Methods of System Identification, Parameter Estimation and Optimisation Applied to Problems of Modelling and Control in Engineering and Physiology (original) (raw)
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The mathematical modeling of physical systems takes two forms. The first form is by differential equations. The second form is by identification methods that may be linear or nonlinear. The mathematical modeling of physical systems for identification has been widely discussed by academia, but most of works are developed within the simulation and not experimentation. Experiments conducted to real physical systems are scarce in the literature and a scarcity. The design of controllers is needed for process conditions regulatory and servant and is subject to the characteristics of the plant to be controlled. However, an actual process has aspects that increase the complexity of this project such as: delay of transport, noise stochastic fluctuations, the dynamics change in time. It is presented in this work, the mathematical modeling identification of a mechanical system fragile, and its dynamic changes over time, by the least squares non-recursive, so that the controller design is best suited to dynamic characteristics of this process.
Modelling, Identification and Control
Iterative Identification and Control, 2002
In this chapter we first review the changing role of the model in control system design over the last fifty years. We then focus on the development, over the last ten years, of the intense research activity and on the important progress that has taken place on the interplay between modelling, identification and robust control design. The major players of this interplay are presented; some key technical difficulties are highlighted, as well as the solutions that have been obtained to conquer them. We end the chapter by presenting the main insights that have been gained by a decade of research on this challenging topic.
Identification and Control of Mechanical Systems
Applied Mechanics Reviews, 2002
IDENTIFICATION AND CONTROL OF MECHANICAL SYSTEMS Vibration is a significant issue in the design of many structures including aircraft, spacecraft, bridges, and high-rise buildings. This book discusses the control of vibrating systems, integrating structural dynamics, vibration analysis, modern control, and system identification. Integrating these subjects is an important feature in that engineers will need only one book, rather than several texts or courses, to solve vibration/control problems. The book begins with a review of the fundamentals in mathematics, dynamics, and control that are needed for understanding subsequent materials. Chapters then cover recent developments in aerospace control and identification theory, including virtual passive control, observer and state-space system identification, and data-based controller synthesis. Many practical issues and applications are addressed, with examples showing how various methods are applied to real systems. Some methods show the close integration of system identification and control theory from the statespace perspective, rather than from the traditional input-output model perspective of adaptive control. This text will be useful for advanced undergraduate and beginning graduate students in aerospace, mechanical, and civil engineering, as well as for practicing engineers.
Editorial: Modeling and control of mechanical/ biomechanical systems
Theoretical and Applied Mechanics Letters, 2012
Many modern control applications are interdisciplinary in nature. Variety of disciplines are oriented on application of control theory and modeling of mechanical/biomechanical systems to solve practical problems in their specific fields. Bearing this in mind, there are included in this special subject some interesting contributions covering different areas such as bifurcations and chaos in dynamical systems, stability of dynamical systems, original numerical methods of vibration analysis, non-smooth systems, engineering systems and differential equations, control in dynamical systems, asymptotic methods in nonlinear dynamics, vibrations of lumped and continuous systems, dynamics in life sciences and bioengineering. A brief description of contents of this special subject is as follows: Analytical study of the two degrees of freedom nonlinear dynamical system is presented by J. Awrejcewicz and R. Starosta. Internal motion of the system is separated and described by one fourth order differential equation. An approximate approach allows for reduction of the problem to the Duffing equation with adequate initial conditions. There is a novel idea for an effective study of nonlinear dynamical systems consisting in a concept of the socalled limiting phase trajectories. Important nonlinear dynamical transition type phenomena are detected and discussed. In particular, nonsteady forced system vibrations are investigated analytically. For selected private reactions, J. Awrejcewicz et al. conducted experiments devoted to mechanisms of complex chemical reactions. It caused a problem of identification of kinetic parameters, because the same set of rate constants must describe both public and private reaction stages, and even the general mechanism. Solution of this problem for a reaction of olefins hydroalumination is successfully proposed, and in order to optimize the computational process, a methodology of parallelization is elaborated. The control design of underactuated robots usually relies on partial feedback linearization based techniques which are exclusively developed for systems modeled by independent coordinates. L. L. Kovács and L. Bencsik propose an interesting control algorithm formulated by using dependent coordinates. The applied computed torque controller is realized by introduction of actuator's constraints that complement the kinematic constraints. They are used to describe the dynamics of the investigated service robotic system in relatively simple and compact form. The proposed controller is applied to the computed torque control of the planar model of the acroboter service robot. V. F. Duma considers the problem of command functions of galvanometer-based scanners which are necessary to produce their linear plus parabolic scanning functions. He completes some theoretical aspects with the experimental study of the most useful scanning functions of
Nonlinear system identification employing automatic differentiation
Communications in Nonlinear Science and Numerical Simulation, 2013
An optimization based state and parameter estimation method is presented where the required Jacobian matrix of the cost function is computed via automatic differentiation. Automatic differentiation evaluates the programming code of the cost function and provides exact values of the derivatives. In contrast to numerical differentiation it is not suffering from approximation errors and compared to symbolic differentiation it is more convenient to use, because no closed analytic expressions are required. Furthermore, we demonstrate how to generalize the parameter estimation scheme to delay differential equations, where estimating the delay time requires attention.
Recent Advancements & Methodologies in System Identification: A Review
System Identification (SI) is a discipline in control engineering concerned with inferring mathematical models from dynamic systems based on its input/output observations. Rich literature is available regarding SI due to its applications in understanding complex systems as well as to design control systems for complex processes. A summary of those literatures is presented in this paper, which covers general classifications of SI, methodologies for design and implementation of the models, as well as recent advancements in application of optimization techniques for SI. It is hoped that this paper would serve as a guide for budding practitioners regarding the fundamentals of the discipline, while serving as a summary of new research trends for experienced researchers in the area.