Adaptive control of large space structures using recursive lattice filters

The use of recursive lattice filters for identification and adaptive control of large space structures is studied. Lattice filters were used to identify the structural dynamics model of the flexible structures. This identification model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures is control engaged. This type of validation scheme prevents instability when the overall loop is closed. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods. The method uses the Linear Quadratic Guassian/Loop Transfer Recovery (LQG/LTR) approach to ensure stability against unmodeled higher frequency modes and achieves the desired performance

Satisficing in multi-armed bandit problems

Satisficing is a relaxation of maximizing and allows for less risky decision making in the face of uncertainty. We propose two sets of satisficing objectives for the multi-armed bandit problem, where the objective is to achieve reward-based decision-making performance above a given threshold. We show that these new problems are equivalent to various standard multi-armed bandit problems with maximizing objectives and use the equivalence to find bounds on performance. The different objectives can result in qualitatively different behavior; for example, agents explore their options continually in one case and only a finite number of times in another. For the case of Gaussian rewards we show an additional equivalence between the two sets of satisficing objectives that allows algorithms developed for one set to be applied to the other. We then develop variants of the Upper Credible Limit (UCL) algorithm that solve the problems with satisficing objectives and show that these modified UCL algorithms achieve efficient satisficing performance.Comment: To appear in IEEE Transactions on Automatic Contro

Algorithm for normal random numbers

We propose a simple algorithm for generating normally distributed pseudo random numbers. The algorithm simulates N molecules that exchange energy among themselves following a simple stochastic rule. We prove that the system is ergodic, and that a Maxwell like distribution that may be used as a source of normally distributed random deviates follows when N tends to infinity. The algorithm passes various performance tests, including Monte Carlo simulation of a finite 2D Ising model using Wolff's algorithm. It only requires four simple lines of computer code, and is approximately ten times faster than the Box-Muller algorithm.Comment: 5 pages, 3 encapsulated Postscript Figures. Submitted to Phys.Rev.Letters. For related work, see http://pipe.unizar.es/~jf

The Nyquist criterion: a useful tool for the robust design of continuous-time ΣΔ modulators

This paper introduces a figure of merit for the robustness of continuous-time sigma-delta modulators. It is based on the Nyquist criterion for the equivalent discrete-time (DT) loop filter. It is shown how continuous-time modulators can be designed by optimizing this figure of merit. This way modulators with increased robustness against variations in the noise-transfer function (NTF) parameters are obtained. This is particularly useful for constrained systems, where the system order exceeds the number of design parameters. This situation occurs for example due to the effect of excess loop delay (ELD) or finite gain bandwidth (GBW) of the opamps. Additionally, it is shown that the optimization is equivalent to the minimization of H_infinity, the maximum out-of-band gain of the NTF. This explains why conventional design strategies that are based on H_infinity, such as Schreier’s approach, provide quite robust modulator designs in the case of unconstrained architectures

A unified smith predictor approach for power system damping control design using remote signals

Published versio

Nonlinear observation in fuel cell systems: a comparison between disturbance estimation and High-Order Sliding-Mode techniques

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper compares two Nonlinear Distributed Parameter Observers (NDPO) for the observation of a Proton Exchange Membrane Fuel Cell (PEMFC). Both NDPOs are based on the discretisation of distributed parameters models and they are used to estimate the state profile of gas concentrations in the anode and cathode gas channels of the PEMFC, giving detailed information about the internal conditions of the system. The reaction and water transport flow rates from the membrane to the channels are uncertainties of the observation problem and they are estimated throughout all the length of the PEMFC without the use of additional sensors. The first observation approach is a Nonlinear Disturbance Observer (NDOB) for the estimation of the disturbances in the NDPO. In the second approach, a novel implementation of a High-Order Sliding-Mode (HOSM) observer is developed to estimate the true value of the states as well as the reaction terms. The proposed observers are tested and compared through a simulation example at different operating points and their performance and robustness is analysed over a given case study, the New European Driving Cycle.Peer ReviewedPostprint (author's final draft