Case Studies
Identification Examples
Abstract
In this chapter, the learning algorithms proposed in the previous chapters (GD-based, SMC theory-based, EKF and hybrid PSO-based learning algorithms) are used to identify and predict two nonlinear systems, namely Mackey-Glass and a second-order nonlinear time-varying plant. Several comparisons are made, and it has been shown that the proposed SMC theory-based algorithm has faster convergence than existing methods such as GD-based and swarm intelligence-based methods. Moreover, the proposed learning algorithm has an explicit form, and it is easier to implement than other existing methods. However, for offline algorithms for which computation time is not an issue, the hybrid training ...
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