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Bastin, G. and Dochain, D. (1990) On-line Estimation and Adaptive
On-line Estimation and Adaptive Control of Bioreactors (Process Measurement and Control)
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On-line Estimation and Adaptive Control of Bioreactors, by G. Bastin
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On-line Estimation and Adaptive Control of Bioreactors : G
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Online estimation and adaptive control of penicillin fermentation
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A nonlinear predictive controller for induction motor drive, an on-line estimation of rotor time-constant and a load torque are proposed. The new controller is designed using a combination of two approaches which are indirect field oriented and continuous time minimum variance (ctmv) controls. The on-line estimation of rotor time-constant is based on the mathematical model of induction machine.
Adaptive control is the control method used by a controller which must adapt to a controlled system with parameters which vary, or are initially uncertain. For example, as an aircraft flies, its mass will slowly decrease as a result of fuel consumption; a control law is needed that adapts itself to such changing conditions.
The development of mixture de- signs and retention mapping and their general application to opti- misation problems.
Buy on-line estimation and adaptive control of bioreactors (process measurement and control book 1): read books reviews - amazon.
Bastin, 9780444884305, available at book depository with free delivery worldwide.
The paper describes an investigation into the application of state estimation and adaptive control to fed-batch fermentation for penicillin production. The work forms part of an industrial collaborative project, the aim of which is the optimising control of large fed-batch fermenters.
This thesis presents a new estimation-based synthesis and analysis procedure for adaptive \filtered lms problems. This new approach formulates the adaptive lter-ing (control) problem as an h1 estimation problem, and updates the adaptive weight vector according to the state estimates provided by an h1 estimator.
Opportunity for real-time online estimation of aerodynamic stability and control derivatives for use in adaptive control.
Aiaa guidance, navigation, and control conference and exhibit.
On-line, closed loop estimation scheme, for time-varying parameters is proposed in order to obtain useful information despite loads, external disturbances and faults detection. An adaptive gain, smooth sliding observer- controller is developed to control uncertain parameters, n -degree of freedom (n -dof), rigid links-rigid joints robotic manipulators.
Adaptive queue length estimation has been in consideration only because the pre-timed control systems, those using historical data, become inefficient when the flow of traffic is much less than the intersection.
(1990) on-line estimation and adaptive control of bioreactors.
Catalog description: methods of parameter estimation and adaptive control for isbn 9780134391007 (required) (comment: free on-line text available.
Abstract: this paper deals with a multivariable adaptive predictive control scheme via on-line estimation of the specific reaction rates of a multistage bioreactor.
An important part of most adaptive control schemes is the on-line parameter identi er or adaptive law, which generates esti-mates of the unknown parameters to be used for calculating orupdating the controller parameters in real-time. The way the adaptive law is combined with the control law gives rise to di erent adaptive control structures.
An adaptive control system can thus be regarded as a control system with on-line parameter estimation. Research in adaptive control started in the early 1950's in connection with the design of autopilots for high-performance aircraft, which operate at a wide range of speeds and altitudes and thus experience large parameter variations.
Mathworks engineers will introduce new capabilities for online parameter estimation and will explain and demonstrate how these capabilities can be used for fault detection and adaptive control. The webinar will begin with an overview of recently developed online parameter estimation algorithms.
Download on line estimation and adaptive control of bioreactors books, this book deals with monitoring and control of biotechnological processes. Different methods are proposed which are based on the nonlinear structure of the process and do not require any a priori knowledge of the fermentation parameters.
On-line estimation and adaptive control of bioreactors volume 1 of contributions to economic analysis volume 1 of process measurement and control, issn 1572-5979: authors: georges bastin, denis dochain: editors: georges bastin, denis dochain: publisher: elsevier, 1990: original from: the university of michigan: digitized: dec 17, 2007: isbn.
The –eld of adaptive control with on-line recursive parameter estimation has received considerable attention in the past three decades. The ease of implementation of on-line parameter estimation algorithms developed over the years has made adaptive model based control a competent al-ternative to nonlinear process control.
This paper presents an adaptive control strategy for an upper-limb exoskeleton based on an on-line dynamic parameter estimator. The objective is to improve the control performance of this system that plays a critical role in assisting patients for shoulder, elbow and wrist joint movements.
The faults that are considered are significant uncertainties affecting the control variables of the process and their estimates are used in an adaptive control.
Parameter identification schemes are the backbones of adaptive control systems used to estimate the unknown parameters on line.
Adaptive controller is a dynamic system with on-line parameter estimation.
The foundation of adaptive control is parameter estimation, which is a branch of system identification.
• “adaptive control” techniques provide a systematic approach for automatic on-line tuning of controller parameters • “adaptive control” techniques can be viewed as approximations of some nonlinear stochastic control problems (not solvable in practice) • objective of “adaptive control” to achieve and to maintain.
This paper focuses on the benefits of adaptive control for permanent-magnet synchronous machines; a novel method of online parameter estimation for such machines has been developed. Two recursive least square algorithm segments, a fast and a slow one, are uniquely combined in real time with rich enough data from the machine to estimate all four machine parameters instead of a subset of these.
Neural network is used to estimate the thickness of a workpiece. The developed based on the detection of spark locations on-line, an adaptive control system.
On recent works in online linear estimation and adaptive control design, the latter of which we survey next.
First, an adaptive control structure based on the nonlinear model of the process is designed as a combination of a linearizing control law and of a parameter estimator, used for the on-line estimation of bioprocess unknown kinetics.
One approach to tracking the effect of different tools is adaptive modeling and control. The basic premise of an adaptive system is to change or adapt the controller as the operating conditions of the system change. Using closed-loop data, the adaptive control algorithm estimates the controller parameters using a recursive estimation technique.
The area of adaptive control has grown to be one of the richest in terms of algorithms, design techniques, analytical tools, and modiflcations. Several books and research monographs already exist on the topics of parameter estimation and adaptive control. Despite this rich literature, the fleld of adaptive control may easily appear.
The paper describes an investigation into the application of state estimation and adaptive control to fed-batch fermentation for penicillin production. The work forms part of an industrial collaborative project, the aim of which is the optimising control of large fed-batch fermenters. Estimates of biomass are made using an extended kalman filter from on-line measurements of carbon dioxide.
Adaptive control techniques can provide an automatic tuning note that on-line estimation of plant model parameters is itself an adaptive sys-.
Secondly, the proposed controller assures the stability of the adaptive repetitive control system. The proposed controller is obtained by solving a simple linear programming problem. Thirdly, a simple period identification algorithm is proposed to estimate the multiple periods.
On-line model estimation and adaptive control have been considered extensively for rigid robots. Much of this work exploits the fact that the kinematic and dynamic equations of rigid manipulators are linear in terms of the link parameters, which is not generally the case for continuum robots.
Firstly, an indirect adaptive control structure based on the nonlinear process model is this estimator is used for on-line estimation of the bioprocess unknown.
The hybrid adaptive control includes an indirect adaptive law that performs an on-line estimation of plant dynamics of the damaged aircraft. The stability of this indirect adaptive law is established by the lyapunov stability theory.
In fact, when one writes down the dynamics of stochastic gradient descent (sgd), the control gain update law in adaptive control, or the map parameter estimate in regression (bayesian or otherwise), the three sets of equations are basically identical in structure.
In order to deal with process nonstationarities and parameter uncertainties, reference is made to adaptive estimation and control techniques. The book is the result of an intensive joint research effort by the authors during the last decade.
A popular scheme for adaptive control is the so-called “self-tuning ” control wherein a parameterized family of system models is presupposed and the parameter is estimated “on-line”. One then uses at each time instant that control which would have been the optimal choice for the current value of the system state if the current parameter.
Save up to 80% by choosing the etextbook option for isbn: 9781483290980, 1483290980. The print version of this textbook is isbn: 9780444884305, 0444884300.
That an inaccurate estimate of the magnetic eld introduces parametric perturbations in the closed loop system. There-fore, the model parameters need to be estimated accurately for the emk controller to work. An adaptive observer that can estimate system parameters on-line and reduce.
An adaptive control system integrates the controller design with on-line recursive parameter estimation (system identification).
An adaptive controller is formed by combining an on-line parameter estima- tor, which provides estimates of unknown parameters at each instant, with a control.
Thus, the indirect adaptive controller estimates model parameters, stabilizes the wire in the unstable region and can be switched into a non-adaptive mode for applications. Recommended citation karve, harshwardhan, online parameter estimation and adaptive control of magnetic wire actuators (2016).
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