optimal Fuzzy Logic Controller(OFLC) and the Optimal Control for optimzation of performance index in past control techniques.

• Journal of Power Electronics
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• 제14권5호
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• pp.1008-1027
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• 2014

An electric scooter with a V-belt continuously variable transmission (CVT) driven by a permanent magnet synchronous motor (PMSM) has a lot of nonlinear and time-varying characteristics, and accurate dynamic models are difficult to establish for linear controller designs. A PMSM servo-drive electric scooter controlled by a novel hybrid modified recurrent Legendre neural network (NN) control system is proposed to solve difficulties of linear controllers under the occurrence of nonlinear load disturbances and parameters variations. Firstly, the system structure of a V-belt CVT driven electric scooter using a PMSM servo drive is established. Secondly, the novel hybrid modified recurrent Legendre NN control system, which consists of an inspector control, a modified recurrent Legendre NN control with an adaptation law, and a recouped control with an estimation law, is proposed to improve its performance. Moreover, the on-line parameter tuning method of the modified recurrent Legendre NN is derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, two optimal learning rates for the modified recurrent Legendre NN are derived to speed up the parameter convergence. Finally, comparative studies are carried out to show the effectiveness of the proposed control scheme through experimental results.

• Earthquakes and Structures
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• 제1권1호
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• pp.43-67
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• 2010

A gradient-based evolutionary optimization methodology is presented for finding the optimal design of both the added dampers and their supporting members to minimize an objective function of a linear multi-storey structure subjected to the critical ground acceleration. The objective function is taken as the sum of the stochastic interstorey drifts. A frequency-dependent viscoelastic damper and the supporting member are treated as a vibration control device. Due to the added stiffness by the supplemental viscoelastic damper, the variable critical excitation needs to be updated simultaneously within the evolutionary phase of the optimal damper placement. Two different models of the entire damper unit are investigated. The first model is a detailed model referred to as "the 3N model" where the relative displacement in each component (i.e., the spring and the dashpot) of the damper unit is defined. The second model is a simpler model referred to as "the N model" where the entire damper unit is converted into an equivalent frequency-dependent Kelvin-Voigt model. Numerical analyses for 3 and 10-storey building models are conducted to investigate the characters of the optimal design using these models and to examine the validity of the proposed technique.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.703-706
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• 1999

In this paper, robust vibration control of a one-link flexible robot arm based on variable structure system is discussed. We derive dynamic equations of it using a Lagragian assumed modes method based on Bernoulli-Euler beam theory. The optimal sliding surface is designed and the problem of chattering is also solved by the adoptation of a continuous control law within a small neighborhood of the switching hyperplane.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.495-495
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• 2000

The Stewart platform manipulator is a closed-kinematis chain robot manipulator that is capable of providing high st겨ctural rigidity and positional accuracy. However, this is a complex structure, so controllability of the system is not so good. In this paper, it introduces a new robust motion control algorithm using partial state feedback for a class of nonlinear systems in the presence of modelling uncertainties and external disturbances. The major contribution of this work introduces the development and design of robust observer for the slate and the perturbation w.hich is integrated into a variable structure controller(VSC) structure. The combination of controller/observer gives rise to the robust routine called sliding mode control with sliding perturbation observer(SMCSPO). The optimal gains of SMCSPO are easily obtained by genetic algorithm. Simulation and experiment are presented in order to apply to the stewart platform manipulator. There results show highly' accuracy and performance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3013-3015
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions, At the same time, the fine tunings of their gain parameters are also troublesome, Thus, in this paper, an Evolving Neural Network ControlleY(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm (RVEGA) was presented for stabilization of an IP system with nonlinearity, This proposed ENNC was described by a simple genetic chromosome. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.335-337
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• 1993

An integral-augmented variable structure system is suggested for the control of an uncertain SISO systems without the reaching phase problems. The integral-augmented sliding surface is defined in order to remove the reaching phase, then it is designed using the optimal technique. The example results show the effectiveness of the algorithm.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권3호
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• pp.157-163
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• 2000

In this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algoithm(RVEGA) was presented for stabilization of an Inverter Pendulum(IP) system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the determinations of input or output neuron, the deleted neuron and the activation functions types are given according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. Through the simulations, we showed that the finally acquired optimal ENNC was successfully applied to the stabilization control of an IP system.

• 대한기계학회논문집
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• 제18권8호
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• pp.1985-1996
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• 1994

A new design method of sliding hyperplanes is proposed in the synthesis of a variable structure controller for robust tracking of general nonlinear multi-input-output(MIMO) uncertain systems of relative degree higher than two. Input/ output(I/O) linearzation is firstly undertaken by employing the concept of relative degree and minimum phase followed by the construction of sliding mode controllers. Sliding hyperplanes are then derived from the inherent properties of companion matrix and ideal sliding mode characterized in I/O linearized system. Subsequently, the gradient magnitudes of the sling hyperplanes are determined in an optimal manner by considering a quadratic performance index to be evaluated at two phases; a reaching phase and a sliding phase. The proposed design methodology is relatively straightforward and systematic compared with conventional strategies such as geometric approach or pole assignment technique. A nonlinear governor and exciter control problem for a power system is adopted herein in order to demonstrate the design efficiency and also favorable and robust control performances.