• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.318-323
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• 2005

In this paper, we propose a systematic method of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear system. A parallel distributed compensation (PDC) technique is then used to design a fuzzy model based controller for both stabilization and tracking. Finally, the designed continuous-time controller is converted to an equivalent discrete-time controller by using an intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy model based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, the single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.667-672
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• 2003

In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may also contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear systems. An extended parallel distributed compensation(EPDC) technique is then used to design a fuzzy-model-based controller for both stabilization and tracking. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using an integrated intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, The single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.519-522
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• 2005

Decentralized Dynamic Surface Control(DDSC) for a class of nonlinear system interconnected via sensor network is presented in this paper. While a centralized design approach of DSC was developed in [1], the decentralized approach to deal with complex large-scale systems is proposed under the assumption that interconnected functions among subsystems are known via sensor network. As shown in [2], the separation principle for DDSC will allow us to design an estimation filter independently. Furthermore, the theoretical results are used to design and simulate an active vibration isolator under the assumption that many embedded sensors are distributed and communicate each other via wireless communication.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.653-662
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• 1989

Cerebellar Model Arithmetic Controller (CMAC) has been introduced as an adaptive control function generator. CMAC computes control functions referring to a distributed memory table storing functional values rather than by solving equations analytically or numerically. CMAC has a unique mapping structure as a coarse coding and supervisory delta-rule learning property. In this paper, learning aspects and a convergence of the CMAC were investigated. The efficient training algorithms were developed to overcome the limitations caused by the conventional maximum error correction training and to eliminate the accumulated learning error caused by a sequential node training. A nonlinear function generator and a motion generator for a two d.o.f. manipulator were simulated. The efficiency of the various learning algorithms was demonstrated through the cpu time used and the convergence of the rms and maximum errors accumulated during a learning process. A generalization property and a learning effect due to the various gains were simulated. A uniform quantizing method was applied to cope with various ranges of input variables efficiently.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.834-844
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• 2012

Nonlinear electronic loads draw harmonic currents from the power grids that can cause energy loss, miss-operation of power equipment, and other serious problems in the power grids. This paper proposes a harmonic compensation method using multiple distributed resources (DRs) such as small distributed generators (DGs) and battery energy storage systems (BESSs) that are integrated to the power grids through power inverters. For harmonic compensation, DRs should inject additional apparent power to the grids so that certain DRs, especially operated in proximity to their rated power, may possibly reach their maximum current limits. Therefore, intelligent coordination methods of multiple DRs are required for efficient harmonic current compensation considering the power margins of DRs, energy cost, and the battery state-of-charge. The proposed method is based on fuzzy multi-objective optimization so that DRs can cooperate with other DRs to eliminate harmonic currents with optimizing mutually conflicting multi-objectives.

• Advances in Computational Design
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• v.5 no.3
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• pp.233-260
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• 2020

The main purpose to introduce model based controller in proposed control technique is to provide better and fast learning of the floating dynamics by means of fuzzy logic controller and also cancelling effect of nonlinear terms of the system. An iterative adaptive dynamic programming algorithm is proposed to deal with the optimal trajectory-tracking control problems for autonomous underwater vehicle (AUV). The optimal tracking control problem is converted into an optimal regulation problem by system transformation. Then the optimal regulation problem is solved by the policy iteration adaptive dynamic programming algorithm. Finally, simulation example is given to show the performance of the iterative adaptive dynamic programming algorithm.

• Structural Engineering and Mechanics
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• v.46 no.5
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• pp.645-672
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• 2013

The differential settlements and rotations among footings cannot be avoided when the frame-footing-soil system is subjected to seismic/dynamic loading. Also, there may be a situation where column(s) of a building are located near adjoining property line causes eccentric loading on foundation system. The strap beams may be provided to control the rotation of the footings within permissible limits caused due to such eccentric loading. In the present work, the seismic interaction analysis of a three-bay three-storey, space frame-footing-strap beam-soil system is carried out to investigate the interaction behavior using finite element software (ANSYS). The RCC structure and their foundation are assumed to behave in linear manner while the supporting soil mass is treated as nonlinear elastic material. The seismic interaction analyses of space frame-isolated footing-soil and space frame-strap footing-soil systems are carried out to evaluate the forces in the columns. The results indicate that the bending moments of very high magnitude are induced at column bases resting on eccentric footing of frame-isolated footing-soil interaction system. However, use of strap beams controls these moments quite effectively. The soil-structure interaction effect causes significant redistribution of column forces compared to non-interaction analysis. The axial forces in the columns are distributed more uniformly when the interaction effects are considered in the analysis.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1105-1129
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• 2014

The unscented Kalman filter (UKF) has been developed for nonlinear model parametric identification, and it assumes that the model parameters are symmetrically distributed about their mean values without any constrains. However, the parameters in many applications are confined within certain ranges to make sense physically. In this paper, a constrained unscented Kalman filter (CUKF) algorithm is proposed to improve accuracy of numerical substructure modeling in hybrid testing. During hybrid testing, the numerical models of numerical substructures which are assumed identical to the physical substructures are updated online with the CUKF approach based on the measurement data from physical substructures. The CUKF method adopts sigma points (i.e., sample points) projecting strategy, with which the positions and weights of sigma points violating constraints are modified. The effectiveness of the proposed hybrid testing method is verified by pure numerical simulation and real-time as well as slower hybrid tests with nonlinear specimens. The results show that the new method has better accuracy compared to conventional hybrid testing with fixed numerical model and hybrid testing based on model updating with UKF.

• Smart Structures and Systems
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• v.18 no.4
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• pp.663-682
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• 2016

Continuum manipulators as a kind of mechanical arms are useful tools in special robotic applications. In medical applications, like colonoscopy, a maneuverable thin and flexible manipulator is required. This research is focused on developing a basic module for such an application using shape memory alloys (SMA). In the structure of the module three wires of SMA are uniformly distributed and attached to the circumference of a flexible tube. By activating wires, individually or together, different rotation regimes are provided. SMA model is used based on Brinson work. The SMA model is combined to model of flexible tube to provide a composite model of the module. Simulating the model in Matlab provided a platform to be used to develop controller. Complex and nonlinear behavior of SMA make the control problem hard especially when a few SMA actuators are active simultaneously. In this paper, position control of the two degree of freedom module is under focus. An experimental control strategy is developed to regulate a desired position in the module. The simulation results present a reasonable performance of the controller. Moreover, the results are verified through experiments and show that the continuum module of this paper would be used in real modular manipulators.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.53-62
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• 2009

Lee[15] examined quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model where quantity discounts are provided based on the previous order size. During the two periods, the retailer faces stochastic (truncated Poisson distributed) demands and he/she places orders to meet the demands. The manufacturer provides for the retailer a price discount for the second period order if its quantity exceeds the first period order quantity. In this paper we extend the above two-period model to a k-period one (where k < 2) and propose a stochastic nonlinear mixed binary integer program for it. In order to make the program tractable, the nonlinear term involving the sum of truncated Poisson cumulative probability function values over a certain range of demand is approximated by an i-interval piecewise linear function. With the value of i selected and fixed, the piecewise linear function is determined using an evolutionary algorithm where its fitness to the original nonlinear term is maximized. The resulting piecewise linear mixed binary integer program is then transformed to a mixed binary integer linear program. With the k-period model developed, we suggest a solution procedure of receding horizon control style to solve n-period (n < k) order decision problems. We implement Lee's two-period model and the proposed k-period model for the use in receding horizon control style to solve n-period order decision problems, and compare between the two models in terms of the pattern of order quantities and the total profits. Our computational study shows that the proposed model is superior to the two-period model with respect to the total profits, and that order quantities from the proposed model have higher fluctuations over periods.