System identification: theory for the user
System identification: theory for the user
System identification
Fractional-order system identification based on continuous order-distributions
Signal Processing - Special issue: Fractional signal processing and applications
Fractional system identification for lead acid battery state of charge estimation
Signal Processing - Fractional calculus applications in signals and systems
Adaptive particle swarm optimization: detection and response to dynamic systems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Multiobjective optimization using dynamic neighborhood particle swarm optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Design of fractional-order PIλDµ controllers with an improved differential evolution
Engineering Applications of Artificial Intelligence
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
The fully informed particle swarm: simpler, maybe better
IEEE Transactions on Evolutionary Computation
On the computation of all global minimizers through particle swarm optimization
IEEE Transactions on Evolutionary Computation
A Cooperative approach to particle swarm optimization
IEEE Transactions on Evolutionary Computation
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This contribution proposes a simple yet elegant scheme for identifying a fractional-order dynamic system based on its observed response to a standard excitation. If the fractional powers in the transfer function are precisely known, a set of simultaneous linear equations connecting the unknown coefficient values is obtained and then solved deterministically to yield the desired estimates. In case the fractional powers are uncertain, these are estimated by formulating an optimisation problem and employing a stochastic search algorithm. Results show that the proposed method offers a high degree of accuracy even for data that are intentionally corrupted to simulate real-life conditions.