Using fuzzy logic: towards intelligent systems
Using fuzzy logic: towards intelligent systems
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
A heuristic particle swarm optimizer for optimization of pin connected structures
Computers and Structures
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Particle swarm optimization based on dynamic niche technology with applications to conceptual design
Advances in Engineering Software
Particle swarm approach for structural design optimization
Computers and Structures
Minimum cost design of a welded orthogonally stiffened cylindrical shell
Computers and Structures
The fully informed particle swarm: simpler, maybe better
IEEE Transactions on Evolutionary Computation
Multi-criteria hybrid PSO algorithm with communications for combinatorial optimisation
Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India
Automatic rule tuning of a fuzzy logic controller using particle swarm optimisation
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part II
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This paper presents a multi-objective fuzzy logic controller (PSO-FLC) for active vibration control of seismically exited buildings by combining a new self configurable multi-objective PSO (particle swarm optimisation) algorithm with fuzzy logic controller. The rule base of the proposed PSO-FLC is tuned for optimal control performance by simultaneously optimizing displacement, drift ratio, acceleration and average control force. In addition, the proposed PSO-FLC algorithm also optimises the number as well as the optimal locations of the actuators. Six and 10 storey framed structures subjected to seismic excitations are considered as numerical examples to demonstrate the superior performance of the PSO-FLC algorithm over other control algorithms.