Showing papers by "Raghunathan Rengaswamy published in 2005"

Control Loop Performance Assessment. 2. Hammerstein Model Approach for Stiction Diagnosis

Abstract: In part 2 of this two-part series, an approach for diagnosis and quantification of stiction using a simple single-parameter model is proposed. The stiction model, in conjunction with an identified process model from routine operating data, is shown to successfully facilitate stiction diagnosis. An optimization approach is used to jointly identify the process model and the stiction parameter. This approach is based on the identification of a Hammerstein model of the system comprising the sticky valve and the process. In this work, a new identification procedure for Hammerstein systems that supports stiction diagnosis is proposed. Industrial and simulation case studies are shown to demonstrate the application of the proposed approach for diagnosing stiction.

Recursive estimation in constrained nonlinear dynamical systems

Abstract: In any modern chemical plant or refinery, process operation and the quality of product depend on the reliability of data used for process monitoring and control. The task of improving the quality of data to be consistent with material and energy balances is called reconciliation. Because chemical processes often operate dynamically in nonlinear regimes, techniques such as extended-Kalman filter (EKF) and nonlinear dynamic data reconciliation (NDDR) have been developed for reconciliation. There are various issues that arise with the use of either of these techniques. EKF cannot handle inequality or equality constraints, whereas the NDDR has high computational cost. Therefore, a more efficient and robust method is required for reconciling process measurements and estimating parameters involved in nonlinear dynamic processes. Two solution techniques are presented: recursive nonlinear dynamic data reconciliation (RNDDR) and a combined predictor–corrector optimization (CPCO) method for efficient state and parameter estimation in nonlinear systems. The proposed approaches combine the efficiency of EKF and the ability of NDDR to handle algebraic inequality and equality constraints. Moreover, the CPCO technique allows deterministic parameter variation, thus relaxing another restriction of EKF where the parameter changes are modeled through a discrete stochastic equation. The proposed techniques are compared against the EKF and the NDDR formulations through simulation studies on a continuous stirred tank reactor and a polymerization reactor. In general, the RNDDR performs as well as the two traditional approaches, whereas the CPCO formulation provides more accurate results than RNDDR at a marginal increase in computational cost. © 2005 American Institute of Chemical Engineers AIChE J, 51: 946–959, 2005

Fault Diagnosis by Qualitative Trend Analysis of the Principal Components

Abstract: Qualitative trend analysis (QTA) is a data-driven semi-quantitative technique that has been used for process monitoring and fault detection and diagnosis (FDD). Though QTA provides quick and accurate diagnosis—the increase in computational complexity of QTA with the increase in the number of sensors used for diagnosis—may prohibit its real-time application for very large-scale plants. In most of the chemical plants, the measurements are highly redundant and this redundancy can be exploited by performing principal component analysis (PCA) on the measured data. In this paper, we present a PCA–QTA technique for fault diagnosis (FD) in large-scale plants. Essentially, QTA is applied on the principal components rather than on the sensor data. The proposed approach is tested on the Tennessee Eastman (TE) process. The reduction in computational complexity in trend-extraction is about 40%. This reduction in computational complexity is expected to increase considerably for larger processes.

Control loop performance assessment. 1. A qualitative approach for stiction diagnosis

Abstract: A spate of industrial surveys over the past decade indicate that only about one-third of industrial controllers provide acceptable performance. Since significant commercial benefits exist in diagnosing and improving the remaining two-thirds of the industrial controllers, the past few years have seen an emergence of control loop performance monitoring techniques using routine operating data. About 20−30% of all control loops oscillate due to valve problems caused by static friction or hysteresis. In the first of this two-part paper, a qualitative pattern recognition approach is described for stiction diagnosis. Stiction in control valves leave distinct qualitative shapes in the controller output (OP) and controlled process variable (PV) data. These shapes can be generally categorized as being square, triangular, and saw-toothed. To classify the patterns that evolve due to stiction, a pattern recognition approach using dynamic time warping (DTW) technique is proposed. The success of our proposed approach is...

Stiction Compensation in Process Control Loops: A Framework for Integrating Stiction Measure and Compensation

Abstract: In this paper, a framework that utilizes a stiction measure for effective stiction compensation in process control valves is proposed for the first time. The performance of a friction compensator termed the “knocker” proposed in the literature is studied. It is observed that the choice of knocker parameters has a significant influence on the performance of the compensator. It is shown that the choice of the knocker parameters can be automated based on the stiction severity exhibited by the loop. We propose the use of a combination of two approaches for estimating stiction severity. Experimental and simulation case studies are used to demonstrate the efficacy of the proposed approach. Results indicate that a reduction of 6−7 times can be obtained for the output variability.

A dynamic spherical agglomerate model for proton exchange membrane fuel cells (PEMFC)

Abstract: There has been growing interest in the modelling of proton exchange membrane fuel cells (PEMFC). While some steady-state models have been proposed, literature is scarce in PEMFC two-phase dynamic models and transient studies. Typical dynamic models for the fuel cell are empirical current-voltage dynamic models. The internal transients associated with reactant and product species and other components are usually neglected. Further, systems engineering studies such as process control, dynamic optimization, identification of faults and other operational problems in fuel cell studies are missing to a large extent. A detailed dynamic model for spherical agglomerate in a PEMFC is presented in this work. The dynamic model will include detailed mathematical equations for O2 and H+ ions. The model will be unique from the earlier proposed models, as it will include not only the dynamics, but also detailed mathematical equations for transport and electrochemical kinetics. Preliminary results using the dynamic model of spherical agglomerate are presented in this paper.