Adaptive rejection of finite band disturbances - theory and applications

Le chapitre présente les techniques de rejection adpative de perturbation inconnue mais de bande finie. Plusieurs exemples sont mentionnés et l'application au rejet adaptatifs de perturbation inconnues sur une suspension active est décrite en détailThe techniques for adaptive rejection of unknown finite band disturbances are reviewed. Several applications are mentionned and the application to the adaptive rejection of unknown disturbances on an active suspension is presented in detail

Indirect Adaptive Attenuation of Multiple Narrow-Band Disturbances Applied to Active Vibration Control

International audienceIn this brief, an indirect adaptive control methodology for attenuation of multiple unknown time varying narrow-band disturbances is proposed. This method is based on the real time estimation of the frequency of narrow-band disturbances using adaptive notch filters followed by the design of a controller using adjustable band-stop filters for the appropriate shaping of the output sensitivity function. A Youla-Kučera parametrization of the controller is used for reducing the computation load. This approach is compared on an active vibration control system with the direct adaptive control scheme based on the internal model principle proposed. Real time experimental results are provided

Learning and Reacting with Inaccurate Prediction: Applications to Autonomous Excavation

Motivated by autonomous excavation, this work investigates solutions to a class of problem where disturbance prediction is critical to overcoming poor performance of a feedback controller, but where the disturbance prediction is intrinsically inaccurate. Poor feedback controller performance is related to a fundamental control problem: there is only a limited amount of disturbance rejection that feedback compensation can provide. It is known, however, that predictive action can improve the disturbance rejection of a control system beyond the limitations of feedback. While prediction is desirable, the problem in excavation is that disturbance predictions are prone to error due to the variability and complexity of soil-tool interaction forces. This work proposes the use of iterative learning control to map the repetitive components of excavation forces into feedforward commands. Although feedforward action shows useful to improve excavation performance, the non-repetitive nature of soil-tool interaction forces is a source of inaccurate predictions. To explicitly address the use of imperfect predictive compensation, a disturbance observer is used to estimate the prediction error. To quantify inaccuracy in prediction, a feedforward model of excavation disturbances is interpreted as a communication channel that transmits corrupted disturbance previews, for which metrics based on the sensitivity function exist. During field trials the proposed method demonstrated the ability to iteratively achieve a desired dig geometry, independent of the initial feasibility of the excavation passes in relation to actuator saturation. Predictive commands adapted to different soil conditions and passes were repeated autonomously until a pre-specified finish quality of the trench was achieved. Evidence of improvement in disturbance rejection is presented as a comparison of sensitivity functions of systems with and without the use of predictive disturbance compensation

Climatic cyclicity at Site 806; the GRAPE record

We used the continuous saturated bulk density records collected by the gamma-ray attenuation porosity evaluator (GRAPE) at Ocean Drilling Program Site 806 on the top of the Ontong Java Plateau to evaluate the continuity of the recovered cores and to splice together a complete section from the multiple holes drilled at the site (for the upper 165 m, this is equivalent to approximately 0-5 Ma). The lack of offset in core breaks (between the 9.5-m-long, successive cores) from hole to hole made splicing difficult, and the results are not unambiguous. The composite section was converted to a time series by using biostratigraphy and supplementing this with oxygen-isotope datums for the interval between 2 and 5 Ma. Evolutionary spectra generated from the composite section clearly indicate the presence of Milankovitch frequencies throughout the record. We chose a final age model that was most consistent with a Milankovitch model but have not, as yet, spectrally tuned the data. The GRAPE (saturated bulk density) changes at Site 806 are the result of changes in grain size, with density decreasing as grain size increases. We attribute this to the removal of fine particles by winnowing, leaving a greater percentage of large hollow foraminifers behind— the winnowing effect. This is in contrast to the dissolution effect, which breaks up large hollow foraminifers into fragments but merely transfers intraparticle porosity to interparticle porosity and thus shows significant changes in grain size without significant changes in density. A 300-k.y. piston core record reveals that during this time interval increased winnowing has been associated with glacials and 100-k.y. cyclicity. For the time interval from 5 to 2 Ma, enhanced winnowing continues to be associated with isotopically heavy intervals dominated by 41-k.y. (obliquity) variance. In this band, the winnowing record is highly correlated with the ice-volume record, particularly since the onset of Northern Hemisphere glaciations. Before that time, the grain-size record continues to show variance in the obliquity band whereas the oxygen isotope record shows a shift to the dominance of precessional frequencies. We suggest that the winnowing signal is a response to increased thermohaline circulation and benthic storm activity associated with enhanced north-south thermal gradients during times of climatic degradation

Evolutionary design of a full-envelope full-authority flight control system for an unstable high-performance aircraft

The use of an evolutionary algorithm in the framework of H1 control theory is being considered as a means for synthesizing controller gains that minimize a weighted combination of the infinite norm of the sensitivity function (for disturbance attenuation requirements) and complementary sensitivity function (for robust stability requirements) at the same time. The case study deals with a complete full-authority longitudinal control system for an unstable high-performance jet aircraft featuring (i) a stability and control augmentation system and (ii) autopilot functions (speed and altitude hold). Constraints on closed-loop response are enforced, that representing typical requirements on airplane handling qualities, that makes the control law synthesis process more demanding. Gain scheduling is required, in order to obtain satisfactory performance over the whole flight envelope, so that the synthesis is performed at different reference trim conditions, for several values of the dynamic pressure, used as the scheduling parameter. Nonetheless, the dynamic behaviour of the aircraft may exhibit significant variations when flying at different altitudes, even for the same value of the dynamic pressure, so that a trade-off is required between different feasible controllers synthesized at different altitudes for a given equivalent airspeed. A multiobjective search is thus considered for the determination of the best suited solution to be introduced in the scheduling of the control law. The obtained results are then tested on a longitudinal non-linear model of the aircraft

Dynamic Stability with Artificial Intelligence in Smart Grids

Environmental concerns are among the main drives of the energy transition in power systems. Smart grids are the natural evolution of power systems to become more efficient and sustainable. This modernization coincides with the vast and wide integration of energy generation and storage systems dependent on power electronics. At the same time, the low inertia power electronics, introduce new challenges in power system dynamics. In fact, the synchronisation capabilities of power systems are threatened by the emergence of new oscillations and the displacement of conventional solutions for ensuring the stability of power systems. This necessitates an equal modernization of the methods to maintain the rotor angle stability in the future smart grids. The applications of artificial intelligence in power systems are constantly increasing. The thesis reviews the most relevant works for monitoring, predicting, and controlling the rotor angle stability of power systems and presents a novel controller for power oscillation damping