Abstract

This paper presents a generic trim problem formulation, in the form of a constrained optimization problem, which employs forces and moments due to the aircraft control surfaces as decision variables. The geometry of the Attainable Moment Set (AMS), i.e. the set of all control forces and moments attainable by the control surfaces, is used to define linear equality and inequality constraints for the control forces decision variables. Trim control forces and moments are mapped to control surface deflections at every solver iteration through a linear programming formulation of the direct Control Allocation algorithm. The methodology is applied to an innovative box-wing aircraft configuration with redundant control surfaces, which can partially decouple lift and pitch control, and allow direct lift control. Novel trim applications are presented to maximize control authority about the lift and pitch axes, and a “balanced” control authority. The latter can be intended as equivalent to the classic concept of minimum control effort. Control authority is defined on the basis of control forces and moments, and interpreted geometrically as a distance within the AMS. Results show that the method is able to capitalize on the angle of attack or the throttle setting to obtain the control surfaces deflections which maximize control authority in the assigned direction. More conventional trim applications for minimum total drag and for assigned angle of elevation are also explored.

Highlights

  • Trimming a dynamic system means finding the combination of input and state variables values which set the system in a steady-state condition [1]

  • This paper presents a novel generic trim problem formulation, in the form of a

  • Control forces and moments are mapped to the effectors using a linear programming (LP) formulation of the Direct Control Allocation (DCA) method [3]

Read more

Summary

Introduction

Trimming a dynamic system means finding the combination of input and state variables values which set the system in a steady-state condition [1]. The constraints (and, optionally, the objective function) of such optimization problem are obtained by exploiting the geometric properties of the Attainable Moment Set (AMS). The latter is a convex polytope representing all the possible forces and moments that can be attained by the aircraft control effectors and flight control system [2]. Due to non-linearities and couplings in the aerodynamic model of control effectors, it is usually hard to characterize the EMS in Moment Space, a Cartesian axis system in RNF with a control force or moment varying on each axis. If the aerodynamic model of Eq (5) is linearized with respect to the control effectors positions, the control effectiveness matrix defines a linear function which maps the ACS to an approximation of the EMS, as shown in Eq (6)

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call