A Tabu Search Procedure For
Sensor Structure Optimisation
Author(s)
M. Carnero, J. Hernández & M. Sánchez
Abstract
This paper presents a meta-heuristic approach for the optimal location of sensors
in chemical plants. Within the Tabu Search framework, a Strategic Oscillation
Technique around the feasibility boundary is implemented that provides an
effective balance between intensification and diversification over the
intermediate to long term of the search. The procedure is applied to minimize the
instrumentation network cost subject to precision and availability constraints on
variable estimates for linear processes. Its performance is compared to other
evolutionary techniques for two case studies. Results show the algorithm
succeeds in locating the optima using lower computation time.
Keywords: sensor network design, stochastic optimisation, tabu search.
1 Introduction
A reliable and complete knowledge of current plant state is essential for plant
monitoring, regulatory and supervisory control, real time optimisation, planning
and scheduling, etc. The quality and availability of variable estimates strongly
depend on the sensor network installed in the process.
The design of sensor networks consists in selecting the type, number,
accuracy, failure rate, and location of new sensors that provide the quantity and
quality of information required from the process. Frequently it is necessary to
satisfy constraints only on a subset of key measured or unmeasured variable
estimates. In this case a general sensor network is designed without knowing in
advance the cardinality of the optimal sensor set. As only a subset of variables
Keywords
sensor network design, stochastic optimisation, tabu search.
Related Book
Other papers in this volume
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