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Robust Self-tuning control Based on Discrete-time Sliding Mode for Auto-regressive Mathematical Model in the Presence of Unmodelled Dynamics

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International Journal of Automation and computing 2016年第3期13卷 277-284页

作者： Nabiha Touijer Samira Kamoun Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (Lab-STA) National School of Engineering of SfaxUniversity of Sfax

In this paper, we propose a new robust selfbtuning control, called the generalized minimum variance a/-equivalent self- tuning control （GMVSTC-a/） for the linear timevarying （LTV） systems, which can be described by the discrete-time auto-regressive exogenous （ARX） mathematical model in the presence of unmodelled dynamics. The estimation of the parameters contained in this mathematical model is made on the basis of the proposed modified recursive least squares （m-RLS） parametric estimation algorithm with dead zone and forgetting factor. The stability analysis of the proposed parametric estimation algorithm m-RLS is treated on the basis of a Lyapunov function. A numerical simulation example is used to prove the performances and the effectiveness of the explicit scheme of the proposed robust self-tuning control GMVSTC-a/.

关键词： Discrete-time systems parametric uncertainty robust estimation robust self-tuning control sliding mode control sta-bility.

Distributed Optimization for Second-Order Multi-Agent Systems with Dynamic Event-Triggered Communication

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arXiv 2018年

作者： Yi, Xinlei Yao, Lisha Yang, Tao George, Jemin Johansson, Karl H. Department of Automatic Control Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm100 44 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States U.S. Army Research Laboratory AdelphiMD20783 United States

In this paper, we propose a fully distributed algorithm for second-order continuous-time multi-agent systems to solve the distributed optimization problem. The global objective function is a sum of private cost functions associated with the individual agents and the interaction between agents is described by a weighted undirected graph. We show the exponential convergence of the proposed algorithm if the underlying graph is connected, each private cost function is locally gradient-Lipschitz-continuous, and the global objective function is restricted strongly convex with respect to the global minimizer. Moreover, to reduce the overall need of communication, we then propose a dynamic event-triggered communication mechanism that is free of Zeno behavior. It is shown that the exponential convergence is achieved if the private cost functions are also globally gradient-Lipschitz-continuous. Numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2018, The Authors. All rights reserved.

关键词： Multi agent systems

Machine-Learning-based High-resolution DOA Measurement and Robust DM for Hybrid Analog-Digital Massive MIMO Transceiver

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arXiv 2018年

作者： Shu, Feng Xu, Ling Lin, Jinyong Hu, Jingsong Gui, Linqing Li, Jun Wang, Jiangzhou School of Electronic and Optical Engineering Nanjing University of Science and Technology 210094 China College of Computer and Information Sciences Fujian Agriculture and Forestry University Fuzhou350002 China Beijing Aerospace Automatic Control Institute Beijing100854 China School of Engineering and Digital Arts University of Kent CanterburyCT2 7NT United Kingdom

—At hybrid analog-digital (HAD) transceiver, an improved HAD rotational invariance techniques (ESPRIT), called I-HAD-ESPRIT, is proposed to measure the direction of arrival (DOA) of desired user, where the phase ambiguity due to HAD structure is addressed successfully. Subsequently, a machine-learning (ML) framework is proposed to improve the precision of measuring DOA. In the training stage, the HAD transceiver works as a receiver and repeatedly measures the values of DOA via I-HAD-ESPRIT to form a slightly large training data set (TDS) of DOA. From TDS, we find that the probability density function (PDF) of DOA measurement error (DOAME) is approximated as a Gaussian distribution by the histogram method in ML. This TDS is used to learn the mean of DOA and the variance of DOAME, which are utilized to infer their values and improve their precisions in the real-time stage. The HAD transceiver rapidly measures the real-time value of DOA some times to form a relatively small real-time set (RTS), which is used to learn the real-time mean and variance of DOA/ DOAME. Then, three weight combiners are proposed to combine the-maximum-likelihood-learning outputs of TDS and RTS. Their weight factors depend intimately on the numbers of elements in TDS and RTS, and signal-to-noise ratios during the two stages. Using the mean and variance of DOA/DOAME, their PDFs can be given directly, and we propose a robust beamformer for directional modulation (DM) transmitter with HAD by fully exploiting the PDF of DOA/DOAME, especially a robust analog beamformer on RF chain. Simulation results show that: 1) The proposed I-HAD-ESPRIT can achieve the HAD CRLB;2) The proposed ML framework performs much better than the corresponding real-time one without training stage, 3) The proposed robust DM transmitter can perform better than the corresponding nonrobust ones in terms of bit error rate and secrecy rate. Copyright © 2018, The Authors. All rights reserved.

关键词： Direction of arrival

Modelling 3D magnetic networks in a realistic solar atmosphere

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arXiv 2019年

作者： Gent, Frederick A. Snow, Ben Fedun, Viktor Erdélyi, Robertus Academy of Finland ReSoLVE Centre of Excellence Department of Computer Science Aalto University FI-02150 Finland College of Engineering Mathematics and Physical Sciences University of Exeter EX4 4QF United Kingdom School of Mathematics Statistics and Physics Newcastle University NE1 7RU United Kingdom School of Mathematics and Statistics University of Sheffield S3 7RH United Kingdom Plasma Dynamics Group Department of Automatic Control and Systems Engineering University of Sheffield S1 3JD United Kingdom Department of Astronomy Eötvös Loránd University Pázmány Péter sétány 1/A Budapest H-1117 Hungary

The magnetic network extending from the photosphere (solar radius ' R) to lower corona (R + 10 Mm) plays an important role in the heating mechanisms of the solar atmosphere. Here we further develop the models with realistic open magnetic flux tubes of the authors in order to model more complicated configurations. Closed magnetic loops, and combinations of closed and open magnetic flux tubes are modelled. These are embedded within a stratified atmosphere, derived from observationally motivated semi-empirical and data-driven models subject to solar gravity and capable of spanning from the photosphere up into the chromosphere and lower corona. Constructing a magnetic field comprising self-similar magnetic flux tubes, an analytic solution for the kinetic pressure and plasma density is derived. Combining flux tubes of opposite polarity it is possible to create a steady background magnetic field configuration modelling a solar atmosphere exhibiting realistic stratification. The result can be applied to SOHO/MDI and SDO/HMI and other magnetograms from the solar surface, upon which photospheric motions can be simulated to explore the mechanism of energy transport. We demonstrate this powerful and versatile method with an application to Helioseismic and Magnetic Imager data. Copyright © 2019, The Authors. All rights reserved.

关键词： 3D modeling

A hybrid systems framework for multi agent task planning and control

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A hybrid systems framework for multi agent task planning and...

American control Conference

作者： Maria Guinaldo Dimos V. Dimarogonas Department of Computer Sciences and Automatic Control School of Computer Engineering UNED Madrid Spain ACCESS Linneaeus Center School of Electrical Engineering KTH Stockholm Sweden

ISBN: (纸本)9781509045839

In this paper, we investigate the coordination of a multi-agent system to achieve a high level plan. In, particular, we assume that this planning is decomposed in a sequence of simple control objectives. The coordination is carried out through event-based communications between the agents, and distributed control laws are synthesized to achieve each control objective according to a time-constraint. All the elements (planning, motion, and communication) are integrated in a hybrid systems framework, which also allows to conclude about the achievement of the high level plan.

关键词： hybrid systems Agents Multi-agent systems Communication Research Planning Standing Orders Frameworks communication between animals Event-based

Exergoeconomics in the sanitary-ware industry to reduce energy and water consumptions

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AIP Conference Proceedings 2019年第1期2190卷

作者： Carlos Cuviella-Suárez Jorge Juan Blanes Peiró David Borge-Diez Antonio Colmenar-Santos 1Department of Electrical Electronic and Control Engineering UNED. Juan del Rosal 12 – University City. 28040 Madrid – Spain 2Department of Electrical and Systems and Automatic Engineering. University of León School of Industrial and Computer Engineering Campus of Vegazana s/n 24071 León Spain

Ceramic sanitary-ware manufacturing is an industrial sector within the ceramic field that globally demands more than 100,000 TJ of primary energy and 21,000 dam3 of water per year. This research aims to quantify the reachable level of improvement within this industrial field by application of thermal engineering through the different thermal processes along the manufacturing line and the way to apply it to recover the water of the process and reduce the total consumption of primary energy. Advanced exergetic analysis has been the selected technique applied to all thermal sub-processes that comprise the overall process. The novelty of this research lays on the application of heat recovery through the different thermal processes to minimize the global consumption of both, energy and water for the specific field of the sanitary-ware manufacturing where no research has been approached in this regard. This research shows that 20% of the inlet exergy in a conventional factory is recoverable and the way to achieve it by an optimized factory which saves 3% of primary energy and 100% of the flushing water for molds.

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Parametric Estimation of Interconnected Nonlinear Systems Described by Input-output Mathematical Models

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International Journal of Automation and computing 2016年第4期13卷 364-381页

作者： Mourad Elloumi Samira Kamoun Laboratory of Sciences and Techniques of Automatic Control & Computer Engineering National Engineering School of Sfax (ENIS) University of Sfax Tunisia B.P. 1173 3038 Sfax Tunisia

In this paper, two types of mathematical models are developed to describe the dynamics of large-scale nonlinear systems, which are composed of several interconnected nonlinear subsystems. Each subsystem can be described by an input-output nonlinear discrete-time mathematical model, with unknown, but constant or slowly time-varying parameters. Then, two recursive estimation methods are used to solve the parametric estimation problem for the considered class of the interconnected nonlinear systems. These methods are based on the recursive least squares techniques and the prediction error method. Convergence analysis is provided using the hyper-stability and positivity method and the differential equation approach. A numerical simulation example of the parametric estimation of a stochastic interconnected nonlinear hydraulic system is treated.

关键词： Large-scale nonlinear systems interconnected nonlinear systems deterministic systems stochastic systems input-outputmathematical models parametric estimation algorithm convergence analysis.

Ananalysis of the SPARSEVA estimate for the finite sample data case

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arXiv 2017年

作者： Ha, Huong Welsh, James S. Rojas, Cristian R. Wahlberg, Bo School of Electrical Engineering and Computer Science University of Newcastle Australia Department of Automatic Control and ACCESS School of Electrical Engineering KTH Royal Institute of Technology StockholmSE-10044

In this paper, we develop an upper bound for the SPARSEVA (SPARSe Estimation based on a VAlidation criterion) estimation error in a general scheme, i.e., when the cost function is strongly convex and the regularized norm is decomposable for a pair of subspaces. We show how this general bound can be applied to a sparse regression problem to obtain an upper bound for the traditional SPARSEVA problem. Numerical results are used to illustrate the effectiveness of the suggested bound. Copyright © 2017, The Authors. All rights reserved.

关键词： Sampling

Computing monotone policies for Markov decision processes: A nearly-isotonic penalty approach

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arXiv 2017年

作者： Mattila, Robert Rojas, Cristian R. Krishnamurthy, Vikram Wahlberg, Bo Department of Automatic Control School of Electrical Engineering KTH Royal Institute of Technology Stockholm Sweden Department of Electrical and Computer Engineering Cornell University Cornell TechNY United States

This paper discusses algorithms for solving Markov decision processes (MDPs) that have monotone optimal *** propose a two-stage alternating convex optimization scheme that can accelerate the search for an optimal policy by exploiting the monotone property. The first stage is a linear program formulated in terms of the joint state-action probabilities. The second stage is a regularized problem formulated in terms of the conditional probabilities of actions given states. The regularization uses techniques from nearly-isotonic regression. While a variety of iterative method can be used in the first formulation of the problem, we show in numerical simulations that, in particular, the alternating method of multipliers (ADMM) can be significantly accelerated using the regularization step. Copyright © 2017, The Authors. All rights reserved.

关键词： Markov processes