Model structure estimation in identification and adaptive control

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Direct adaptive control using feedforward neural networks

ABSTRACT: This paper proposes a new scheme for direct neural adaptive control that works efficiently employing only one neural network, used for simultaneously identifying and controlling the plant. The idea behind this structure of adaptive control is to compensate the control input obtained by a conventional feedback controller. The neural network training process is carried out by using two different techniques: backpropagation and extended Kalman filter algorithm. Additionally, the convergence of the identification error is investigated by Lyapunov's second method. The performance of the proposed scheme is evaluated via simulations and a real time application. __________________________________________________________________________________ RESUMOEste artigo propõe uma nova estratégia de controle adaptativo direto em que uma única rede neural é usada para simultaneamente identificar e controlar uma planta. A motivação para essa estratégia de controle adaptativo é compensar a entrada de controle gerada por um controlador retroalimentado convencional. O processo de treinamento da rede neural é realizado através de duas técnicas: backpropagation e filtro de Kalman estendido. Adicionalmente, a convergência do erro de identificação é analisada através do segundo método de Lyapunov. O desempenho da estratégia proposta é avaliado através de simulações e uma aplicação em tempo real

Modeling, simulation and identification for control of tandem cold metal rolling

This paper describes a modeling procedure for tandem cold metal rolling, including the linearization step and system identification for control. The tandem cold rolling process is described by a mathematical model based on algebraic equations developed for control purposes and empirical relations. A state-space model is derived and detailed analyses in open loop are presented, concerning the sensitivity with regard to the variations in process parameters and results for the application of a new subspace identification method are compared with classical methodologies. Therefore, this work intents to be a contribution for developments in new control strategies for tandem cold rolling process that offer the potential to reduce the design efforts, the commissioning time and maintenance in rolling mills. The preliminary results obtained with this model have shown reasonable agreement with operational data presented at literature for industrial cold rolling process

The Development of a Flight Test Real Time GPS Navigation Tool (GNAV)

ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, CaliforniaThe real time acquisition and monitoring of the aircraft trajectory parameters is essential for the safety of the flight tests campaigns held by most of the tests centers. Nowadays the us age of an airborne GPS receiver as the main sensor for these parameters has become the preferred solution for the Flight Tests Instrumentation (FTI) systems. The main problem arises when it is required a high accuracy for these measurements (e.g. air data calibration) where the solution is achieved through differential GPS techniques. The integration of this solution requires the acquisition and the correlation of the pseudorange and phase measurements for all GPS satellites in view observed by both base and rover GPS receivers. To avoid the usage of an additional uplink for the GPS differential corrections (i.e. from the base receiver to the rover), it was developed a novel solution where the GPS observables acquired by the rover receiver are merged into the FTI PCM data stream and processed in the Telemetry ground station by a Real Time GPS Navigation (GNAV) tool together with the GPS observables acquired by the base receiver. The GNAV development is divided into several phases where the accuracy for the trajectory parameters and the complexity of the solution increases. The prototype system was built and evaluated against the post-mission Ashtech PNAV® tool and the initial tests results show a satisfactory performance for the GNAV. The tests profiles are fully compliant with the Federal Aviation Administration (FAA) Advisory Circular (AC) 25-7A.International Foundation for TelemeteringProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection

Flight Path Reconstruction and Parameter Estimation Using Output-Error Method

This work describes the application of the output-error method using the Levenberg-Marquardt optimization algorithm to the Flight Path Reconstruction (FPR) problem, which constitutes an important preliminary step towards the aircraft parameter identification. This method is also applied to obtain the aerodynamic and control derivatives of a regional jet aircraft from flight test data with measurement noise and bias. Experimental results are reported, employing a real jet aircraft, with flight test data acquired by smart probes, inertial sensors (gyrometers and accelerometers) and Global Positioning Systems (GPS) receivers

Optimization of Flight Test Maneuvers for Aerodynamic Derivatives Inverse Problem

This work deals with the application of optimization techniques to the determination of aircraft light test input maneuvers for aircraft model identification and aerodynamic parameter estimation. The optimum flight test maneuvers are necessary to increase the efficiency of aircraft identification and parameter estimation algorithms, respecting operational restrictions related to flight safety and limits of the assumed mathematical models. In this work we compare the effectiveness of identification processes obtained with conventional aircraft maneuvers and maneuvers defined by a special optimization procedure. In both cases, the increase of the efficiency of the estimation algorithms uses the maximization of sensitivity of output equations to the parameters of the model. For the conventional maneuver signals, however, this is made in an indirect form, by shaping the input signals in a way to increase the power spectral density of the signals in the range of the natural frequencies of the dynamic system of interest. The optimization technique, on the other hand is based on the concept of Maximum Likelihood Estimation (MLE) where the sensitivity matrix and Cramer-Rao lower bounds are used to compose the optimization criteria and to generate an optimal signal that minimizes the uncertainties related with the estimation of the aerodynamic parameters. One case study is discussed with the use of lateraldirectional dynamic models of a jet aircraft. The advantages and disadvantages of the proposed maneuvers are presented, stressing the easiness of implementation of the signals and the strong improvement made possible with the application of the optimized maneuver signals. Considerations and recommendations are regarding the importance of parameter estimation flight test maneuver