Control Design Using Nonlinear Reduced Models
Reduced-order model design for nonlinear smart system models
... discretize nonlinear smart material system models can yield full-order numerical models that accurately characterize the system dynamics but do so at significant computational ...full-order ...
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Identification and Control of Nonlinear Systems using Multiple Models
... the control signal is computed in a similar way as weighted one-step- ahead predictive control, by relying on the piecewise affine ...in control, and thus the control signal is evaluated ...
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Identification and estimation of nonlinear regression models using control functions
... A reduced version of an earnings equation is esti- mated and it is found that the estimator differs substantially from other estimators obtained for comparison ...
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Closed-loop control of an open cavity flow using reduced-order models
... The eigenvalues of the reduced-order model based on BPOD modes The ability of reduced-order models based on BPOD modes to capture the input– output behaviour, as demonstrated above by co[r] ...
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Feedback Control for Systems with Uncertain Parameters Using Online-Adaptive Reduced Models
... in control, numerical linear algebra, and model learn- ...based control altogether, or estimate system models from ...and control methods opens new pathways for designing efficient ...the ...
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Nonlinear Backstepping Control Design using a High Gain Observer for Automatic Gauge Control
... In practice, the technique used to measure the thickness deviations corresponds to the installation of the X-ray sensor located after the roll stand, which causes a delay in the reaction system and causes a significant ...
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Potentials of Evolving Linear Models in Tracking Control Design for Nonlinear Variable Structure Systems
... neuro-fuzzy models have been developed in modeling nonlinearity and time-varying ...a nonlinear evolving model often can be described as an interpolated of locally linear models constructed from ...
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Nonlinear Observer-Based Tracking Control Using Piecewise Multi-Linear Models
... The controller is based on feedback and observer linearizations. The piecewise model is a nonlinear approximation and fully parametric. Feedback linearization is an effective method to stabilize nonlinear ...
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Control-Relevant System Identification using Nonlinear Volterra and Volterra-Laguerre Models
... Volterra models, the primary area of emphasis has been on the identification of second-order ...these models display a multiplicity behavior, ...linear, nonlinear diagonal, and third-order ...
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Nonlinear Model Predictive Control of Hammerstein and Wiener Models Using Genetic Algorithms
... Predictive Control or MPC can provide robust control for processes with variable gain and dynam- ics, multivariable interaction, measured loads and unmea- sured ...of Nonlinear MPC is proposed ...
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Iterated Nonlinear Control of Ship's Manoeuvring Models
... inherent nonlinear characteristics of the system 0 s behaviour, providing the grounds for a robust control implementation where modelling uncertainties are ...DOF nonlinear manoeuvring ship ...
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Optimal design for additive partially nonlinear models
... of using optimal designs through an application to our motivating example on engine ...been reduced considerably, so it is more likely that they will be adopted in industry and generate ...
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On the Implementation of Nonlinear Model Predictive Control for Simultaneous Design and Control Using a Back-Off Approach
... simultaneous design and control methodology based on a back-off ...and control from the optimal steady-state design using bounded optimization problems that are constructed based on PSE ...
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Sound design for nonlinear artefacts: models for sound design in the transformation between linear and nonlinear artefacts.
... main nonlinear game ...the nonlinear construction, most games incorporate a ‘nonlinear music ...with using linear cinematic music in games is that it often evokes the wrong ...
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Reduced Order Framework for Optimal Control of Nonlinear Partial Differential Equations
... Chapter 1 Introduction Partial differential equations is one of the most diverse and ubiquitous fields of both pure and applied mathematics. A partial differential equation (PDE) is an equation involving an unknown ...
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A nonlinear optimal control design using narrowband perturbation feedback for magnetostrictive actuators
... narrowband control design utilizes optimal control theory to obtain a feedback control design of an augmented plant that includes a number of narrowband harmonics at specified ...
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Nonlinear identification and control of Organic Rankine Cycle systems using sparse polynomial models
... to design a controller using current available ...a nonlinear polynomial ...the nonlinear Extended Prediction Self-Adaptive control (NEPSAC) approach to Non- linear Model Predictive ...
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Reduced order modelling of parameter dependent linear and nonlinear dynamic PDE models
... methods. Using m = 10 snapshots, the decrease in the relative errors r in kGPE-POD is negligible for r > 15, while the global basis method continues to improve beyond r = ...
24
Reduced order modelling of parameter dependent linear and nonlinear dynamic PDE models
... methods. Using m = 10 snapshots, the decrease in the relative errors r in kGPE-POD is negligible for r > 15, while the global basis method continues to improve beyond r = ...
24
Simulation and control techniques for nonlinear rational expectation models
... the models are typically estimated by single-equation techniques, and in practice the estimation periods of these individual equations may not ...empirical models of the UK economy all contain a number of ...
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