Considerando los sistemas lineales invariantes en el tiempo (Linear Time-Invariant Systems, LTI) continuos con incertidumbres politópicas, esta contribución presenta un método para la síntesis de ...filtros robustos de detección y diagnóstico de fallas. El método está basado en condiciones de desempeño modificadas, establecidas a partir de las normas , las cuales se describen como desigualdades matriciales lineales (Linear Matrix Inequalities, LMIs). La generación de los residuos, producto de los filtros robustos, se obtiene aplicando esas condiciones modificadas sobre los sistemas con perturbación desconocidas y sujetos a incertidumbres. Los parámetros inciertos se suponen que pertenecen a un politopo. Las condiciones de desempeño extendidas se obtienen por medio del lema de proyección. El diagnóstico de las fallas se alcanza en primer lugar, estableciendo condiciones, extendidas también, de detectabilidad y aislamiento. En segundo lugar, si esas condiciones se satisfacen, se diseña un banco de filtros, es decir, por multifiltraje, basado en observadores de Luenberger. Para cada falla objeto de separación, se diseña un filtro. Para ilustrar los resultados y el desempeño del multifiltraje, se presenta además, un ejemplo numérico.
Mobile robot modelling and autonomous guidance Perez-Montenegro, Carlos; Canuto, Enrico; Cardenas-Olaya, Andrea ...
2015 IEEE 2nd Colombian Conference on Automatic Control (CCAC),
10/2015
Conference Proceeding
This paper presents a generic model for a mobile robot with n wheels and active suspension. The model is presented in the fashion of an Embedded Model (EM) in order to apply the control framework ...known as Embedded Model Control (EMC). EMC is a model based control technique which allows the proper active real-time estimation and rejection of system disturbances. This research constitutes the initial steps for the application of the EMC framework and its future implementation on mobile robotics related problems. A guidance strategy with elliptical trajectories is developed, which guaranties position and attitude constraints. Some simulations are presented at the end showing the capabilities of the model and guidance algorithm built and presented.
This paper presents a novel technique for robust fault detection, based on a modified H2/H∞ performance condition, which is described as LMI. Some theoretical results are shown in order to synthesize ...the residual generation scheme, for systems subjected to parametric uncertainty. The uncertainty parameters are supposed to belong to a polytope. The extended H2/H∞ conditions are obtained by means of the well known projection lemma. Fault detection and isolation are done by using a filters bank (i.e. multifiltering) based on Luenberger's observer and one filter is obtained for each fault. Performance of the proposed synthesis technique is illustrated by a numerical example.
The error loop and robust closed-loop stability Canuto, E.; Acuna-Bravo, W.; Jimenez, A. M. ...
2012 IEEE International Conference on Mechatronics and Automation,
2012-Aug.
Conference Proceeding
The paper formulates the error loop as a tool for designing robust stability control systems in front of structured and unstructured uncertainties. The error loop indicates that a tool for ...accommodating such uncertainties is the noise estimator, which is the unique feedback channel from plant to control. It is shown that causality constraint in cancelling causal uncertainties (unknown disturbance) makes control law to play a role, offering a further degree of freedom. Employing asymptotic expansions of the closed-loop transfer functions, simple and explicit design formulae derive from stability inequalities: they relate closed-loop eigenvalues to model parameter and requirements. A simple example is provided from a ball and beam plant.
Robust control design is mainly devoted to guarantee closed-loop stability of
a model-based control law in presence of parametric and structural
uncertainties. The control law is usually a complex ...feedback law which is
derived from a (nonlinear) model, possibly complemented with some mathematical
envelope of the model uncertainty. Stability may be guarantee with the help of
some ignorance coefficients and restricting the feedback control effort with
respect to the model-based design. Embedded Model Control shows that under
certain conditions, the model-based control law must and can be kept intact
under uncertainty, if the controllable dynamics is complemented by a suitable
disturbance dynamics capable of real-time encoding the different uncertainties
affecting the 'embedded model', i.e. the model which is both the design source
and the core of the control unit. To be real-time updated the disturbance state
is driven by an unpredictable input vector, called noise, which can be only
estimated from the model error. The uncertainty (or plant)-based design
concerns the noise estimator, as the model error may convey into the embedded
model uncertainty components (parametric, cross-coupling, neglected dynamics)
which are command-dependent and thus prone to destabilize the controlled plant.
Separation of the components into the low and high frequency domain by the
noise estimator allows to recover and guarantee stability, and to cancel the
low frequency ones from the plant. Among the advantages, control algorithms are
neatly and univocally related to the embedded model, the embedded model
provides a real-time image of the plant, all control gains are tuned by fixing
closed-loop eigenvalues. Last but not least, the resulting control unit has
modular structure and algorithms, thus facilitating coding. A simulated case
study helps to understand the key assets of the methodology.
This paper deals with the dynamic modelling of a complex electro-hydraulic system. Modelling is based on physical laws and the system knowledge. The main idea is to obtain a simple and reliable model ...that can be used for controller synthesis and implementation by using the architecture of embedded model control. Simplifications are made by taking as basis the ideas of singular perturbation. A subsequent identification procedure is made in order to acquire some important parameters, required for carrying out a simulation.
