Search results for "nonlinear control"

showing 10 items of 28 documents

Adaptive Neural Control of MIMO Nonstrict-Feedback Nonlinear Systems with Time Delay

2016

In this paper, an adaptive neural output-feedback tracking controller is designed for a class of multiple-input and multiple-output nonstrict-feedback nonlinear systems with time delay. The system coefficient and uncertain functions of our considered systems are both unknown. By employing neural networks to approximate the unknown function entries, and constructing a new input-driven filter, a backstepping design method of tracking controller is developed for the systems under consideration. The proposed controller can guarantee that all the signals in the closed-loop systems are ultimately bounded, and the time-varying target signal can be tracked within a small error as well. The main con…

0209 industrial biotechnologyComputer scienceMIMOAdaptive trackingoutput-feedback controller02 engineering and technologyNonlinear controlmultiple-input and multiple-output (MIMO)020901 industrial engineering & automationControl theoryAdaptive system0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringArtificial neural networkControl engineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionFilter (signal processing)neural networksComputer Science ApplicationsHuman-Computer InteractionNonlinear systemControl and Systems EngineeringBackstepping020201 artificial intelligence & image processingAdaptive tracking; multiple-input and multiple-output (MIMO); neural networks; output-feedback controller; Control and Systems Engineering; Software; Information Systems; Human-Computer Interaction; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic EngineeringSoftwareInformation Systems
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Motor-skill learning in an insect inspired neuro-computational control system

2017

In nature, insects show impressive adaptation and learning capabilities. The proposed computational model takes inspiration from specific structures of the insect brain: after proposing key hypotheses on the direct involvement of the mushroom bodies (MBs) and on their neural organization, we developed a new architecture for motor learning to be applied in insect-like walking robots. The proposed model is a nonlinear control system based on spiking neurons. MBs are modeled as a nonlinear recurrent spiking neural network (SNN) with novel characteristics, able to memorize time evolutions of key parameters of the neural motor controller, so that existing motor primitives can be improved. The ad…

0301 basic medicineComputer scienceBiomedical Engineeringinsect brainNonlinear controlAdaptation and learning03 medical and health sciences0302 clinical medicineMotor controllerArtificial Intelligenceinsect mushroom bodiesHypothesis and TheoryMotor skillSpiking neural networkHexapodgoal-oriented behaviorControl systemslearningbusiness.industryControl systems; Neural networks; Adaptation and learning030104 developmental biologyControl systemRobotArtificial intelligencespiking neural controllersMotor learningbusiness030217 neurology & neurosurgeryNeural networksNeuroscience
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Analytical-numerical methods for investigation of hidden oscillations in nonlinear control systems

2011

The method of harmonic linearization, numerical methods, and the applied bifurcation the- ory together discover new opportunities for analysis of oscillations of control systems. In the present survey analytical-numerical algorithms for hidden oscillation localization are discussed. Examples of hidden attrac- tor localization in Chua's circuit and counterexamples construction to Aizerman's conjecture and Kalman's conjecture are considered.

Chua's circuitHarmonic balanceNumerical analysisMathematical analysisApplied mathematicsGeneral MedicineKalman filterNonlinear controlHidden oscillationBifurcationCounterexampleMathematicsIFAC Proceedings Volumes
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Relaxation for a Class of Control Systems with Unilateral Constraints

2019

We consider a nonlinear control system involving a maximal monotone map and with a priori feedback. We assume that the control constraint multifunction $U(t,x)$ is nonconvex valued and only lsc in the $x \in \mathbb{R}^{N}$ variable. Using the Q-regularization (in the sense of Cesari) of $U(t,\cdot )$, we introduce a relaxed system. We show that this relaxation process is admissible.

Class (set theory)Partial differential equationApplied Mathematics010102 general mathematicsMaximal monotone mapNonlinear control01 natural sciencesAdmissible relaxation010101 applied mathematicsConstraint (information theory)CombinatoricsMonotone polygonQ-regularizationSettore MAT/05 - Analisi MatematicaControl systemRelaxation (approximation)0101 mathematicsLower semicontinuous multifunctionVariable (mathematics)MathematicsContinuous selection
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Multi-level optimization of a fiber transmission system via nonlinearity management

2006

Nonlinearity management is explored as a complete tool to obtain maximum transmission reach in a WDM fiber transmission system, making it possible to optimize multiple system parameters, including optimal dispersion pre-compensation, with fast simulations based on the continuous-wave approximation. © 2006 Optical Society of America.

Computer sciencePhysics::OpticsPolarization-maintaining optical fiber02 engineering and technology01 natural sciencesGraded-index fiber[PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]010309 optics020210 optoelectronics & photonicsOpticsWavelength-division multiplexing0103 physical sciencesDispersion (optics)0202 electrical engineering electronic engineering information engineeringFiber optic splitterDispersion-shifted fiberSpontaneous emissionPlastic optical fiber[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]Mode volumecomputer simulation; nonlinear control systems; optimizationbusiness.industryComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSSingle-mode optical fiberNonlinear opticsTransmission systemAtomic and Molecular Physics and OpticsFiber-optic communication[ PHYS.PHYS.PHYS-AO-PH ] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]Raman amplifiersTransmission (telecommunications)Fiber optic sensorbusiness
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State Space-Vector Model of Linear Induction Motors including End-Effects and Iron Losses Part I: Theoretical Analysis

2020

This is the first part of the article, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses and its offline identification. This first part specifically treats the theoretical formulation of this model, which has been expressed in a state form, so to be, in perspective, suitably adopted for developing novel nonlinear control techniques, nonlinear observers as well as electrical losses minimization techniques. Besides the formulation of the dynamic model in space-vector state form, a steady-state analysis is proposed, highlighting the combined effects …

Computer sciencestate modelend-effectsNonlinear controlIndustrial and Manufacturing EngineeringMagnetic fluxEnd-effectIdentification (information)Nonlinear systemPerspective (geometry)Settore ING-INF/04 - AutomaticaControl and Systems EngineeringControl theoryLinear induction motorspace vectorState spacelinear induction motor (LIM)MinificationElectrical and Electronic Engineering
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Input-Output Feedback Linearization Control of a Linear Induction Motor Taking Into Consideration Its Dynamic End-Effects and Iron Losses

2020

This article proposes a new input-output feedback linearization control (FLC) technique of linear induction motors (LIMs), taking into consideration both the dynamic end-effects and the iron losses. Starting from a previously conceived dynamic model, including the dynamic end-effects and the iron losses, all the theoretical framework of the FLC has been developed. The proposed FLC improves a previous version of FLC in accounting also the iron losses, which in LIMs with fixed-secondary sheet play a pivotal role more than in rotating induction motors (RIMs). The proposed FLC has been experimentally tested on a suitably developed test setup, and experimental comparisons between the proposed FL…

Dynamic end-effectsEnd effectComputer scienceinput-output feedback linearization control (FLC)05 social sciencesControl (management)020207 software engineering02 engineering and technologyiron lossesIndustrial and Manufacturing EngineeringLinear Induction Motor (LIM) Input-output Feedback Linearization Control (FLC) Dynamic end-effects Iron Losses Space-vector State ModelSettore ING-INF/04 - AutomaticaControl and Systems EngineeringControl theoryLinear induction motor0202 electrical engineering electronic engineering information engineeringlinear induction motor (LIM)0501 psychology and cognitive sciencesFeedback linearizationspace-vector state modelnonlinear controlElectrical and Electronic EngineeringInput output feedback linearization050107 human factors
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Semiactive Control Methodologies for Suspension Control With Magnetorheological Dampers

2012

Authors version of an article published in the journal: IEEE/ASME Transactions on Mechatronics. Also available from the publisher at: http://dx.doi.org/10.1109/TMECH.2011.2107331 Suspension systems are one of the most critical components of transportation vehicles. They are designed to provide comfort to the passengers to protect the chassis and the freight. Suspension systems are normally provided with dampers that mitigate these harmful and uncomfortable vibrations. In this paper, we explore two control methodologies (in time and frequency domain) used to design semiactive controllers for suspension systems that make use of magnetorheological dampers. These dampers are known because of th…

EngineeringChassisbackstepping magnetorheological (MR) damper quantitative feedback control semiactive control suspension controlNonlinear controlsuspension controlDamperQuantitative feedback theoryControl theoryMagnetorheological dampersmagnetorheological (MR) damperAutomòbils -- AmortidorsElectrical and Electronic EngineeringSuspension (vehicle)Amortidors magneto-reològicsquantitative feedback controlsemiactive controlbusiness.industryVDP::Technology: 500::Mechanical engineering: 570Linear systemBackstepping; magnetorheological (MR) damper; quantitative feedback control; semiactive control; suspension control; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic EngineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionControl engineeringComputer Science ApplicationsBacksteppingControl and Systems EngineeringBacksteppingMagnetorheological fluidbusinessIEEE/ASME Transactions on Mechatronics
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NARX Models of an Industrial Power Plant Gas Turbine

2005

This brief reports the experience with the identification of a nonlinear autoregressive with exogenous inputs (NARX) model for the PGT10B1 power plant gas turbine manufactured by General Electric-Nuovo Pignone. Two operating conditions of the turbine are considered: isolated mode and nonisolated mode. The NARX model parameters are estimated iteratively with a Gram-Schmidt procedure, exploiting both forward and stepwise regression. Many indexes have been evaluated and compared in order to perform subset selection in the functional basis set and determine the structure of the nonlinear model. Various input signals (from narrow to broadband) for identification and validation have been consider…

EngineeringNonlinear autoregressive exogenous modelbusiness.industryTurbinesSystem identificationControl engineeringNonlinear controlTurbineDistributed power generationElectric power systemNonlinear systemAutoregressive modelControl and Systems EngineeringSteam turbineControl theoryElectrical and Electronic EngineeringbusinessGas turbines
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Nonlinear control of an activated sludge aeration process: use of fuzzy techniques for tuning PID controllers

1999

In this paper, several tuning algorithms, specifically ITAE, IMC and Cohen and Coon, were applied in order to tune an activated sludge aeration PID controller. Performance results of these controllers were compared by simulation with those obtained by using a nonlinear fuzzy PID controller. In order to design this controller, a trial and error procedure was used to determine, as a function of error at current time and at a previous time, sets of parameters (including controller gain, integral time and derivative time) which achieve satisfactory response of a PID controller actuating over the aeration process. Once these sets of data were obtained, neural networks were used to obtain fuzzy m…

EngineeringSewageArtificial neural networkbusiness.industryApplied MathematicsOpen-loop controllerPID controllerControl engineeringNonlinear controlFuzzy logicComputer Science ApplicationsKineticsNonlinear systemOxygen ConsumptionFuzzy LogicNonlinear DynamicsControl and Systems EngineeringControl theoryProcess controlComputer SimulationBiomassElectrical and Electronic EngineeringbusinessInstrumentationAlgorithmsISA Transactions
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