Closed-loop Identification of an Industrial Extrusion Process

This paper deals with the challenging problem of closed-loop identification for multivariable chemical processes and particularly the estimation of an open-loop plant model for a lab-scale industrial twin-screw extruder used in a powder coatings manufacturing line. The aim is to produce a low order efficient model in order to assist the scaling-up and the model-based control design of the manufacturing process. To achieve this goal, a two-stage indirect approach has been deployed which relies on the a-priori knowledge of the controller parameters in order to extract good estimates of the open-loop dynamics of the underlying process. As input excitation signals we have used multiple single variable step tests at various operating conditions (current industrial practice) carried out manually in order to generate the data-set which captures the dynamics of the extrusion process. In order to increase the efforts for obtaining a suitable plant model, we have employed various identification techniques, such as Prediction Error Methods (PEM) and Subspace Identification Methods (SIM) in order to generate candidate closed-loop models that fit to the original input-output process data. Then, a comparison of the estimated models was performed by means of the mean square error and data fitting criteria in order to select the model that best describes the dynamic behaviour of the extrusion process. Model validation based on closed-loop step responses also used as verification of the results

System identification from closed-loop data with known output feedback dynamics

This paper presents a procedure to identify the open loop systems when it is operating under closed loop conditions. First, closed loop excitation data are used to compute the system open loop and closed loop Markov parameters. The Markov parameters, which are the pulse response samples, are then used to compute a state space representation of the open loop system. Two closed loop configurations are considered in this paper. The closed loop system can have either a linear output feedback controller or a dynamic output feedback controller. Numerical examples are provided to illustrate the proposed closed loop identification method

Optimal realizations of floating-point implemented digital controllers with finite word length considerations.

The closed-loop stability issue of finite word length (FWL) realizations is investigated for digital controllers implemented in floating-point arithmetic. Unlike the existing methods which only address the effect of the mantissa bits in floating-point implementation to the sensitivity of closed-loop stability, the sensitivity of closed-loop stability is analysed with respect to both the mantissa and exponent bits of floating-point implementation. A computationally tractable FWL closed-loop stability measure is then defined, and the method of computing the value of this measure is given. The optimal controller realization problem is posed as searching for a floating-point realization that maximizes the proposed FWL closed-loop stability measure, and a numerical optimization technique is adopted to solve for the resulting optimization problem. Simulation results show that the proposed design procedure yields computationally efficient controller realizations with enhanced FWL closed-loop stability performance

Foreword

In this paper, we show that the consistency of closed-loop subspace identification methods (SIMs) can be achieved through innovation estimation. Based on this analysis, a sufficient condition for the consistency of a new proposed closed-loop SIM is given, A consistent estimate of the Kalman gain under closed-loop conditions is also provided based on the algorithm. A multi-input-multi-output simulation shows that itis consistent under closed-loop conditions, when traditional SIMs fail to provide consistent estimates

On Validating Closed-Loop Behaviour from Noisy Frequency-Response Measurements

It is shown how noisy closed-loop frequency-response measurements can be used to obtain pointwise in frequency bounds on the possible difference between the actual closed-loop system and the closed-loop comprising a nominal model of the plant and the stabilising controller. To this end, Vinnicombe's gap metric framework for robustness analysis plays a central role. Indeed, an optimisation problem and corresponding algorithm are proposed for estimating the chordal distance between the frequency responses of the nominal plant model and a plant that is consistent with the closed-loop data and a priori information, when projected onto the Riemann sphere

Closed-loop approach to thermodynamics

We present the closed loop approach to linear nonequilibrium thermodynamics considering a generic heat engine dissipatively connected to two temperature baths. The system is usually quite generally characterized by two parameters: the output power $P$ and the conversion efficiency $\eta$, to which we add a third one, the working frequency $\omega$. We establish that a detailed understanding of the effects of the dissipative coupling on the energy conversion process, necessitates the knowledge of only two quantities: the system's feedback factor $\beta$ and its open-loop gain $A_{0}$, the product of which, $A_{0}\beta$, characterizes the interplay between the efficiency, the output power and the operating rate of the system. By placing thermodynamics analysis on a higher level of abstraction, the feedback loop approach provides a versatile and economical, hence a very efficient, tool for the study of \emph{any} conversion engine operation for which a feedback factor may be defined