Title :
Redundant Instruments Placement Using ACO
Author_Institution :
Dept. of Control Eng., Chengdu Univ. of Inf. Technol., Chengdu, China
Abstract :
In this paper, ant colony optimization (ACO) algorithm is introduced to redundant instruments placement for optimum process variable estimation accuracy. It is proved that additional redundancy measurement will enhance estimation accuracy if the measurements relate the process variables in a different way, whereas the quantity of accuracy improvement is determined by the measurements structure. To find the optimal redundant instruments placement is substantially combinatorial optimization problem, ant colony system (ACS) can perform this perfectly. In this paper, ACO based redundant instruments placement algorithm is proposed. Simulation shows the proposed outperform the GA algorithm, which is a prevailing algorithm to combinatorial problem.
Keywords :
combinatorial mathematics; optimisation; ant colony optimization; optimisation algorithm; process variable estimation; redundant instruments placement; Ant colony optimization; Computational intelligence; Control engineering; Cost function; Covariance matrix; Information technology; Instruments; Q measurement; Redundancy; Simulated annealing; ACO; Sensor network; constraint combinatorial problem; data reconciliation; estimation accuracy;
Conference_Titel :
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3645-3
DOI :
10.1109/CINC.2009.170