Modelling Systems
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Mathematical Modelling and Computer Simulation of Biomechanical Systems
The book presents a new scientific approach to the problem of biomechanical systems description.This approach is based on development of a universal anthropomorphic model and employment of methodology of imitational dynamic modeling (IDM). The novelty of this approach is that there appears a possibility to operate with a whole class of models, derived from the universal model on the basis of motion separation principle. This is followed by utilization of iterational procedures realizing the method of successive approximations and resulting in description of the real motion with the pre-set accuracy level. By use of the IDM there has been for the first time ascertained certain laws governing human locomotions: presence of so-called controlling and stabilizing interlink moments, wavelike speeding of forces extremums along the kinematic chain, adaptation of control functions for astronauts motion coordination preservation. The book includes new theoretical conceptions explaining the deterioration of functional state of skeletal-muscular apparatus of astronauts due to zero-gravity influence.
Automating Data-Driven Modelling of Dynamical Systems
This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user’s perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification.