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Integrated framework for constrained minimum‐time trajectory generation, fault detection and reconfiguration: A case‐study
Author(s) -
Suryawan Fajar,
De Doná José,
Seron María
Publication year - 2016
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2651
Subject(s) - trajectory , fault detection and isolation , control reconfiguration , polytope , flatness (cosmology) , computer science , mathematical optimization , control theory (sociology) , algorithm , mathematics , artificial intelligence , control (management) , physics , cosmology , discrete mathematics , quantum mechanics , astronomy , actuator , embedded system
Summary This paper provides a unified treatment to the problems of constrained minimum‐time trajectory generation, fault detection and isolation and (after a fault has been detected and identified) trajectory reconfiguration, in an integrated scheme using a differential flatness and B‐splines parameterisation. Using the flatness/B‐splines parameterisation, the problem of minimum‐time constrained trajectory planning is cast into a feasibility‐search problem in the splines control‐points space, in which the constraint region is characterised by a polytope. A close approximation of the minimum‐time trajectory is obtained by systematically searching the end‐time that makes the constraint polytope to be minimally feasible. Fault detection is carried out by using B‐splines in an FIR filter implementation. Thus, the three problems (namely, trajectory generation, fault detection and trajectory reconfiguration), which are traditionally dealt with separately, are solved in a unified manner, using the same mathematical/computational tools. This, not only offers a unified solution but also simplifies the use of mathematical libraries in the coding of algorithms for real‐time applications. All through the paper, a case‐study consisting in a nonlinear input‐constrained double‐tank system is analysed in order to illustrate the techniques in an intuitive manner. Copyright © 2015 John Wiley & Sons, Ltd.