Abstract
Keywords:
System identification, MIMO-ARMAX models, Hybrid optimisation, Prediction-error methods.
Abstract:
This paper attempts to describe the lateral dynamics of a full-car vehicle, based on multiple input and multiple, noise-corrupted, output data, by means of a corresponding ARMAX model, which is estimated using a novel hybrid optimisation algorithm, and a corresponding estimation procedure, based on Prediction-Error Method. The specific algorithm attempts to interconnect the diverse characteristics of two entirely different optimisation techniques, deterministic and stochastic, combining high convergence rate with increased reliability in the search for global optimum, and it consists of a super-positioned stochastic global search, followed by an independent deterministic procedure. In the full-car vehicle application study, the proposed method yielded satisfying results, regarding its consistency, the description of the system, as well as the corresponding computational cost.