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IEEE Power and Energy Society General Meeting

作者： V.Verma M. J. Hossain T. Saha C. Chakraborty Department of Electrical Engineering Indian Institute of Technology Kharagpur India-721302 School of Information Technology and Electrical Engineering The University of Queensland QLD 4072 Australia School of Information Technology and Electrical Engineering The University of Queensland QLD 4072 Australia. Department of Electrical Engineering Indian Institute of Technology Kharagpur India-721302.

ISBN: (纸本)9781467327275

Rotor speed is required for the independent control of active power, reactive power and to achieve maximum power and also for pitch control. Speed estimation is preferred rather than sensing from accuracy, cost and reliability point of view. Different model reference adaptive System (MRAS) based speed estimation techniques are available for grid connected doubly fed induction machines. Performance of all the MRAS speed estimators has been studied under normal grid voltage. As per the new grid codes, wind turbine should remain connected to the grid during severe voltage dips [1]. Hence the performance of these speed estimators should also be studied under voltage dips. This paper compares the performances of different MRAS based estimators during voltage dips up to 50% and 5% of the nominal grid voltage. This paper also shows the effect of resistance variation on speed estimation during above mentioned operating conditions. Simulation has been performed in MATLAB/SIMULINK and the results are presented for various speed estimators.

关键词： MRAS Doubly fed induction machine Voltage dip Speed estimation MRAS gene voltage sags grids Induction machines gate voltage Grid Speed Estimation Estimators rotor speed independent control Maximum power model reference adaptive control

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adaptive model-based control of the Utah/MIT hand

Adaptive model-based control of the Utah/MIT hand

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IEEE International Conference on Systems Engineering

作者： Rainey Leahy Department of Electrical and Computer Engineering Air Force Institute of Technology OH USA

Although previous case studies rigorously investigated the feasibility of implementing passivity-based inner loop adaptation on an industrial manipulator, an unanswered question was the general validity of those results. That issue is addressed by repeating the analysis on a small serial robot with a pneumatic tendon drive system. Experimental analysis reverified the algorithm's adaptation/learning capabilities and provided insight into how the implementation issues of tuning and parameter convergence depend on specific manipulator structure. Direct adaptive control enhances trajectory efficacy for a wide range of manipulators.< >

关键词： model reference adaptive control Pneumatic systems

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Arbitrarily Fast Multivariable Least-squares MRAC

arXiv

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arXiv 2024年

作者： Hsu, Liu Costa, Ramon R. Lizarralde, Fernando Peixoto, Alessandro J. Department of Electrical Engineering COPPE Federal University of Rio de Janeiro RJ Brazil

A novel least-squares model-reference direct adaptive control (LS-MRAC) algorithm for multivariable (MIMO) plants is presented. The controller parameters are directly updated based on the output tracking error. The control law is crucially modified to reduce the relative degree of the error model to zero. A complete Lyapunov-based stability analysis as well as a tracking error convergence characterization is provided demonstrating that the LS-MRAC can achieve arbitrarily fast tracking while maintaining satisfactory parameter convergence for appropriate adaptation gains. Simulation results show a significant improvement in tracking performance compared to previous methods. © 2024, CC BY.

关键词： model reference adaptive control

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adaptive Tracking of Infinite-Dimensional reference models for Linear Infinite-Dimensional Systems in Hilbert Space

Adaptive Tracking of Infinite-Dimensional Reference Models f...

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American control Conference

作者： Mark J. Balas Susan A. Frost Embry-Riddle Aeronautical University Daytona Beach FL 32119 USA NASA Ames Research Center Moffett Field CA

ISBN: (纸本)9781479917730

This paper is focused on adaptively controlling a linear infinite-dimensional system to cause it to track an infinite-dimensional reference model. Given a linear continuous-time infinite-dimensional plant on a Hilbert space and disturbances of known waveform but unknown amplitude and phase, we show that there exists a stabilizing direct model reference adaptive control law with certain disturbance rejection and robustness properties. Both the plant and the reference model are described by closed, densely defined linear operators that generate continuous semigroups of bounded operators on the Hilbert space of states. An extension of the Barbalat-Lyapunov result for infinite dimensional Hilbert spaces is used to determine conditions under which a linear Infinite-dimensional system can be directly adaptively controlled to follow such a reference model. In particular we examine conditions for a set of ideal trajectories to exist for the tracking problem and show the solvability of the infinite dimensional matching conditions under the simple condition that the high frequency gain CB is nonsingular and the reference system is a normal operator with compact resolvent.

关键词： Hilbert space reference model adaptive tracking reference system tracking problem model reference adaptive control linear operators Disturbance rejection control law computability Linear

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Multi-core Implementation of F-16 Flight Surface control System using Genetic Algorithm Based adaptive control Algorithm

Multi-core Implementation of F-16 Flight Surface Control Sys...

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IEEE National Aerospace and Electronics Conference

作者： Xiaoru Wang Mohammad Wadood Majid Mohsin M. Jamali Department of Electrical Engineering & Computer Science University of Toledo

ISBN: (纸本)9781457710407

A Multiple model reference adaptive control (MMRAC) with Genetic Algorithm (GA) based model selection scheme for a F-16 flight surface control system has been proposed. It is an extension of previously reported work [5]. It simulates all three rotation motion controls such as pitch, roll and yaw. It then incorporates numerical solution of differential equation using 4th order Runge-Kutta algorithm in the simulation. This paper focuses on implementation of the proposed algorithm on a 4-core-Architecture of Intel i5 CPU. The sequential code was first written in C++ on .NET Framework 4. Parallel processing approaches were exploited for parallelization of the control system. Several optimization techniques were used to achieve the maximum speed up. The parallelized algorithm is appropriate for real time computation.

关键词： control systems Genetic Algorithm (GA) maximum speed Computer algorithms flight YAW model reference adaptive control parallelization adaptive control Differential equations real-time computation sequential codes

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Improving the Efficiency of Power Supplies with an adaptive control Method

Improving the Efficiency of Power Supplies with an Adaptive ...

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International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology

作者： M. Mahdavian M. Bayati Poudeh N. Wattanapongsakorn Department of Computer Engineering King Mongkut's University of Technology Thonburi 126 Pracha-Utid Rd. Bangmod Toongkru Bangkok 10140 Thailand

ISBN: (纸本)9781479905461

Normally power supplies provide a constant output voltage. A DC-DC converter in most of the applications is controlled by a voltage mode or a current mode controller. The DC converters are employed to feed electric vehicles, telephone sets and civil invertors, or for induction motors and frequency control. In this regard, optimal exploitation of DC transformed by classical controllers has been a controversial issue in reputable journal publications. Due to their switching property included in their structure, DC-DC converters have a non-linear behavior and their controlling design is accompanied with complexities. However, by employing the average method, it is possible to simplify the system as a linear system and exploiting linear control methods. In this article, an attempt is made to control the buck converter by PI and PID controllers. By using PID controller and genetic algorithm, a new adaptive control method model is introduced. A Genetic algorithm is applied to discover the supreme values for PID controller's parameters within a short time period. The improvement of the current control response is the result of the simulation.

关键词： buck converter genetic algorithm PID controller model reference adaptive control

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A Reproducing Kernel Hilbert Space Approach for the Online Update of Radial Bases in Neuro-adaptive control

A Reproducing Kernel Hilbert Space Approach for the Online U...

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IEEE Conference on Decision and control

作者： Hassan A. Kingravi Girish Chowdhary Patricio A. Vela Eric N. Johnson School of Electrical and Computer Engineering at Georgia Institute of Technology Atlanta GA Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology Atlanta GA

ISBN: (纸本)9781612848006

Classical gradient based adaptive laws in model reference adaptive control for uncertain nonlinear dynamical systems with a Radial Basis Function (RBF) neural networks adaptive element do not guarantee that the network weights stay bounded in a compact neighborhood of the ideal weights without Persistently Exciting (PE) system signals or a-priori known bounds on ideal weights. Recent work has shown, however, that an adaptive controller using specifically recorded data concurrently with instantaneous data can guarantee such boundedness without requiring PE signals. However, in this work, the assumption has been that the RBF network centers are fixed, which requires some domain knowledge of the uncertainty. We employ a Reproducing Kernel Hilbert Space theory motivated online algorithm for updating the RBF centers to remove this assumption. Along with showing the boundedness of the resulting neuro-adaptive controller, a connection is also made between PE signals and kernel methods. Simulation results show improved performance.

关键词： Nonlinear dynamical systems domain knowledge network weight Hilbert space adaptive controller model reference adaptive control signals

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Research of MRAC on Intervals between Arriving Flights controlling

Research of MRAC on Intervals between Arriving Flights Contr...

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The 22nd China control and Decision Conference(2010年中国控制与决策会议)

作者： Shiwei ZHAO Keqiang HUA Peng ZHANG Guo WEI Engineering Techniques Training Center Civil Aviation University of China Tianjin 300300 China

In this paper, the problem of interval controlling between arriving flights is researched. According to character of arriving flights dynamic process, bring forward reasonable assumption, and convert problem of arriving flights’ interval controlling, whose attribute is discrete event dynamic system, into problem of generalized dynamic system controlling. Through analyzing actual measuring data, establish model of arriving flights dynamic process by identification technology, and design arriving flights interval control system with method of model reference adaptive control (MRAC). Adopting MATLAB to carry out simulation, result shows that arriving flights’ intervals variance obviously reduces and process of arriving flights becomes smooth. This supplies new way to research and develop air traffic control (ATC) assistant decision system, and realize ATC automation.

关键词： Interval controlling Discrete event Dynamic System model reference adaptive control Air Traffic control

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Nonparametric adaptive control using Gaussian Processes with Online Hyperparameter Estimation

Nonparametric Adaptive Control using Gaussian Processes with...

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IEEE Annual Conference on Decision and control

作者： Robert C. Grande Girish Chowdhary Jonathan P. How Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology Cambridge MA

ISBN: (纸本)9781467357159

Many current model reference adaptive control methods employ parametric adaptive elements in which the number of parameters are fixed a-priori and the hyperparameters, such as the bandwidth, are pre-defined, often through expert judgment. Typical examples include the commonly used Radial Basis Function (RBF) Neural Networks (NNs) with pre-allocated centers. As an alternative to these methods, a nonparametric model using Gaussian Processes (GPs) was recently proposed. Using GPs, it was shown that it is possible to maintain constant coverage over the operating domain by adaptively selecting new kernel locations without any previous domain knowledge. However, even if kernel locations provide good coverage of the input domain, incorrect bandwidth selection can result in poor characterization of the model uncertainty, leading to poor performance. In this paper, we propose methods for learning hyperparameters online in GP-MRAC by optimizing a modified likelihood function. We prove the stability and convergence of our algorithm in closed loop. Finally, we evaluate our methods in simulation on an example of wing rock dynamics. Results show learning hyperparameters online robustly reduces the steady state modeling error and improves control smoothness over other MRAC schemes.

关键词： Gaussian processes model uncertainty model reference adaptive control Hyperparameter Expert Opinion control Methods Bandwidth domain knowledge adaptive control

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A Multivariable MRAC Design Using State Feedback for Linearized Aircraft models with Damage

A Multivariable MRAC Design Using State Feedback for Lineari...

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American control Conference

作者： Jiaxing Guo Yu Liu Gang Tao Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904

ISBN: (纸本)9781424474264

Aircraft damage causes large uncertain system parametric and structural changes which lead to unknown deviations of the aircraft equilibrium points and unknown coupling of the aircraft dynamics. To deal with such unknown changes, we use a sequential linear model with a dynamics offset to represent a linearized aircraft system before and after damage. A state feedback multivariable model reference adaptive control (MRAC) scheme is developed for such a linear model, with adaptive compensation of the uncertain dynamics offset as well as system parametric uncertainties. Desired closed-loop signal boundedness and asymptotic output tracking are established. Numerical values of linearized models from the NASA GTM were used in the simulation study and its results verified the desired system performance despite uncertain damage.

关键词： adaptive control state feedback output tracking aircraft damage flight control linearization GTM State feedback Aircraft control adaptive control Linearization model reference adaptive control System performance Aircraft models Aircraft adaptive compensation linear models

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