In this paper, a heuristic solution is suggested to tune a bounded amplitude multisine control signal in a closed-loop setup. The solution consists in the combination of two algorithms: (i) a first one that minimizes ...
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In this paper, a heuristic solution is suggested to tune a bounded amplitude multisine control signal in a closed-loop setup. The solution consists in the combination of two algorithms: (i) a first one that minimizes the Crest Factor of the control signal and (ii) a second one to shape the spectrum of the control signal so that it converges to a desired signal via the tuning of the reference spectrum. Considering a flexible motor-to-joint mechanical transmission, an illustrative example based on simulated data shows that the suggested solution allows to avoid nonlinear distortions created by the control signal bounds, thus improving the estimation of the frequency response function.
This paper presents a novel approach for closed-loop identification of continuous-time systems. The method is based on the projection of measured signals onto a finite-dimensional signal subspace, which results in inh...
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This paper presents a novel approach for closed-loop identification of continuous-time systems. The method is based on the projection of measured signals onto a finite-dimensional signal subspace, which results in inherent robustness against measurement noise and capability for various structures for LTI models. The proposed method enables us to handle indirect closed-loop configurations as well as open-loop ones without any special manipulation. The effectiveness of the method is demonstrated through a numerical example for non-minimum phase and unstable plants in closed-loop.
Asymptotic variance expressions are analysed for models that are identified on the basis of closed-loop data. The considered methods comprise the classical ’direct’ and ’indirect’ method, as well as the more recen...
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Asymptotic variance expressions are analysed for models that are identified on the basis of closed-loop data. The considered methods comprise the classical ’direct’ and ’indirect’ method, as well as the more recently developed indirect methods, employing coprime factorized models and model parametrizations based on the dual Youla/Kucera parametrization. The variance expressions are compared with the open-loop situation, and evaluated in terms of their relevance for subsequent model-based control design. Additionally it is specified what is the optimal experimental situation in identification (open-loop or closed-loop), in view of the variance of the resulting model-based controller.
This paper presents a new closed-loop identification method for first-order and second-order plus-dead-time models, using first-order Padé approximation. In this method, the influence of the“ zero “ relative to...
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This paper presents a new closed-loop identification method for first-order and second-order plus-dead-time models, using first-order Padé approximation. In this method, the influence of the“ zero “ relative to the Padé approximation is considered in the temporal parameters transient behavior. Simulation results are presented, showing the method performance for some kinds of systems. An experimental platform with a heat sink bar was used to apply this identification method.
During the operation of a power plant, open-loop experiments are prohibited and this results in great difficulties for proportional-integral (PI) controller optimization. To overcome this question, a practical closed-...
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During the operation of a power plant, open-loop experiments are prohibited and this results in great difficulties for proportional-integral (PI) controller optimization. To overcome this question, a practical closed-loop identification method with feedforward control is proposed in this paper. The theoretical analyses and the implementations are carried out based on closed-loop data, and simulation results have validated the effectiveness of the proposed method. Finally, the identified system built by the proposed method is applied to the control optimization for a low-pressure heater in a 330MW power plant. Based on the identified system, the PI parameters are retuned and optimized, and the field running data validate the obvious improvement of the disturbance rejection performance. The successful application shows a promising future of the proposed closed-loop identification in practical industrial processes.
The identification of dynamical systems on the basis of data, measured under closed-loop experimental conditions, is a problem which is highly relevant in many (industrial) applications. When using models as a basis f...
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The identification of dynamical systems on the basis of data, measured under closed-loop experimental conditions, is a problem which is highly relevant in many (industrial) applications. When using models as a basis for model-based robust control design both nominal models and model uncertainty bounds are required. In this paper it is shown how -in particular- model uncertainty bounds can be obtained from closed-loop experimental data in the classical prediction error identification framework. The considered uncertainty structure is adjusted so as to allow direct evaluation of the performance robustness of both the actual and a to-be-designed controller.
The direct closed-loop identification algorithm based on cyclic spectral is considered in frequency domain in this paper. It is illustrated that the input and output signals obtained through inter-sampling technique h...
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The direct closed-loop identification algorithm based on cyclic spectral is considered in frequency domain in this paper. It is illustrated that the input and output signals obtained through inter-sampling technique have cyclic spectral, and the cyclic spectral contain plant model information, then the plant model can be estimated just from the cyclic spectral of the plant input and output signals. It is clarified that the test signal is not necessary, and the new algorithm does not depend on the controller structure. The effectiveness of the proposed algorithm is also demonstrated through several numerical examples.
This paper presents a new approach to input design for closed-loop identification. The idea is to maximize the trace of the Fisher information matrix associated with the plant model, while enforcing explicit constrain...
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This paper presents a new approach to input design for closed-loop identification. The idea is to maximize the trace of the Fisher information matrix associated with the plant model, while enforcing explicit constraints on both inputs and outputs. The result is the richest possible excitation signal for which the operation of a running closed-loop system remains within acceptable bounds. The function to be maximized is a convex quadratic. A Moving Horizon Predictive (MHP) framework is used to solve the input design problem at each sample time. The method can be combined with a fixed model variable regressor technique to estimate time delays. The suggested technique is implemented and used to identify machine-directional processes in an industrial paper machine.
An analysis of the variance of the parameters of a multi-input plant estimated in closed-loop operation is performed. More specifically, the effect of the simultaneous excitation of an additional input on the variance...
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An analysis of the variance of the parameters of a multi-input plant estimated in closed-loop operation is performed. More specifically, the effect of the simultaneous excitation of an additional input on the variance of the estimated parameters is investigated. The resulting expressions are valid for all conventional Prediction Error Models (PEM). It is shown that, regardless of the parametrization, the presence of an additional reference signal never impairs and, in most cases, improves the accuracy of the parameter estimates. The analytical results are illustrated by two simulation examples.
A class of identification algorithms for the closed-loop identification problem is discussed based on the output inter-sampling scheme. It is illustrated that the inter-sampled linear plant has a special single-input ...
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A class of identification algorithms for the closed-loop identification problem is discussed based on the output inter-sampling scheme. It is illustrated that the inter-sampled linear plant has a special single-input multiple-output model structure with common control input, and the inter-sampled output has cyclostationary property. Thus it can be clarified that the identifiability of the algorithm can be guaranteed by the multiple model structure in the time domain, and the cyclostationary property can be used to eliminate the correlation between the plant input and output noise in the frequency domain even though no persistently exciting reference signal is available. Some simulation and experiment results demonstrate the effectiveness of the proposed algorithms.
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