This paper presents experimental results obtained in temperature adaptivecontrol of a heating vessel. A non-linear model of the process showed that the feed flow rare causes severe variations in time constant and pro...
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This paper presents experimental results obtained in temperature adaptivecontrol of a heating vessel. A non-linear model of the process showed that the feed flow rare causes severe variations in time constant and process gain. An extended horizon self-tuning controller and two different model reference adaptive controllers were tested. The influence of design parameters on control performance for each algorithm was assessed. The control system was disturbed with load and setpoint changes.
The control of a pH process using neural networks is examined. The neural network as a universal approximator is used to good effect in this nonlinear problem, as is shown in the simulation results. In the modelling t...
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The control of a pH process using neural networks is examined. The neural network as a universal approximator is used to good effect in this nonlinear problem, as is shown in the simulation results. In the modelling task, the dynamics of the process was carefully examined to determine a suitable structure for the net. In particular, a multilayer net consisting of two single hidden layers was constructed to reflect the Wiener model of the pH process. This led to much simpler training compared to similar modelling attempts by other researchers. For the control task, two schemes were simulated. In one approach, a net was used to deal with the static nonlinearity to achieve control over a wide working range. The dynamic controller used was the PID, with its parameters tuned on a relay auto-tuner. This control design was compared with the strong acid equivalent method. In the second approach, a direct modelreferenceadaptive neural network control scheme was proposed. The training procedure uses the more efficient least squares algorithm developed by Loh and Fong.
The technique most commonly used now for the control of induction motor drives is known as Field Oriented control or Vector control. The direct implementation of the field-oriented control technique requires the deter...
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The technique most commonly used now for the control of induction motor drives is known as Field Oriented control or Vector control. The direct implementation of the field-oriented control technique requires the determination of the rotor flux components;these latter are generally obtained by a state observer, The availability of an observer, characterized by a reduced sensitivity to the parametric variations, has aroused interest in using more-sophisticated control strategies as well. The paper proposes an adaptivecontrol technique that, besides ensuring perfect tracking of the model, makes it possible to estimate the drive parameters that present the largest variations. To this end, an exact linearization of the machine model by a nonlinear feedback is performed and the linearized model is employed as referencemodel.
A state feedback dynamic controller is constructed to achieve asymptotic tracking and disturbance rejection for a class of nonlinear systems regardless of certain plant uncertainties, This controller is based on kth-o...
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A state feedback dynamic controller is constructed to achieve asymptotic tracking and disturbance rejection for a class of nonlinear systems regardless of certain plant uncertainties, This controller is based on kth-order robust control law introduced in [1] and features what is called the internal model principle in the linear literature, The result extends the robust linear servomechanism theory to the nonlinear setting.
The principal aim of this paper is to present a new algorithm for the control of continuous time linear systems with a large relative degree and unknown parameters. If the standard approach is used for these systems, ...
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The principal aim of this paper is to present a new algorithm for the control of continuous time linear systems with a large relative degree and unknown parameters. If the standard approach is used for these systems, the controller structure is very complicated and implementation is problematic. A comparative study of two classes of model reference adaptive control methods is also presented. Finally, simulation results are also presented to illustrate the effectiveness of the proposed method.
In a major breakthrough, Guo and Chen [1] have recently shown how to establish the self-optimality and mean square stability of a self-tuning regulator. The ideas there allow us to proceed with the development of a mo...
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In a major breakthrough, Guo and Chen [1] have recently shown how to establish the self-optimality and mean square stability of a self-tuning regulator. The ideas there allow us to proceed with the development of a more comprehensive theory of stochastic adaptive filtering, control and identification. In adaptive filtering, we examine both indirect and noninterlaced direct schemes for prediction, using both least-squares and gradient parameter estimation algorithms. In addition to analyzing similar direct adaptivecontrol algorithms, we propose new generalized certainty equivalence adaptivemodelreferencecontrol laws with simultaneous disturbance rejection. We also establish that the parameters converge to the null space of a certain matrix. From this one may deduce the convergence of several adaptivecontrollers.
In this paper an adaptive way of mainsteam temperature control is proposed for a thermal power plant at the ramping stage. A physical model of the super-heater system is built up based on the experimental knowledge on...
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In this paper an adaptive way of mainsteam temperature control is proposed for a thermal power plant at the ramping stage. A physical model of the super-heater system is built up based on the experimental knowledge on actual thermal power plants. The model yields a continuous time nonlinear system with several unknown varying parameters. A quick identification method is Introduced to estimate online the model parameters. The identified model is used for designing a control signal to raise the mainsteam temperature at the outlet of the super- heater along a reference curve. In this way, an adaptivecontrol of thermal power plant can be realized in the framework of MRACS. The effectiveness of the method has been confirmed through simulation studies.
This paper looks at the application of encoderless vector control in medium performance induction motor drives. In recent publications some attention has been given to methods which utilize adaptive flux observers to ...
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This paper looks at the application of encoderless vector control in medium performance induction motor drives. In recent publications some attention has been given to methods which utilize adaptive flux observers to identify rotor speed. This paper evaluates some of these techniques with particular focus on their application in a single processor drive. The authors discuss three MRAC (model reference adaptive control) speed estimation techniques: rotor flux MRAC, MRAC using counter EMF, and MRAC using reactive power.< >
Flux oriented control systems of induction machines are sensitive to the variation of the machine parameters such as rotor time constant and stator resistance. Speed estimation has been proposed by many papers however...
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Flux oriented control systems of induction machines are sensitive to the variation of the machine parameters such as rotor time constant and stator resistance. Speed estimation has been proposed by many papers however they depend on the variation in rotor time constant and stator resistance. A system that has speed estimation and is also independent of rotor time constant and stator resistance is desirable. This paper adapted the methods proposed by G. Yang and T. Chin (1989) and K. Tungpimolrut (1994) and investigates and extends these strategies in rotor flux oriented control. The authors discuss the rotor flux observer and the reactive power modelreferenceadaptive system.< >
Based on a simplified model reference adaptive control(SMRAC) algorithm a parameter modification algorithm according to fuzzy laws is proposed in this paper. The method makes the adaptive parameters in SMRAC only rely...
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Based on a simplified model reference adaptive control(SMRAC) algorithm a parameter modification algorithm according to fuzzy laws is proposed in this paper. The method makes the adaptive parameters in SMRAC only rely on the status of performance error. Thus it eliminates the influences of gain coefficients in SMRAC and the amplitude of input signal on the dynamic characteristics. Experiments on various step amplitudes and loads show that the performances of SMRAC are improved by incorporating fuzzy modification method.
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