TA3 Adaptive Control

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Continuous-Time Self-Tuning Controller

Authors:

Bobal V., Brno University of Technology, Czech Republic

Dostal P., Brno University of Technology, Czech Republic

Kolomaznik K., Brno University of Technology, Czech Republic

ABSTRACT

A self – tuning controller algorithm has been derived in this paper. The process is identified by the regression (ARX) continuous – time model using the recursive least squares method (RLSM) with applied directional forgetting. The recursive parameter estimates of the continuous – time model (differential equation) are used to controller synthesis. Controller synthesis is designed on the basis of pole – placement (assignment) method. The algorithm is suitable for the automatic setting of analog controllers for deterministic processes or the adaptive control of stochastic and nonlinear processes without or with time delay. One modification of the controller has been verified by computer simulation.

ta3-1

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Direct adaptive predictive control using subspace identification in Laguerre domain in the presence of constraints

Authors:

Huzmezan M., University of British Columbia, Canada

Dumont A.G. - University of British Columbia, Canada

ABSTRACT

The classic way to control a system, in a model based framework, is to obtain a model of the system and then to use it for the design of a controller. For the class of systems characterized by a large number of inputs and outputs, such as for the cross direction control of a paper machine, we require a reduced computational time to produce the controller parameters. Our solution to this problem is a direct adaptive predictive controller which operates in the Laguerre shift operator domain and replaces the system identification step together with the calculation of the predictive controller parameters (controller that additionally contains input and output constraints) by: 1) a least squares solution, 2) two simple linear algebra operations (QR decomposition and a singular value decomposition) of a matrix constructed from input and output measurements of the unknown system and 3) a quadratic program optimization or another least squares problem. The modeling step is accomplished in a subspace identfication fashion. The resulting algorithm provides major computational savings due to the reduced dimension of the system matrices together with the absence of a specific state space model.

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On the Performance of Multimodel Adaptive Control

Authors:

Karimi A., Sharif University of Technology, Iran

Motee N., Sharif University of Technology, Iran

ABSTRACT

The performance of multimodel adaptive control based on switching and tuning will be studied via several simulation examples for a exible transmission system. The effects of some design parameters like number of fixed and adaptive models and forgetting factor will be considered. The performance of a recently developed parameter adaptation algorithm based on closed loop output error will be compared with the classical least squares prediction error algorithm in the multimodel adaptive control.

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Predictive Transient Control of EGR/VTG for Internal Combustion Engines

Authors:

Hafner M., Darmstadt University of Technology, Germany

ABSTRACT

Modern engine control systems basically use stationary curves and 3D maps in order to control internal combustion (IC) engines. Future legislative emission restrictions, however, will require an additional optimization of the transients between different static operating points. This contribution presents a model based predictive optimization of transient EGR (exhaust gas recirculation) and VTG (Turbocharger with variable turbine geometry) control settings between two operating points. Basic tran-sient functions, which are piecewise linear, are introduced. The parameters of these transient functions are then optimized concerning the emissions-consumption trade-off. The model base is realized by fast neural networks. A DSP-based process computer system allows a fast application of the optimization tool at the engine test stand.

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New Approach of Adaptive Automatic Load Shedding

Authors:

Terzija V., Universitaet des Saarlandes, Germany

Koglin H.-J., Universitaet des Saarlandes, Germany

ABSTRACT

In the paper a new approach of adaptive automatic load shedding, a procedure for protecting electric power systems from dynamic instability and frequency collapse is presented. It is consisted of two main stages. In the first stage the frequency and the rate of its change are estimated by nonrecursive Newton Type Algorithm and Least Error Squares Method. In the second stage the magnitude of disturbance, i.e. the difference between generated and consumed active power is estimated by applying the simplest form of generator swing equation. Results of multimachine test system computer simulations are presented.

ta3-5

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