413 research outputs found
Adaptive Optimal Dynamic Control for Nonholonomic Systems
In this paper two different control methods are combined for controlling a typical nonholonomic device (a bicycle) the dynamic model and parameters of which are only approximately known. Most of such devices suffer from the problem that the time-derivatives of the coordinates of their location and orientation cannot independently be set so an arbitrarily prescribed trajectory cannot precisely be traced by them. For tackling this difficulty Optimal Control is proposed that can find acceptable compromise between the tracking error of the various coordinates. Further problem is that the solution proposed by the optimal controller cannot exactly be implemented in the lack of precise information on the dynamic model of the system. Based on the decoupled nature of the dynamic model of the longitudinal and lateral behavior of the engine special fixed point transformations are proposed to achieve adaptive tracking. These transformations were formerly successfully applied for the control of holonomic systems. It is the first time that the combined method is checked for various trajectories and dynamic model errors via simulation. It yielded promising results
Modelling and Control of Freeway Traffic
This paper presents the most recent developments of the Simulator
of Intelligent Transportation Systems (SITS). The SITS is based on a microscopic
simulation approach to reproduce real traffic conditions in an urban or non-urban
network. In order to analyse the quality of the microscopic traffic simulator SITS
a benchmark test was performed. A dynamical analysis of several traffic phenomena,
applying a new modelling formalism based on the embedding of statistics and
Laplace transform, is then addressed. The paper presents also a new traffic control
concept applied to a freeway traffic system
LPV-based quality interpretations on modeling and control of diabetes
In this study we introduce different novel interpretations in
the case of Linear Parameter Varying (LPV) methodology, which
are directly usable in modeling and control design in diabetes
research. These novel interpretations are based on the
parameter vectors of the LPV parameter space. The theoretical
solutions are demonstrated on a simple, known Type 1 Diabetes
Model used in intensive care
Adaptive vibration damping based on casual time-invariant green-functions and fractional order derivates
In this paper a simple nonlinear, adaptive control using causal time-invariant Green-functions and fractional order derivatives is applied for damping the vibration of a car forced during passing along a bumpy road. Its key idea is the replacement of the integer order derivates in a Green-functions-based nonlinear controller with a time-shift invariant, causal approximation of the Riemann-Liouville fractional derivative that also behaves like a Green-function. Since its physical essence is rather frequency filtering than providing inter order derivatives in limit cases, the approximation applied numerically is quite convinent. In this way simple kinematic design of the desired damping becomes possible. The adaptive part of the controller guarantees the realization of this kinematic design without making it necessary for the designer to have accurate and complete dynamic model of the system to be controlled or to design a sophisticated linear "CRONE" controller that has to take the responsability for the unknown dynamics of the system. The applicability of the approach is illustrated via simulations for a paradigm that is a rough model of a car. It was found that both adaptivity and the use of fractional order derivatives in the control are essential parts of the success of the method.info:eu-repo/semantics/publishedVersio
Simple Geometric Approach of Identification and Control Using Floating Basis Vectors for Representation
As a plausible alternative of certain sophisticated soft computing approaches trying to identify complete and static system models, a simple adaptive controller is outlined that creates only a temporal model. This model can be built up and maintained step-by-step on the basis of slowly fading information by the use of simple updating rules consisting of finite algebraic steps of lucid geometric interpretation. The method may be used for filling in the lookup tables or rule bases of the above representations
experimentally. The method is tested by the use of a simple dynamic system as a typical paradigm via simulation.N/
Optimal approximation of fractional derivatives through discrete-time fractions using genetic algorithms
This study addresses the optimization of rational fraction approximations for the discrete-time calculation of fractional derivatives. The article starts by analyzing the standard techniques based on Taylor series and Padé expansions. In a second phase the paper re-evaluates the problem in an optimization perspective by tacking advantage of the flexibility of the genetic algorithms
Approximating fractional derivatives through the generalized mean
This paper addresses the calculation of fractional order expressions through rational fractions. The article starts by analyzing the techniques adopted in the continuous to discrete time conversion. The problem is re-evaluated in an optimization perspective by tacking advantage of the degree of freedom provided by the generalized mean formula. The results demonstrate the superior performance of the new algorithm
Simple Kinematic Design for Evading the Forced Oscillation of a Car-Wheel Suspension System
An adaptive control damping the forced vibration of a car while passing
along a bumpy road is investigated. It is based on a simple kinematic description
of the desired behavior of the damped system. A modified PID controller containing
an approximation of Caputo’s fractional derivative suppresses the high-frequency
components related to the bumps and dips, while the low frequency part of passing
hills/valleys are strictly traced. Neither a complete dynamic model of the car nor ’a
priori’ information on the surface of the road is needed. The adaptive control realizes
this kinematic design in spite of the existence of dynamically coupled, excitable
internal degrees of freedom. The method is investigated via Scicos-based simulation
in the case of a paradigm. It was found that both adaptivity and fractional order
derivatives are essential parts of the control that can keep the vibration of the load at
bay without directly controlling its motion
Improved Numerical Simulation for a Novel Adaptive Control Using Fractional Order Derivatives
A novel control technique is investigated in the adaptive control of a
typical paradigm, an approximately and partially modeled cart plus double pendulum
system. In contrast to the traditional approaches that try to build up ”complete”
and ”permanent” system models it develops ”temporal” and ”partial” ones that are
valid only in the actual dynamic environment of the system, that is only within some
”spatio-temporal vicinity” of the actual observations. This technique was investigated
for various physical systems via ”preliminary” simulations integrating by the
simplest 1st order finite element approach for the time domain. In 2004 INRIA issued
its SCILAB 3.0 and its improved numerical simulation tool ”Scicos” making it possible
to generate ”professional”, ”convenient”, and accurate simulations. The basic
principles of the adaptive control, the typical tools available in Scicos, and others
developed by the authors, as well as the improved simulation results and conclusions
are presented in the contribution
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