Vicente Mata1, Nidal Farhat1, Miguel Díaz-Rodríguez2, Ángel Valera3 and Álvaro Page4, Universidad Politécnica de Valencia, Departamento de Mecánica y Materiales Valencia1, Universidad de los Andes, Facultad de Ingeniería, Departamento de Tecnología y Diseño Mérida2, Universidad Politécnica de Valencia, Departamento de Ingeniería de Sistemas y Automática Valencia3, Universidad Politécnica de Val...

This paper presents a parameter identification technique for multibody dynamic systems, based on a nonlinear least–square optimization procedure. The procedure identifies unknown parameters in the differential–algebraic multibody system model by matching the acceleration time history of a point of interest with given data. Derivative information for the optimization process is obtained through ...

An efficient secant-method based algorithm for solving nonlinear least squares problem is presented which showed good stability and convergence properties even with relatively high number of unknowns and large system response deviations. The trial solutions were generated by a special transformation in each iteration step. The distance between observed and simulated system responses were define...

For several decades, PID (Proportional-Integral-Derivative) control has succesfully been applied to numerous industrial processes for regulating them. The PID controller has indisputably become a backbone of every automation system being available for controlling a large scale of industrial processes. However, it has also other capabilities than just that for regulating processes by manipulatin...

The problem of eliciting priors on the parameter space of a signal hypothesis is considered in this paper, and two lesser-known approaches are emphasized. Each yields conservative priors appropriate for data-dominated Bayesian parameter inference. They are based, respectively, on the principles of (i) a posteriori transformation invariance, and (ii) a priori maximum entropy. Novel priors on a w...

This work presents the development, assessment and comparison of four techniques for identifying dynamic parameters in an industrial redundant manipulator robot with 5 degrees of freedom. Based on the Lagrange–Euler formulation, a linear model of the robot with unknown parameters is obtained. Then, these parameters are identified using the following techniques: least squares, artificial Adaline...

In this paper, the metaheuristics algorithm Cuckoo Search (CS), is adapted and applied for a model parameter identification of an E. coli fed-batch cultivation process. The dynamics of bacteria growth and substrate (glucose) utilization is described by a system of ordinary nonlinear differential equations. Using real experimental data set from an E. coli MC4110 fed-batch cultivation process a p...

Estimating observability matrices or state sequences is the central component of existing subspace identification methods. In this paper a different approach, in which Markov parameters are first estimated under general input excitation, is proposed. The prominent difference of this approach is that a three-block arrangement of data matrices is used. It is shown that one advantage of this appro...