Hugo Lhachemi

A Robust and Self-Scheduled Longitudinal Flight Control System: a Multi-Model and Structured H-infinity Approach

This paper presents a novel approach to design robust and smooth self-scheduled controllers in the framework of structured H∞ control. The newly available MATLAB-based tool, hinfstruct, is used to tune fixed-structure linear controllers to meet H∞ constraints. Moreover, multi-model and multi-channel capabilities are exploited in the design of selfscheduled controllers. In this context, we define a priori both controller architecture and gain-scheduling structure. This approach is successfully applied to the longitudinal control of a F-16 Fighting Falcon over the flight envelope under mass and center of gravity uncertainties. After casting the control synthesis into a structured H∞ problem, the scheduled gains are directly obtained as quadratic polynomial functions of altitude and Mach number. The performance of the designed control systems is validated by numerical simulations.

Gain-scheduling control design in the presence of hidden coupling terms via eigenstructure assignment: Application to a pitch-axis missile autopilot

This paper tackles the gain-scheduling control design issue in the presence of hidden coupling terms. Hidden coupling terms naturally arise when endogenous signals, such as system outputs or state variables, are used as scheduling parameters. In this case, additional terms appear in the linearized gain-scheduled controller dynamics, which are generally omitted in the linear controller dynamics used in control synthesis. Such a discrepancy can induce severe performance degradation, or even the destabilization of the closed-loop system if the gain-scheduled controller is applied to the original nonlinear system. This paper presents a self-scheduling technique enabling to take into account the hidden coupling terms in the design process, so that the local properties of the nonlinear gain-scheduled controller can be preserved. The proposed approach is illustrated via an eigenstructure assignment-based design for a pitch-axis missile autopilot benchmark problem and is validated by nonlinear simulations.

An enhanced velocity-based algorithm for safe implementations of gain-scheduled controllers

ABSTRACT This paper presents an enhanced velocity-based algorithm to implement gain-scheduled controllers for nonlinear and parameter-dependent systems. A new scheme including pre- and post-filtering is proposed with the assumption that the time-derivative of the controller inputs is not available for feedback control. It is shown that the proposed control structure can preserve the input–output properties of the linearised closed-loop system in the neighbourhood of each equilibrium point, avoiding the emergence of the so-called hidden coupling terms. Moreover, it is guaranteed that this implementation will not introduce unobservable or uncontrollable unstable modes, and hence the internal stability will not be affected. A case study dealing with the design of a pitch-axis missile autopilot is carried out and the numerical simulation results confirm the validity of the proposed approach.

Performance enhancement of a self-scheduled longitudinal flight control system via multi-objective optimization

The present work aims at improving the performance of robust and smooth self-scheduled controllers in the framework of structured H∞ design. The developed procedure exploits multi-model and multi-channel capabilities of a MATLAB-based tool hinfstruct in the design of robust and self-scheduled flight control systems. In this approach, both controller and gain-scheduling architectures are defined a priori and are cast into the structured H∞ synthesis framework. By formulating the considered problem in the multi-objective optimization framework, the control design amounts then to computing weakly Pareto optimal solutions in which weighting coefficients can be determined based on physical considerations or preliminary designs. The tuning of weighting coefficients can be performed by normalizing the minimization effort over the operating domain or assigning more weight to a specific sub-domain. The proposed procedure is applied to the design of a robust and self-scheduled longitudinal flight control system. Numerical analysis and simulation show an important performance improvement.

Boundary feedback stabilization of a flexible wing model under unsteady aerodynamic loads

This paper addresses the boundary stabilization of a flexible wing model, both in bending and twisting displacements, under unsteady aerodynamic loads, and in presence of a store. The wing dynamics is captured by a distributed parameter system as a coupled Euler–Bernoulli and Timoshenko beam model. The problem is tackled in the framework of semigroup theory, and a Lyapunov-based stability analysis is carried out to assess that the system energy, as well as the bending and twisting displacements, decay exponentially to zero. The effectiveness of the proposed boundary control scheme is evaluated based on simulations.

Partition modeling and optimization of ARINC 653 operating systems in the context of IMA

The adoption of Integrated Modular Avionics (IMA) architecture is a technological trend in the avionics industry due to its capability of supporting space and temporal partitioning, which is mandatory for systems with mixed criticality. However, combining partition allocation and schedule design for applications sharing hardware, software, and communication resources of the same computing platform while assuring temporal behavior is a complex task that requires adequate tools for system design and integration. This paper presents the main features of a model that has been developed for simultaneous partition allocation and schedule design, which allows for automatic adjustment of both applications distribution over the partitions and scheduling parameters toward performance optimization. In the proposed model, all the variables are integer and all constraints are formulated via linear equalities and inequalities. Therefore, this problem can be efficiently solved by many existing mixed integer linear programming algorithms. A set of timing constraints at both partition and task levels are established, and different optimization objective functions are provided. The results of a case study show that, if a solution exists, the proposed model can achieve a global optimum while guaranteeing that all the constraints are met.