B. Bergeon

Modelling of Longitudinal Disturbed Aircraft Model by Flatness Approach

In this paper, an LFT model representing the longitudinal dynamic of the gap between the open loop nominal of an Hight Incidence aircraft Research model named HIRM+ and the disturbed model on a trajectory is given. Five of the most relevant uncertainties on pitch axis are considered. This model describes the gap along a trajectory passing through flight condition FC1, with an angle of attack equal to 6 - . The proposed approach is based on a simplified longitudinal model used to determine a nominal trajectory and corresponding input. The specific outputs are angle of attack fi and pitch angle µ. These outputs allow a parameterisation of state-space trajectory. First the LFT generation by flatness approach is described. Then an LFT model of the open loop model for the above flight condition is given. Thereafter an LFT model of closed loop HIRM+RIDE is proposed to allow the identification of worst case stability margin.

Generic Expert System for Identification of Industrial Processes

Abstract The final goal of our Expert System in Identification is to provide a helpful tool for the user of Identification techniques. Because the Identification theory is still growing, we have to implement our ES in such a way that it allows further developments of theoretical results or of the way to use them. Moreover, each user could wish to describe easily its own expertise. So we aim to design a generic knowledge base, for evolutivity and flexibility. for that purpose we use the Static, Semiotic and Dynamic Design method, as described in the first part of the paper. The most relevant aspect of this method is the structuration of the knowledge base into three components: the generic component, the static knowledge base and the dynamic knowledge base. The second part of our paper presents the description and the structuration of the objects involved in identification procedure and the links between them (the static description), the strategy of an user for solving a specific problem of identification (the dynamic knowledge base). The third and last part describes the generic component, which contains the control structure under the form of generic rules. In this paper we focus on a part of identification general problem, namely the choice of Model Structure, Parameter Estimation Method and Computation Algorithm.

Robust Control of Flat Nonlinear System

Abstract This paper proposes a systematic approach for robust tracking control design of a class of nonlinear systems, refered to dynamic flat systems. First, a nonlinear dynamic feedback is designed to ensure nominal path tracking performance. Next, a compact set of models is elaborated in the vicinity of the nominal path, taking into account both state space disturbances and parametric uncertainties. Finally, a robust linear controller is designed which guarantees the path tracking perfomance objectives for the above so-obtained compact set. Simulations results obtained from speed control of a synchronous actuator demonstrate the potential of the proposed approach.

Frequency Space Synthesis of a Robust Dynamic Command

Real time programming of manipulators implies two distinct, real time operations, namely the generation and the checking of trajectories defined by an operator. In another contribution, we discussed the real time generation of trajectories by a syntaxer, focussing on an optical, three dimensional syntaxer. Here, therefore, we shall study the real time control of the trajectory and the design of a high performance dynamic command for a manipulator.

Specification of a Real-time Knowledge Based Supervision System

Abstract We propose a hierarchical structure for the supervision of an industrial process. The general frame for the specification of the knowledge based is presented through the specific example of a supervision system for the robust control of a robot. The role devoted to the supervision system lies in the surveillance of a few indexes of good functioning of the path-planner, the robust controller and the electro-mechanical plant. After detection, analysis and diagnosis of a failure situation, the supervision layer decides to set off appropriate actions as readjustment of the path-planner design parameters, either self-tuning of the robust controller through an identification phase, or switch to a different operating mode

An Expert System for Industrial Process Identification

Abstract An expert identification package would be a very useful1 tool as soon as every industrial process identification problem requires a great knowledge of identification methods and a good experience of technological rea1izations. It must be composed with a control mechanism, a set of inference rules, an algorithms base and the interfaces allowing conversation between all these blocks. We present here some generalities about the identification problem, the required structure of the expert knowledge and the specifications on the control mechanism. A demonstration model has been developed, using ELISE, an expert system shell developed at University of Bordeaux I.

Flatness Approach to LFT Modelling

In this chapter, an LFT model representing the longitudinal dynamic of the gap between the open loop nominal HIRM+ model and the perturbed model on a trajectory is given. Five of the most relevant uncertainties on the pitch axis are considered. This model describes the gap along a trajectory passing through flight condition FC1, with an angle of attack equal to 6°. The proposed approach is based on a simplified longitudinal model used to determine a nominal trajectory and corresponding input. The specific outputs are angle of attack α and pitch angle θ. These outputs allow a parametrisation of state-space trajectory. First the LFT generation by flatness approach is described. Then an LFT model of the open loop HIRM+ model for the above flight condition is given. Thereafter an LFT model of the closed loop HIRM+RIDE is proposed to allow the identification of worst case stability margin.

Modeling of Disturbed Flat System for Robust Control Design

Abstract This paper aims at presenting a modelization of the uncertainty on the linear model obtained from the so-called linearizing feedback of dynamic flat systems. After such a linearizing feedback is computed to ensure good nominal tracking performance, a compact set of models can be computed by taking account of both state space disturbances and parametric errors. A robust linear feedback is then designed in order to guarantee a specified level of performance. This representation of the compact set of models makes use of the Linear Fractional Transformation. so that the global robustness of tracking performance is assessed by μanalysis.

H-infinity design and multivariable delay margin: Application to the dynamical control of a four-wheeled vehicle

One way of taking account of stability robustness to unmodelled dynamics, consists in the definition of delay margin. In the linear monovariable case, this delay margin, defined as the smallest additional delay in the loop, able to destabilize the closed-loop, is calculated by the way of phase margin and crossover frequency. In the multivariable case, the delay margin can be bounded by constraint on the upper principal gains on sensitivity and complementary sensitivity of the closed-loop. This constraint can be used in H-infinity mixed sensitivity design to achieve specified delay margin. An example is given on the control design of dynamical control of a four-wheeled vehicle, and has been developed in an industrial cooperation context.

LFT representation of a longitudinal perturbed aircraft model by flatness approach

In this paper, an linear fractional transformations (LFT) model representing, the dynamic of the gap between a nominal model and a perturbed model of a longitudinal aircraft fighter along a trajectory is given. The proposed approach is based on a simplified model used to determine a nominal trajectory and corresponding input. This simplified nonlinear model is a flat nonlinear system. As the measures on the so-called flat outputs, used in the linearizing feedback, are corrupted with noise and effects of unmodelled dynamics or parametric errors (model simplifications), the state space trajectory of the actual plant is not identical to the reference state space trajectory. Then the exact linearization is not achieved, but, as long as the tracking error remains small enough, the actual quasi-linearised plant can be modelled as a disturbed linear plant. The gap behaviour is modelled by a set of linear models described by a LFT model.