• Title/Summary/Keyword: Adaptive Combination

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A Novel Cluster-Based Cooperative Spectrum Sensing with Double Adaptive Energy Thresholds and Multi-Bit Local Decision in Cognitive Radio

  • Van, Hiep-Vu;Koo, In-Soo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.3 no.5
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    • pp.461-474
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    • 2009
  • The cognitive radio (CR) technique is a useful tool for improving spectrum utilization by detecting and using the vacant spectrum bands in which cooperative spectrum sensing is a key element, while avoiding interfering with the primary user. In this paper, we propose a novel cluster-based cooperative spectrum sensing scheme in cognitive radio with two solutions for the purpose of improving in sensing performance. First, for the cluster header, we use the double adaptive energy thresholds and a multi-bit quantization with different quantization interval for improving the cluster performance. Second, in the common receiver, the weighed HALF-voting rule will be applied to achieve a better combination of all cluster decisions into a global decision.

Speed Estimation and Control of IPMSM using HAI Control (HAI 제어를 이용한 IPMSM의 속도 추정 및 제어)

  • Lee, Jung-Chul;Lee, Hong-Gyun;Lee, Young-Sil;Nam, Su-Myeong;Chung, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • 2004.10a
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    • pp.176-178
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    • 2004
  • Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed.

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Maximum Torque Control of IPMSM Drive using Adaptive Fuzzy-Neuro Controller (적응 퍼지-뉴로 제어기를 이용한 IPMSM 드라이브의 최대토크 제어)

  • Kim, Do-Yeon;Ko, Jae-Sub;Choi, Jung-Sik;Jung, Byung-Jin;Park, Ki-Tae;Choi, Jung-Hoon;Chung, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • 2007.10c
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    • pp.126-128
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    • 2007
  • This paper proposes maximum torque control of IPMSM drive using Adaptive Fuzzy-Neuro controller and artificial neural network(ANN). The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. This paper proposes the analysis results to verify the effectiveness of the Adaptive Fuzzy-Neuro and ANN controller.

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A Simple Speech/Non-speech Classifier Using Adaptive Boosting

  • Kwon, Oh-Wook;Lee, Te-Won
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.3E
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    • pp.124-132
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    • 2003
  • We propose a new method for speech/non-speech classifiers based on concepts of the adaptive boosting (AdaBoost) algorithm in order to detect speech for robust speech recognition. The method uses a combination of simple base classifiers through the AdaBoost algorithm and a set of optimized speech features combined with spectral subtraction. The key benefits of this method are the simple implementation, low computational complexity and the avoidance of the over-fitting problem. We checked the validity of the method by comparing its performance with the speech/non-speech classifier used in a standard voice activity detector. For speech recognition purpose, additional performance improvements were achieved by the adoption of new features including speech band energies and MFCC-based spectral distortion. For the same false alarm rate, the method reduced 20-50% of miss errors.

Robust Flight Control System Using Neural Networks: Dynamic Surface Design Approach (신경 회로망을 이용한 강인 비행 제어 시스템: 동적 표면 설계 접근)

  • Yoon, Sung-Jin;Choi, Yoon-Ho;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2006.07d
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    • pp.1848-1849
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    • 2006
  • The new robust controller design method is proposed for the flight control systems with model uncertainties. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the "explosion of complexity" problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system.

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A New Excitation Control for Multimachine Power Systems I: Decentralized Nonlinear Adaptive Control Design and Stability Analysis

  • Psillakis Haris E.;Alexandridis Antonio T.
    • International Journal of Control, Automation, and Systems
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    • v.3 no.spc2
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    • pp.278-287
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    • 2005
  • In this paper a new excitation control scheme that improves the transient stability of multi machine power systems is proposed. To this end the backstepping technique is used to transform the system to a suitable partially linear form. On this system, a combination of both feedback linearization and adaptive control techniques are used to confront the nonlinearities. As shown in the paper, the resulting nonlinear control law ensures the uniform boundedness of all the state and estimated variables. Furthermore, it is proven that all the error variables are uniformly ultimately bounded (DUB) i.e. they converge to arbitrarily selected small regions around zero in finite-time. Simulation tests on a two generator infinite bus power system demonstrate the effectiveness of the proposed control.

An Adaptive Tracking Controller for Vibration Reduction of Flexible Manipulator

  • Sung Yoon-Gyeoung;Lee Kyu-Tae
    • International Journal of Precision Engineering and Manufacturing
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    • v.7 no.3
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    • pp.51-55
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    • 2006
  • An adaptive tracking controller is presented for the vibration reduction of flexible manipulator employed in hazardous area by combining input shaping technique with sliding-mode control. The combined approach appears to be robust in the presence of severe disturbance and unknown parameter which will be estimated by least-square method in real time. In a maneuver strategy, it is found that a hybrid trajectory with a combination of low frequency mode and rigid-body mode results in better performance and is more efficient than the traditional rigid body trajectory alone which many researchers have employed. The feasibility of the adaptive tracking control approach is demonstrated by applying it to the simplified model of robot system. For the applications of the proposed technique to realistic systems, several requirements are discussed such as control stability and large system order resulted from finite element modeling.

A Study on the Desired Target Signal Estimation using MUSIC and LCMV Beamforming Algorithm in Wireless Coherent Channel

  • Lee, Kwan Hyeong
    • International journal of advanced smart convergence
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    • v.9 no.1
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    • pp.177-184
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    • 2020
  • In this paper, we studied to direction of arrival (DoA) estimation to use DoA and optimum weight algorithms in coherent interference channels. The DoA algorithm have been considerable attention in signal processing with coherent signals and a limited number of snapshots in a noise and an interference environment. This paper is a proposed method for the desired signal estimation using MUSIC algorithm and adaptive beamforming to compare classical subspace techniques. Also, the proposed method is combined the updated weight value with LCMV beamforming algorithm in adaptive antenna array system for direction of arrival estimation of desired signal. The proposed algorithm can be used with combination to MUSIC algorithm, linearly constrained minimum variance beamforming (LCMV) and the weight value method to accurately desired signal estimation. Through simulation, we compare the proposed method with classical direction of in order to desired signals estimation. We show that the propose method has achieved good resolution performance better that classical direction arrival estimation algorithm. The simulation results show the effectiveness of the proposed method.

Integrated Guidance and Control Design Based on Adaptive Neural Network for Unpowered Air Vehicle (무추력 비행체를 대상으로 한 적응 통합 유도제어기 설계)

  • Kim, Boo-Min;Sung, Duck-Yong;Sung, Jea-Min;Kim, Byoung-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.1
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    • pp.15-22
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    • 2009
  • The guidance controller of the conventional aircraft consists of inner-loop (autopilot) and outer-loop (guidance). If the guidance controller can be designed as an integrated guidance and control (IGC), the various advantages exist. The integrated guidance and control formulation can compensate for the effect of autopilot lag. An integrated approach also helps avoid the iterative procedure involved in tuning the guidance and autopilot subsystems, if designed separately. Integrated design is also less susceptible to saturation and stability problems. This paper presents an approach to IGC design for the unpowered air vehicle with the only flaperon using a combination of adaptive output feedback inversion and backstepping techniques. Adaptive neural networks are trained online with available measurements to compensate for unmodeled nonlinearities in the design process.

A Study on the Adaptive Fuzzy Nonlinear VSS (비선형 슬라이딩 면을 가지는 적응 퍼지 제어기 설계)

  • 이대식;김혜경
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.9
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    • pp.788-792
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    • 2001
  • Although the general sliding model control has the robust property, bounds on the disturbances and parameter variations should be known a prior to the designer of the control system. However, these bounds may not be easily obtained. Fuzzy logic provides an effective way to design a controller of the system with disturbances and parameter variations. Therefore, combination of the best feature of the fuzzy logic control and the sliding mode control is considered. In this paper, the adaptive fuzzy variable structure controller developed for variables of fuzzy logic. A variable length pendulum system is used to demonstrate the availability of the proposed algorithm.

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