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Basic characteristics inherent in model reference adaptive control systems

Theoretical and Applied Mechanics Japan 2008年 56卷 105-113页

作者： Yamamoto, Daizo Baba, Kensuke Token Corporation Nagoya Aichi Japan Department of Architectural Engineering Osaka University Suita Osaka Japan

The design indicator is not necessarily provided systematically with adaptive control algorithm when assembling vibration control systems for building construction and in consequence obliged to follow after empirical rules, Present study aims at accumulating the basic properties necessary for designing adaptive composition with state variable filters to give circulated signal information and active on-line loops sustaining adaptive organization. In the simulation analysis, target conditions are firstly set up tight without reference models to arrange objective signals calm. The second situations are prepared with relaxant objective setting on reference signals to investigate the working of target models.

关键词： model reference adaptive control

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An Improved MRAC Scheme for Non-linear Design of Adaption Gain γ using Heuristic Algorithms

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IFAC Proceedings Volumes 2014年第1期47卷 734-739页

作者： Anuj Abraham N. Pappa Department of Instrumentation Engineering Madras Institute of Technology Campus Anna University Chennai-44. India

This paper presents an approach to Optimal model reference adaptive control (OMRAC) and comparative performance evaluation are analyzed for a conical tank process which exhibits behavior of a class of nonlinear dynamical system. The conventional model reference adaptive control (MRAC) method based on the MIT rule reported in the works (P. Swarnkar et al., 2010), has its difficulty in choosing the reference model and adaption gain γ . Inspired by the above work, the selection of reference models in MRAC scheme are based on the multiple models (MM) depending on the operating regime of the process. In this proposed work, the reference model considered is a second order system having fixed roots in denominator polynomial representing the most dominant poles in the process determined using Dominant Pole Algorithm (DPA). The numerator polynomial of the reference model is designated as static sensitivity from each linearized region of the process. The optimal adaption gain γ of MRAC is obtained by Bacterial Foraging based Particle Swarm Optimization (BFPSO) algorithm and the system performance is compared with traditional algorithms such as Bacterial Foraging Optimization (BFO) and Particle Swarm Optimization (PSO). The simulated result gives consistently better setpoint tracking mechanism and error minimization.

关键词： adaptive control systems adaption gain MIT rule model reference adaptive control multiple model bacterial foraging optimization dominant pole

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Robust Evolving Fuzzy adaptive control With Input-domain Clustering

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IFAC Proceedings Volumes 2014年第3期47卷 5387-5392页

作者： Saso Blazic Dejan Dovzan Igor Skrjanc Faculty of Electrical Engineering University of Ljubljana Ljubljana Slovenia

The paper proposes a fuzzy model reference adaptive control approach with evolving antecedent part. The proposed algorithm has the possibility of controlling a plant with poorly known and/or time-varying nonlinearity which is an advantage over approaches with fixed antecedent part. It is intended for control of a large class of nonlinear plant models with the dominant dynamics of the first order. Such plants occur quite often in process industries.

关键词： adaptive neural and fuzzy control adaptive control model reference adaptive control evolving systems Takagi-Sugeno model clusters

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State Dependent Riccati Equation Based model reference adaptive Stabilization of Nonlinear Systems with Application to Cancer Treatment

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IFAC Proceedings Volumes 2014年第3期47卷 1296-1301页

作者： Naser Babaei Metin U. Salamci Department of Mechanical Engineering Gazi University Ankara Turkey

The paper suggests a new approach to model reference adaptive control (MRAC) design for stabilization of a class of uncertain nonlinear systems. The proposed MRAC design methodology is based upon a stable nonlinear reference model which is produced by a state feedback controller using the so-called State Dependent Riccati Equation (SDRE) techniques. Based on states of the reference model, the designed stabilizer for the nonlinear reference model is then adapted for the nonlinear plant dynamics with a suitable adaptation mechanism, again by using the SDRE methodology. The proposed technique is illustrated to develop an optimal chemotherapy drug administration for cancer treatment using a tumor growth mathematical model. Simulation results show the effectiveness of the proposed SDRE-based MRAC method for the stabilization of nonlinear systems.

关键词： model reference adaptive control Nonlinear systems Cancer treatment Optimal control State dependent Riccati equation

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adaptive control of Bivalirudin in the Cardiac Intensive Care Unit

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IFAC Proceedings Volumes 2014年第3期47卷 8427-8432页

作者： Qi Zhao T. Edrich Ioannis Ch. Paschalidis Division of System Eng. Boston Univ. USA Dept. of Anesthesia Perioperative and Pain Medicine Brigham and Women's Hospital Boston USA Dept. of Electrical & Computer Eng. and Center for Information & Systems Eng. Boston Univ. 8 St. Mary's St. Boston MA 02215 USA http://ionia.bu.edu

Bivalirudin is a direct thrombin inhibitor used in the cardiac intensive care unit in patients who develop an allergic reaction to heparin. Since it is not a commonly used drug, clinical experience with its dosing is sparse. In earlier work (Zhao et al. [2014]) we developed a dynamic system model that accurately predicts the effect of bivalirudin when given dosage over time and patient physiological characteristics. This paper develops adaptive dosage controllers that regulate its effect to desired levels. To that end, and in the case that bivalirudin model parameters are available, we develop a model reference control law. In the case that model parameters are unknown, an indirect model reference adaptive control scheme is applied to estimate model parameters first and then adapt the controller. Our algorithms are validated using actual data from a large hospital in the Boston area.

关键词： Bivalirudin Pharmacokinetics Parameter Identification model reference control model reference adaptive control

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Improving Position Sensor Accuracy through Spatial Harmonic Decoupling, and Sensor Scaling, Offset, and Orthogonality Correction Using Self-Commissioning MRAS-Methods

Improving Position Sensor Accuracy through Spatial Harmonic ...

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IEEE Energy Conversion Congress and Exposition

作者： Caleb W. Secrest Jon S. Pointer Michael R. Buehner Robert D. Lorenz Univ. of Wisconsin-Madison WEMPEC Madison WI 53706 Woodward Inc. Fort Collins CO 80525

ISBN: (纸本)9781479957774

This paper presents methods for improving the accuracy of vector-based position measurements through the decoupling of multiple non-ideal sensor properties using model reference adaptive system (MRAS) techniques. The non-ideal sensor properties considered are: signal scaling errors (amplitude imbalance on the vector components), signal offsets, imperfect orthogonality (quadrature error) between sensor vector components, and additional spatial harmonics superimposed on the fundamental sensor outputs. Simulation and experimental results are provided to evaluate the proposed MRAS-based decoupling methods. The methods presented here can be applied to multiple forms of vector-based position measurement and estimation such as the use of magneto-resistive sensors, sine/cosine encoders, resolvers, or self-sensing (sensorless) methods. These methods can be implemented in real-time and are well-suited to the self-commissioning of vector-based position sensors for enhanced sensor accuracy.

关键词： position sensor DECOUPLING Sensors Position measurement Multiple forms space harmonics orthogonality model reference adaptive control

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MR based PET attenuation correction (MRAC) and anatomical localization of human brain using an optimized UTE-mDixon pulse sequence

MR based PET attenuation correction (MRAC) and anatomical lo...

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IEEE Nuclear Science Symposium

作者： Lingzhi Hu Christian Stehning Nghi Nguyen Andrew Sher Claudia Martinez Rios Zhiqiang Hu Lingxiong Shao Philips Healthcare Cleveland OH 44124 USA

ISBN: (纸本)9781479960989

MR based Attenuation Correction (MRAC) is essential for PET quantitation and image quality assurance in PET/MR. Ultra-short TE (UTE) sequence is promising in generating positive contrast for cortical bone but its further adoption is limited by prohibitively long scan time, lack of soft tissue contrast, and potential ambiguity in a tissue classification due to MR imaging artifacts. In this investigation, we aimed to develop a new MRAC method that consists an optimized under-sampled UTE-mDixon sequence and an iterative voxel-based tissue classification algorithm to generate 4-compartment μ-map, including water, fat, bone and air cavity. In vivo UTE-mDixon images were acquired on 12 human subjects and the developed segmentation method was employed for tissue classification. Diagnostic quality of MR images and the tissue classification accuracy for MRAC was evaluated by three radiologists independently. As a unique advantage over other MRAC sequences, the under-sampled UTE-mDixon of whole brain with retrospective trajectory delay calibration can be finished within less than 3 minutes providing both high quality water/fat separation images for anatomical localization and UTE images for bone segmentation. Robust tissue classification was achieved in all subjects as evaluated by radiologists. The developed MR scan methodology together with tissue classification algorithm may provide a one-scan solution for attenuation correction and anatomical localization in PET/MR.

关键词： model reference adaptive control human subject air cavity Image quality Sorting algorithm

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Novel switched model reference adaptive control for continuous Piecewise Affine systems

Novel switched Model Reference Adaptive Control for continuo...

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47th IEEE Conference on Decision and control

作者： di Bernardo, Mario Montanaro, Umberto Santini, Stefania Univ Naples Federico II Dept Syst & Comp Engn Via Claudio 21 I-80125 Naples Italy

ISBN: (纸本)9781424431243

This paper is concerned with the derivation of a novel model reference adaptive control (MRAC) scheme for piecewise-affine (PWA) continuous systems. A novel version of the minimal control synthesis algorithm, originally developed as a MRAC for smooth systems, is presented. The resulting adaptive algorithm is a switched feedback controller able to cope with uncertain continuous PWA systems. The proof of stability, based on the newly developed passivity theory for hybrid systems, is provided and the effectiveness of the new proposed control strategy is numerically tested.

关键词： model reference adaptive control

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H∞ adaptive Tracking control for Switched Systems Based on an Average Dwell-time Method

H∞ Adaptive Tracking Control for Switched Systems Based on ...

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西南大学2014年全国博士生学术论坛(电子技术与信息科学领域)

作者： Caiyun Wu Jun Zhao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 China

This paper investigates the H∞ state tracking model reference adaptive control (MRAC) problem for a class of switched systems using an average dwell-time ***, a stability criterion is established for a switched reference ***, an adaptive controller is designed and the state tracking control problem is converted into the stability *** global practical stability of the error switched system can be guaranteed under a class of switching signals characterized by an average dwell ***, sufficient conditions for the solvabilty of the H∞ state tracking model reference adaptive control problem are *** example of Highly Maneuverable Aircraft Technology (HiMAT) vehicle is given to demonstrate the feasibility and effectiveness of the proposed design method.

关键词： Switched systems model reference adaptive control H∞ control average dwell time

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Asymptotic adaptive Tracking with Input Amplitude and Rate Constraints and Bounded Disturbances

Asymptotic Adaptive Tracking with Input Amplitude and Rate C...

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IEEE Annual Conference on Decision and control

作者： Sze Zheng Yong Emilio Frazzoli Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA USA

ISBN: (纸本)9781467360890

In this paper, we develop a direct model reference adaptive control framework for asymptotic adaptive tracking in the presence of actuator input amplitude and rate constraints for some classes of uncertain linear time-invariant systems and nonlinear systems. This framework also allows for rejection of bounded time-varying disturbances, without causing any chatter in the control input. Moreover, positive (ρ,μ)-modification is proposed to protect the control law from the actuator saturation limits. The design is model-based and ensures global asymptotic tracking for open-loop input-to-state stable systems, while an estimate of the domain of attraction is derived for local asymptotic tracking in the case of input-to-state unstable systems. The approach is illustrated with examples.

关键词： adaptive tracking control law stabilization system asymptotic tracking region of attraction model reference adaptive control Bounded Amplitude asymptotic

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