• Title/Summary/Keyword: Self-Adaptive Systems

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Optimal Design of a Hybrid Structural Control System using a Self-Adaptive Harmony Search Algorithm (자가적응 화음탐색 알고리즘을 이용한 복합형 최적 구조제어 시스템 설계)

  • Park, Wonsuk
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.31 no.6
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    • pp.301-308
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    • 2018
  • This paper presents an optimal design method of a hybrid structural control system considering multi-hazard. Unlike a typical structural control system in which one system is designed for one specific type of hazard, a simultaneous optimal design method for both active and passive control systems is proposed for the mitigation of seismic and wind induced vibration responses of structures. As a numerical example, an optimal design problem is illustrated for a hybrid mass damper(HMD) and 30 viscous dampers which are installed on a 30 story building structure. In order to solve the optimization problem, a self-adaptive Harmony Search(HS) algorithm is adopted. Harmony Search algorithm is one of the meta-heuristic evolutionary methods for the global optimization, which mimics the human player's tuning process of musical instruments. A self-adaptive, dynamic parameter adjustment algorithm is also utilized for the purpose of broad search and fast convergence. The optimization results shows that the performance and effectiveness of the proposed system is superior with respect to a reference hybrid system in which the active and passive systems are independently optimized.

Adaptive Control of the Nonlinear Systems Using Diagonal Recurrent Neural Networks (대각귀환 신경망을 이용한 비선형 적응 제어)

  • Ryoo, Dong-Wan;Lee, Young-Seog;Seo, Bo-Hyeok
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.939-942
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    • 1996
  • This paper presents a stable learning algorithm for diagonal recurrent neural network(DRNN). DRNN is applied to a problem of controlling nonlinear dynamical systems. A architecture of DRNN is a modified model of the Recurrent Neural Network(RNN) with one hidden layer, and the hidden layer is comprised of self-recurrent neurons. DRNN has considerably fewer weights than RNN. Since there is no interlinks amongs in the hidden layer. DRNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. To guarantee convergence and for faster learning, an adaptive learning rate is developed by using Lyapunov function. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed algorithm is demonstrated by computer simulation.

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Development of Modern Control Simulation Pachage - KERICON(I)

  • Park, Jung-Woo;Lee, Jae-Duck;Kim, Kook-Hun;Kim, Hee-Yo
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.1436-1439
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    • 1990
  • Even though the concept "Adaptive" was introduced in the late 50's, the main contribution to adaptive and/or self-tuning control has been made since late 70's. This paper describes the feature of adaptive control simulation package KERICON(I) developed in KERI. Informations on hardware environments, install and testing of a new algorithm and user interfacings are also summarized. The package is written in C language and currently being updated for expert-type adaptive control package (KERICON II).RICON II).

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Seismic damage mitigation of bridges with self-adaptive SMA-cable-based bearings

  • Zheng, Yue;Dong, You;Chen, Bo;Anwar, Ghazanfar Ali
    • Smart Structures and Systems
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    • v.24 no.1
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    • pp.127-139
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    • 2019
  • Residual drifts after an earthquake can incur huge repair costs and might need to replace the infrastructure because of its non-reparability. Proper functioning of bridges is also essential in the aftermath of an earthquake. In order to mitigate pounding and unseating damage of bridges subjected to earthquakes, a self-adaptive Ni-Ti shape memory alloy (SMA)-cable-based frictional sliding bearing (SMAFSB) is proposed considering self-adaptive centering, high energy dissipation, better fatigue, and corrosion resistance from SMA-cable component. The developed novel bearing is associated with the properties of modularity, replaceability, and earthquake isolation capacity, which could reduce the repair time and increase the resilience of highway bridges. To evaluate the super-elasticity of the SMA-cable, pseudo-static tests and numerical simulation on the SMA-cable specimens with a diameter of 7 mm are conducted and one dimensional (1D) constitutive hysteretic model of the SMAFSB is developed considering the effects of gap, self-centering, and high energy dissipation. Two types of the SMAFSB (i.e., movable and fixed SMAFSBs) are applied to a two-span continuous reinforced concrete (RC) bridge. The seismic vulnerabilities of the RC bridge, utilizing movable SMAFSB with the constant gap size of 60 mm and the fixed SMAFSBs with different gap sizes (e.g., 0, 30, and 60 mm), are assessed at component and system levels, respectively. It can be observed that the fixed SMAFSB with a gap of 30 mm gained the most retrofitting effect among the three cases.

Effectiveness of e-health systems in improving hypertension management and awareness: a systematic review

  • Alotaibi, Mohamed;Ammad uddin, Mohammad
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.1
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    • pp.173-187
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    • 2022
  • Recent studies have focused on self-management of hypertension using smart devices (cellular phones, tablets, watches). It has proven to be an effective tool for early detection and control of high Blood Pressure (BP) without affecting patients' daily routines. This systematic review surveys the existing self-monitoring systems, evaluate their effectiveness and compares the different approaches. We investigated the current systems in terms of various attributes, including methods used, sample size, type of investigation, inputs/ outputs, rate of success in controlling BP, group of users with higher response rate and beneficiaries, acceptability, and adherence to the system. We identified some limitations, shortcomings, and gaps in the research conducted recently studying the impact of mobile technology on managing hypertension. These shortcomings can generate future research opportunities and enable it to become more realistic and adaptive. We recommended including more observable factors and human behaviors that affect BP. Furthermore, we suggested that vital monitoring/logging and medication tuning are insufficient to improve hypertension control. There is also a need to observe and alter patient behavior and lifestyles.

Adaptive compliant control for scara manipulator

  • Yee, Yanghyi;Ka, Minho;Kim, Sungwoo;Park, Mignon;Lee, Sangbae
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.1322-1326
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    • 1990
  • In this paper, compliant motion control of a manipualator in manipulator is proposed by using the self-tuning adaptive controller. Compliant motion is needed in order to applicated to complicated and accurate fields such as assembly operation in which several parts are matched. For a control method of compliant motion hybrid control is used so forces and position control are proposed selectively through a closed feedback loop. By contacting with environment, the uncertainties higher. Self-tuning controller which adapts to variable dynamic response is applied to compliant motion control in order to satisfy the desired operation. The applicability of the suggested algorithm was confirmed by simulation of the contour tracking task of four joint manipulator.

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The Self-tuning PID Control Based on Real-time Adaptive Learning Evolutionary Algorithm (실시간 적응 학습 진화 알고리듬을 이용한 자기 동조 PID 제어)

  • Chang, Sung-Ouk;Lee, Jin-Kul
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.9
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    • pp.1463-1468
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    • 2003
  • This paper presented the real-time self-tuning learning control based on evolutionary computation, which proves its superiority in finding of the optimal solution at the off-line learning method. The individuals of the populations are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations is proposed. It is possible to control the control object slightly varied as time changes. As the state value of the control object is generated, evolutionary strategy is applied each sampling time because the learning process of an estimation, selection, mutation is done in real-time. These algorithms can be applied; the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes.

Indirect Adaptive Self-Regulating Fuzzy Control of Uncertain Nonlinear Systems Using Second Order Sliding Mode (2차 슬라이딩 모드를 이용한 불확실성을 갖는 비선형 시스템의 간접적응 자기조정 퍼지제어)

  • Park, Won-Sung;Yang, Hai-Won;Chung, Ki-Chull;Kim, Do-Woo
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.1716-1717
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    • 2007
  • In this paper, a second order fuzzy sliding mode control that combines with a adaptive self-regulating technique is proposed for a nonlinear system with unknown dynamics. The chattering effect that is a representative disadvantage of the sliding mode control is avoided by using the second order sliding mode control instead of the first order sliding mode control. The proposed sub-controller is composed of the equivalent control that is approximated by an online rule regulation sheme and the hitting control that is used to constrain the states of the sub-system to maintain on the sub-sliding surface and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller

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Decentralized Adaptive Control of Interconnected System using Off-Set Modeling (오프셋 모형화 기법을 이용한 상호연관 시스템의 분산형 적응제어)

  • 양흥석;박용식;주성순
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.37 no.12
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    • pp.879-883
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    • 1988
  • In this paper, self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in MIMO ARMA procss. This process is simlified as independent SISO ARMA processes having offset terma, which are considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the paramter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results consider well with the analysis in case of linear interconnection.

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Design of Learning Fuzzy Controller by the Self-Tuning Algorithm for Equipment Systems (설비시스템을 위한 자기동조기법에 의한 학습 FUZZY 제어기 설계)

  • Lee, Seung
    • The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.9 no.6
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    • pp.71-77
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    • 1995
  • This paper deals with design method of learning fuzzy controller for control of an unknown nonlinear plant using the self-tuning algorithm of fuzzy inference rules. In this method the fuzzy identification model obtained that the joined identification model of nonlinear part and linear identification model of linear part by fuzzy inference systems. This fuzzy identification model ordered self-tuning by Decent method so as to be servile to nonlinear plant. A the end, designed learning fuzzy controller of fuzzy identification model have learning structure to model reference adaptive system. The simulation results show that th suggested identification and learning control schemes are practically feasible and effective.

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