Showing papers by "Raghunathan Rengaswamy published in 2008"
TL;DR: Two novel approaches for stiction compensation are proposed: a simple two-move approach and an optimization based approach much in the spirit of predictive control strategies based on a data-driven model for stictions.
82 citations
TL;DR: A novel diagonal nonlinear residual feedback observer is proposed which is valid for a certain class of nonlinear systems where, subject to other conditions, the state depends nonlinearly on the fault.
74 citations
TL;DR: Robustness enhancing criteria for the design of sensor networks for reliable fault diagnosis are presented and incorporated in a lexicographic manner along with the overall reliability-maximization and cost-minimization objectives in a single optimization problem.
60 citations
11 Jun 2008
TL;DR: This contribution presents the use of two well known techniques of multi-objective optimization to solve for a plant friendly input design where the plant friendly objective is to keep input move sizes low.
Abstract: In optimal input design problems, the designer seeks to solve for maximally informative inputs to be used as perturbation signals in system identification experiments. Plant- friendly identification experiments are those that satisfy plant or operator constraints on experiment time, input and output amplitudes or input move sizes. These have been reported to be in direct conflict with requirements for good identification. Hence plant-friendly input design is inherently multi-objective in nature. In this contribution, we present the use of two well known techniques of multi-objective optimization to solve for a plant friendly input design where the plant friendly objective is to keep input move sizes low. We relax the constraint on the input move sizes by constraining the variance of the move size instead. Both techniques result in convex optimization problems which can be solved efficiently using powerful algorithms.
11 citations
11 Jun 2008
TL;DR: In this paper, possible approaches to detect stiction in nonlinear process control loops are discussed.
Abstract: Stiction in control loops lead to oscillations and loss of productivity. Timely detection of stiction in control valves can be used in scheduling valve maintenance and deployment of compensation techniques to reduce their impact. Several approaches have been proposed for detection of stiction. Data-based approaches use unique shapes of the PV and OP data to identify stiction. Approaches based on nonlinearity detection have also been used to identify stiction. Yet another approach uses a Hammerstein model structure identification for detecting stiction. Most of these approaches are restricted to linear processes. In this paper, possible approaches to detect stiction in nonlinear process control loops are discussed.
7 citations
11 Jun 2008
TL;DR: It is shown through experiments on industrial valves that in the presence of static and dynamic friction, the valve behavior is dependent on the rate of the valve input.
Abstract: Stiction has been reported as the most commonly occurring nonlinearity in control valves. In the literature, mechanistic and data based models have been proposed to characterize stiction. In this paper, the available models are critically analyzed. The complexities associated with modeling stiction are highlighted. It is shown through experiments on industrial valves that in the presence of static and dynamic friction, the valve behavior is dependent on the rate of the valve input. An approach to model this rate dependent valve behavior - which is not considered in existing data driven models - is proposed.
6 citations