The Experts below are selected from a list of 104856 Experts worldwide ranked by ideXlab platform
Jun Wang - One of the best experts on this subject based on the ideXlab platform.
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a neurodynamic optimization approach to robust pole assignment for synthesizing linear Control Systems based on a convex feasibility problem reformulation
International Conference on Neural Information Processing, 2013Co-Authors: Jun WangAbstract:A neurodynamic optimization approach to robust pole assignment for synthesizing linear Control Systems is presented in this paper. The problem is reformulated from a quasi-convex optimization problem into a convex feasibility problem with the spectral condition number as the robustness measure. Two coupled globally convergent recurrent neural networks are applied for solving the reformulated problem in real time. Robust parametric configuration and exact pole assignment of Feedback Control Systems can be achieved. Simulation results of the proposed neurodynamic approach are reported to demonstrate its effectiveness.
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global exponential stability of recurrent neural networks for synthesizing linear Feedback Control Systems via pole assignment
IEEE Transactions on Neural Networks, 2002Co-Authors: Yunong Zhang, Jun WangAbstract:Global exponential stability is the most desirable stability property of recurrent neural networks. The paper presents new results for recurrent neural networks applied to online computation of Feedback gains of linear time-invariant multivariable Systems via pole assignment. The theoretical analysis focuses on the global exponential stability, convergence rates, and selection of design parameters. The theoretical results are further substantiated by simulation results conducted for synthesizing linear Feedback Control Systems with different specifications and design requirements.
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a multilayer recurrent neural network for real time robust pole assignment in synthesizing output Feedback Control Systems
IFAC Proceedings Volumes, 2002Co-Authors: Jun WangAbstract:Abstract Pole assignment is a basic design method for synthesis of Feedback Control Systems. In this paper, a multilayer recurrent neural network is presented for robust pole assignment in synthesizing output Feedback Control Systems. The proposed recurrent neural network is composed of three layers and is shown to be capable of synthesizing linear output Feedback Control Systems via robust pole assignment in real time. Convergence of the neural network can be guaranteed. Moreover, with appropriate design parameters the neural network converges exponentially to an optimal solution to the robust pole assignment problem and the closed-loop Control system based on the neural network is globally exponentially stable. These desired properties make it possible to apply the proposed recurrent neural network to slowly time-varying linear Control Systems. Simulation results are shown to demonstrate the effectiveness and advantages of the proposed neural network approach.
Zhengzhi Han - One of the best experts on this subject based on the ideXlab platform.
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Robust right coprime factorization and robust stabilization of nonlinear Feedback Control Systems
IEEE Transactions on Automatic Control, 1998Co-Authors: Guanrong Chen, Zhengzhi HanAbstract:Robust right coprime factorization and robust stabilization of nonlinear Feedback Control Systems are studied. The concept of robust right coprime factorization of nonlinear operators for Feedback Control Systems is introduced. Some conditions for the robustness of a right coprime factorization of a nonlinear plant under unknown but bounded perturbations are derived. An example with a closed-form solution is included to illustrate the general theory and a step-by-step construction of the robust factorization and the robust stabilization.
Michael D Lemmon - One of the best experts on this subject based on the ideXlab platform.
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self triggered Feedback Control Systems with finite gain cal l _ 2 stability
IEEE Transactions on Automatic Control, 2009Co-Authors: Xiaofeng Wang, Michael D LemmonAbstract:This paper examines a class of real-time Control Systems in which each Control task triggers its next release based on the value of the last sampled state. Prior work used simulations to demonstrate that self-triggered Control Systems can be remarkably robust to task delay. This paper derives bounds on a task's sampling period and deadline to quantify how robust the Control system's performance will be to variations in these parameters. In particular we establish inequality constraints on a Control task's period and deadline whose satisfaction ensures that the closed-loop system's induced L 2 gain lies below a specified performance threshold. The results apply to linear time-invariant Systems driven by external disturbances whose magnitude is bounded by a linear function of the system state's norm. The plant is regulated by a full-information H infin Controller. These results can serve as the basis for the design of soft real-time Systems that guarantee closed-loop Control system performance at levels traditionally seen in hard real-time Systems.
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event design in event triggered Feedback Control Systems
Conference on Decision and Control, 2008Co-Authors: Xiaofeng Wang, Michael D LemmonAbstract:This paper studies the event design in event-triggered Feedback Systems with asymptotic stability. A new event-triggering scheme is presented that may postpone the occurrence of events over previously proposed methods. Our approach pertains to nonlinear state-Feedback Systems. The resulting event-triggered Feedback Systems are guaranteed to be asymptotically stable, provided that the continuous Systems are stabilizable. We also show that the task periods and deadlines generated by our scheme are bounded strictly away from zero if the continuous Systems are input-to-state stable with respect to measurement errors. Simulation results indicate that our event-triggered scheme has a much larger average period compared with the prior work. Moreover, our scheme also appears to be robust to task delays.
Kuno Kaufmann - One of the best experts on this subject based on the ideXlab platform.
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1 Compaction Monitoring Using Intelligent Soil Compactors
2015Co-Authors: Roland Dr. Anderegg, Dominik A. Von Felten, Kuno KaufmannAbstract:The nonlinear vibrations of dynamic soil compactors are taken as the basis for Feedback Control Systems for intelligent compaction. According to the achieved compaction, the parameters of the soil compactor are continuously changed. The vibratory roller measures permanently the stiffness of the subgrade. In conjunction with GPS-data, this measurement can be used as a QA/QC tool. The stiffness data are directly correlated to plate bearing test. In practice, the intelligent compaction ensures that the compaction job is completed in a minimum number of passes, the result is monitored and the compaction energy is automatically adjusted while measuring the soil stiffness
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Compaction Monitoring Using Intelligent Soil Compactors
GeoCongress 2006, 2006Co-Authors: Roland Dr. Anderegg, Dominik A. Von Felten, Kuno KaufmannAbstract:The nonlinear vibrations of dynamic soil compactors are taken as the basis for Feedback Control Systems for intelligent compaction. According to the achieved compaction, the parameters of the soil compactor are continuously changed. The vibratory roller measures the stiffness of the subgrade. In conjunction with GPS-data, this measurement can be used as a QA/QC tool. The stiffness data are directly correlated to plate bearing test. In practice, the intelligent compaction ensures that the compaction job is completed in a minimum number of passes, the result is monitored and the compaction energy is automatically adjusted while measuring the soil stiffness.
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Intelligent Compaction with Vibratory Rollers: Feedback Control Systems in Automatic Compaction and Compaction Control
Transportation Research Record, 2004Co-Authors: Roland Anderegg, Kuno KaufmannAbstract:Dynamic compactors with parameters that adjust automatically to the condition of the subgrade form the basis for intelligent compaction. Dynamic soil compactors create nonlinear vibrations, and the typical characteristics of these vibrations are taken as the basis for the Feedback Control system for intelligent compaction. With the model of the machine and the soil as the starting point, the periodic loss of contact between the drum and the subgrade is postulated to be the main nonlinear effect. This nonlinearity leads to near periodic and subharmonic vibration phenomena, and it can bring about unstable drum dynamics. The machine behavior can be investigated with the help of the chaos theory. Feedback Control Systems for rollers are based on the results from the theory of nonlinear oscillations, and they allow optimal compaction performance thanks to continuous adjustment to the compaction status. Starting with large amplitudes and low frequencies, the automatic Control system ensures a good depth effect....
Hisaya Fujioka - One of the best experts on this subject based on the ideXlab platform.
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constructing a bimodal switched lyapunov function for non uniformly sampled data Feedback Systems
American Control Conference, 2011Co-Authors: Hisaya Fujioka, Toshiharu NakaiAbstract:Stability analysis of non-uniformly sampled-data Feedback Control Systems is considered. An algorithm is proposed based on the property that the exponential stability is implied by the existence of a switched Lyapunov function for the associate discrete-time Systems. In order to reduce the computational complexity, the algorithm is proposed taking account of the dimensions of LMIs to be solved. It is shown that the proposed algorithm constructs a bimodal switched Lyapunov function in a finite step if one exists.
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output regulation for sampled data Feedback Control Systems internal model principle and h 8 servo Controller synthesis invited
Journal of The Chinese Institute of Engineers, 2010Co-Authors: Hisaya Fujioka, Shinji HaraAbstract:Abstract The output regulation problem for sampled‐data Feedback Systems is considered in a general setup. Necessary and sufficient conditions are derived based on the state‐space approach in the lifted domain. The results are applied to synthesis problems for servo Systems based on H 8 Control. The validity is demonstrated by a design example of repetitive Control.
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a discrete time approach to stability analysis of Systems with aperiodic sample and hold devices
IEEE Transactions on Automatic Control, 2009Co-Authors: Hisaya FujiokaAbstract:Motivated by the widespread use of networked and embedded Control Systems, an algorithm for stability analysis is proposed for sampled-data Feedback Control Systems with uncertainly time-varying sampling intervals. The algorithm is based on the robustness of related discrete-time Systems against perturbation caused by the variation of sampling intervals. The validity of the algorithm is demonstrated by numerical examples.
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stability analysis for a class of networked embedded Control Systems a discrete time approach
American Control Conference, 2008Co-Authors: Hisaya FujiokaAbstract:Motivated by the widespread use of networked and embedded Control Systems, an algorithm for stability analysis is proposed for sampled-data Feedback Control Systems with uncertainly time-varying sampling intervals. The algorithm is based on the robustness of discrete-time Systems against perturbation caused by the variation of sampling intervals. The validity of the algorithm is demonstrated by numerical examples.
