Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method ...

This paper presents a methodology for locating sensors in dynamic systems. It aims to maximize Kalman filtering performance by using accuracy as its main performance index. To accomplish this task, both the measurement noise and the observation matrices are manipulated. The method has been applied in two academic case studies and in the Tennessee Eastman Challenge Problem and has shown promisin...

Abstract— In this paper, subspace identification methods are compared regarding their capability to cope with process disturbances occurring in complex plants. The Tennessee Eastman process is considered to be a realistic simulation model of chemical processes. The MOESP, N4SID and ORT methods as well as some of their variants are applied to data gathered from the process while being subject to...

In this article, we use a genetic algorithm to obtain an economically optimal preventive maintenance frequency for different equipment, the parts inventory policy (number and type of spare parts to keep in stock), and labor allocation in process plants. To assess cost, we improved a previously published Monte Carlo simulationbased maintenance model (Nguyen et al. Ind. Eng. Chem. Res. 2008, 47(6...

This paper presents a large-scale application of a new approach to simultaneously design and control chemical processes that does not require dynamic programming and a priori assumptions of the disturbance dynamics. The process closed-loop behavior is represented as a state space uncertain model. The robust models are then used to calculate infinite-time horizon bounds on the process stability,...

A distributed hybrid strategy is outlined for the isolation of faults and disturbances in the Tennessee Eastman Process, which would build on existing structures for distributed control systems, so should be easy to implement, be cheap and be widely applicable. The main emphasis in the paper is on one component of the strategy, a steady state based approach. Results obtained by applying this ap...

In this paper, a cumulative sum based statistical method is used to detect faults in the Tennessee Eastman Process (TEP). The methodology is focused on three particular faults that could not be observed with other fault detection methodologies previously reported. Hotelling’s-T charting based on the cumulative sums of the faults’ relevant variables was successful in detecting these faults, howe...

This paper presents a fault diagnosis procedure based on discriminant analysis and mutual information. In order to obtain good classification performances, a selection of important features is done with a new developed algorithm based on the mutual information between variables. The application of the new fault diagnosis procedure on a benchmark problem, the Tennessee Eastman Process, shows bet...