• Title/Summary/Keyword: fuzzy-logic theory

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Control of a Segway with unknown control coefficient and input constraint

  • Park, Bong Seok
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.2
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    • pp.140-146
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    • 2016
  • This paper proposes a control method of the Segway with unknown control coefficient and input saturation. To design a simple controller for the Segway with the model uncertainty, the prescribed performance function is used. Furthermore, an auxiliary variable is introduced to deal with unknown time-varying control coefficient and input saturation problem. Due to the auxiliary variable, function approximators are not used in this paper although all model uncertainties are unknown. Thus, the controller can be simple. From the Lyapunov stability theory, it is proved that all errors of the proposed control system remain within the prescribed performance bounds. Finally, the simulation results are presented to demonstrate the performance of the proposed scheme.

Path Following Control of Mobile Robot Using Lyapunov Techniques and PID Cntroller

  • Jin, Tae-Seok;Tack, Han-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.1
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    • pp.49-53
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    • 2011
  • Path following of the mobile robot is one research hot for the mobile robot navigation. For the control system of the wheeled mobile robot(WMR) being in nonhonolomic system and the complex relations among the control parameters, it is difficult to solve the problem based on traditional mathematics model. In this paper, we presents a simple and effective way of implementing an adaptive following controller based on the PID for mobile robot path following. The method uses a non-linear model of mobile robot kinematics and thus allows an accurate prediction of the future trajectories. The proposed controller has a parallel structure that consists of PID controller with a fixed gain. The control law is constructed on the basis of Lyapunov stability theory. Computer simulation for a differentially driven nonholonomic mobile robot is carried out in the velocity and orientation tracking control of the nonholonomic WMR. The simulation results of wheel type mobile robot platform are given to show the effectiveness of the proposed algorithm.

Hybrid Feature Selection Using Genetic Algorithm and Information Theory

  • Cho, Jae Hoon;Lee, Dae-Jong;Park, Jin-Il;Chun, Myung-Geun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.1
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    • pp.73-82
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    • 2013
  • In pattern classification, feature selection is an important factor in the performance of classifiers. In particular, when classifying a large number of features or variables, the accuracy and computational time of the classifier can be improved by using the relevant feature subset to remove the irrelevant, redundant, or noisy data. The proposed method consists of two parts: a wrapper part with an improved genetic algorithm(GA) using a new reproduction method and a filter part using mutual information. We also considered feature selection methods based on mutual information(MI) to improve computational complexity. Experimental results show that this method can achieve better performance in pattern recognition problems than other conventional solutions.

Approximate Dynamic Programming-Based Dynamic Portfolio Optimization for Constrained Index Tracking

  • Park, Jooyoung;Yang, Dongsu;Park, Kyungwook
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.1
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    • pp.19-30
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    • 2013
  • Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.

A Term-based Language for Resource-Constrained Project Scheduling and its Complexity Analysis

  • Kutzner, Arne;Kim, Pok-Son
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.1
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    • pp.20-28
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    • 2012
  • We define a language $\mathcal{RS}$, a subclass of the scheduling language $\mathcal{RS}V$ (resource constrained project scheduling with variant processes). $\mathcal{RS}$ involves the determination of the starting times for ground activities of a project satisfying precedence and resource constraints, in order to minimize the total project duration. In $\mathcal{RS}$ ground activities and two structural symbols (operators) 'seq' and 'pll' are used to construct activity-terms representing scheduling problems. We consider three different variants for formalizing the $\mathcal{RS}$-scheduling problem, the optimizing variant, the number variant and the decision variant. Using the decision variant we show that the problem $\mathcal{RS}$ is $\mathcal{NP}$-complete. Further we show that the optimizing variant (or number variant) of the $\mathcal{RS}$-problem is computable in polynomial time iff the decision variant is computable in polynomial time.

Development of New Algorithm for RWA Problem Solution on an Optical Multi-Networks

  • Tack, Han-Ho;Kim, Chang-Geun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.2 no.3
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    • pp.194-197
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    • 2002
  • This paper considers the problem of routing connections in a optical multi tree networks using WDM (Wavelength Division Multiplexing), where each connection between a pair of nodes in the network is assigned a path through the network and a wavelength on that path, so that connections whose paths share a common link in the network are assigned different wavelengths. The problem of optimal coloring of the paths on the optical multi-networks is NP-hard[1], but if that is the coloring of all paths, then there exists efficient polynomial time algorithm. In this paper, using a "divide & conquer" method, we give efficient algorithm to assign wavelengths to all the paths of a tree network based on the theory of [7]. Here, our time complexity is 0(n4log n).

Efficient Extraction of Hierarchically Structured Rules Using Rough Sets

  • Lee, Chul-Heui;Seo, Seon-Hak
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.2
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    • pp.205-210
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    • 2004
  • This paper deals with rule extraction from data using rough set theory. We construct the rule base in a hierarchical granulation structure by applying core as a classification criteria at each level. When more than one core exist, the coverage is used for the selection of an appropriate one among them to increase the classification rate and accuracy. In Addition, a probabilistic approach is suggested so that the partially useful information included in inconsistent data can be contributed to knowledge reduction in order to decrease the effect of the uncertainty or vagueness of data. As a result, the proposed method yields more proper and efficient rule base in compatability and size. The simulation result shows that it gives a good performance in spite of very simple rules and short conditionals.

Formulation of the Neural Network for Implicit Constitutive Model (II) : Application to Inelastic Constitutive Equations

  • Lee, Joon-Seong;Lee, Eun-Chul;Furukawa, Tomonari
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.4
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    • pp.264-269
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    • 2008
  • In this paper, two neural networks as a material model, which are based on the state-space method, have been proposed. One outputs the rates of inelastic strain and material internal variables whereas the outputs of the other are the next state of the inelastic strain and material internal variables. Both the neural networks were trained using input-output data generated from Chaboche's model and successfully converged. The former neural network could reproduce the original stress-strain curve. The neural network also demonstrated its ability of interpolation by generating untrained curve. It was also found that the neural network can extrapolate in close proximity to the training data.

Multiple Sliding Surface Control Approach to Twin Rotor MIMO Systems

  • Van, Quan Nguyen;Hyun, Chang-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.3
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    • pp.171-180
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    • 2014
  • In this paper, a multiple sliding surface (MSS) controller for a twin rotor multi-input-multioutput system (TRMS) with mismatched model uncertainties is proposed. The nonlinear terms in the model are regarded as model uncertainties, which do not satisfy the standard matching condition, and an MSS control technique is adopted to overcome them. In order to control the position of the TRMS, the system dynamics are pseudo-decomposed into horizontal and vertical subsystems, and two MSSs are separately designed for each subsystem. The stability of the TRMS with the proposed controller is guaranteed by the Lyapunov stability theory. Some simulation results are given to verify the proposed scheme, and the real time performances of the TRMS with the MSS controller show the effectiveness of the proposed controller.