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Two observer-based tracking algorithms for a unicycle mobile robot

100%
Jakubiak J., Lefeber E., Tchoń K., Nijmeijer H.
International Journal of Applied Mathematics and Computer Science
|
2002
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tom 12
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nr 4
513-522
EN
A trajectory tracking problem for the three-dimensional kinematic model of a unicycle-type mobile robot is considered. It is assumed that only two of the tracking error coordinates are measurable. By means of cascaded systems theory we develop observers for each of the error coordinates and show the K-exponential convergence of the tracking error in combined closed-loop observer-controller systems. The results are illustrated with computer simulations.
2
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Separation principle for nonlinear systems: a bilinear approach

100%
Hammami M. A., Jerbi H.
International Journal of Applied Mathematics and Computer Science
|
2001
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tom 11
|
nr 2
481-492
EN
In this paper we investigate the local stabilizability of single-input nonlinear affine systems by means of an estimated state feedback law given by a bilinear observer. The associated bilinear approximating system is assumed to be observable for any input and stabilizable by a homogeneous feedback law of degree zero. Furthermore, we discuss the case of planar systems which admit bad inputs (i.e. the ones that make bilinear systems unobservable). A separation principle for such systems is given.
3
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A Hamiltonian approach to fault isolation in a planar vertical take-off and landing aircraft model

88%
Rodriguez-Alfaro L., Alcorta-Garcia E., Lara D., Romero G.
International Journal of Applied Mathematics and Computer Science
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2015
|
tom 25
|
nr 1
65-76
EN
The problem of fault detection and isolation in a class of nonlinear systems having a Hamiltonian representation is considered. In particular, a model of a planar vertical take-off and landing aircraft with sensor and actuator faults is studied. A Hamiltonian representation is derived from an Euler-Lagrange representation of the system model considered. In this form, nonlinear decoupling is applied in order to obtain subsystems with (as much as possible) specific fault sensitivity properties. The resulting decoupled subsystem is represented as a Hamiltonian system and observer-based residual generators are designed. The results are presented through simulations to show the effectiveness of the proposed approach.
4
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Neural network-based MRAC control of dynamic nonlinear systems

75%
Debbache G., Bennia A., Golea N.
International Journal of Applied Mathematics and Computer Science
|
2006
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tom 16
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nr 2
219-232
EN
This paper presents direct model reference adaptive control for a class of nonlinear systems with unknown nonlinearities. The model following conditions are assured by using adaptive neural networks as the nonlinear state feedback controller. Both full state information and observer-based schemes are investigated. All the signals in the closed loop are guaranteed to be bounded and the system state is proven to converge to a small neighborhood of the reference model state. It is also shown that stability conditions can be formulated as linear matrix inequalities (LMI) that can be solved using efficient software algorithms. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters. Simulation results are presented to show the effectiveness of the approach.
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