Nonlinear Control of Fighter Aircraft


Book Description

The problem of designing flight control systems for high performance tailless fighter aircraft is discussed in the report. The research uses linear matrix inequalities and semidefinite programming to addresses three areas of tailless fighter flight control. The first area investigates H2 and Hinf controller design using linear matrix inequalities. The second area uses linear matrix inequalities and linear parameter varying models to develop stability analysis tools for gain scheduled and reconfigurable control laws. The third area focused on using linear matrix inequalities to design aeroservoelastic fitters.




Robust Nonlinear Control of Tailless Fighter Aircraft


Book Description

Tools that lead to effective control strategies for tailless fighter aircraft were developed. Emphasis was placed on the development of control algorithms that yield robust performance in the presence of actuator magnitude and rate limits and that account for the interaction of a pilot with the airframe and control system. Numerous new analysis tools for nonlinear control systems were developed, with an emphasis on disturbance attenuation and sampled data control. Previously developed algorithms for control (especially anti-windup control) in the presence of actuator rate and magnitude limits were extended. The algorithms were applied to the manual flight control problem for open loop unstable fighter aircraft.




Robust Nonlinear Control of Piloted Tailless Fighters


Book Description

The theme of this research has been to develop effective strategies for the design and analysis of flight control systems for tailless fighter aircraft. In our quest to understand the fundamental issues in the aggressive maneuvering of high performance fighter aircraft, we have developed tools and techniques, and the appropriate supporting theoretical results, for the study and analysis of high performance maneuvering systems. We have developed a simplified flight dynamics model, the coordinated flight vehicle (CFV). Exploiting the geometric structure of the CFV, one may easily explore the space of aggressive flight maneuvers. We have developed an optimization based, trajectory morphing technique by which CFV maneuvers may be used to parametrize the achievable flight maneuvers (i.e., maneuvers that satisfy given high fidelity aircraft model dynamics). We have also developed theory and algorithms to allow these model based optimization techniques to used online, in a receding horizon fashion. As a theoretical bonus, we have obtained new results on the structure of the trajectory manifold of a nonlinear system.




Fighter Aircraft Maneuver Limiting Using MPC: Theory and Application


Book Description

Flight control design for modern fighter aircraft is a challenging task. Aircraft are dynamical systems, which naturally contain a variety of constraints and nonlinearities such as, e.g., maximum permissible load factor, angle of attack and control surface deflections. Taking these limitations into account in the design of control systems is becoming increasingly important as the performance and complexity of the aircraft is constantly increasing. The aeronautical industry has traditionally applied feedforward, anti-windup or similar techniques and different ad hoc engineering solutions to handle constraints on the aircraft. However these approaches often rely on engineering experience and insight rather than a theoretical foundation, and can often require a tremendous amount of time to tune. In this thesis we investigate model predictive control as an alternative design tool to handle the constraints that arises in the flight control design. We derive a simple reference tracking MPC algorithm for linear systems that build on the dual mode formulation with guaranteed stability and low complexity suitable for implementation in real time safety critical systems. To reduce the computational burden of nonlinear model predictive control we propose a method to handle the nonlinear constraints, using a set of dynamically generated local inner polytopic approximations. The main benefit of the proposed method is that while computationally cheap it still can guarantee recursive feasibility and convergence. An alternative to deriving MPC algorithms with guaranteed stability properties is to analyze the closed loop stability, post design. Here we focus on deriving a tool based on Mixed Integer Linear Programming for analysis of the closed loop stability and robust stability of linear systems controlled with MPC controllers. To test the performance of model predictive control for a real world example we design and implement a standard MPC controller in the development simulator for the JAS 39 Gripen aircraft at Saab Aeronautics. This part of the thesis focuses on practical and tuning aspects of designing MPC controllers for fighter aircraft. Finally we have compared the MPC design with an alternative approach to maneuver limiting using a command governor.




Nonlinear Analysis and Synthesis Techniques for Aircraft Control


Book Description

Despite many signi?cant advances in the theory of nonlinear control in recent years, the majority of control laws implemented in the European aerospace - dustry are still designed and analysed using predominantly linear techniques applied to linearised models of the aircrafts' dynamics. Given the continuous increase in the complexity of aircraft control laws, and the corresponding - crease in the demands on their performance and reliability, industrial control law designers are highly motivated to explore the applicability of new and more powerful methods for design and analysis. The successful application of fully nonlinear control techniques to aircraft control problems o?ers the prospect of improvements in several di?erent areas. Firstly, there is the possibility of - proving design and analysis criteria to more fully re?ect the nonlinear nature of the dynamics of the aircraft. Secondly, the time and e?ort required on the part of designers to meet demanding speci?cations on aircraft performance and h- dling could be reduced. Thirdly, nonlinear analysis techniques could potentially reduce the time and resources required to clear?ight control laws, and help to bridge the gap between design, analysis and?nal?ight clearance. Theaboveconsiderationsmotivatedtheresearchpresentedinthisbook, which is the result of a three-year research e?ort organised by the Group for Aeron- tical Research and Technology in Europe (GARTEUR). In September 2004, GARTEUR Flight Mechanics Action Group 17 (FM-AG17) was established to conduct research on "New Analysis and Synthesis Techniques for Aircraft Control."




Robust Nonlinear Control of Tailless Aircraft


Book Description

The objective of this research was to develop tools leading to effective control strategies for tailless fighter aircraft. Emphasis was placed on the development of control algorithms that yield robust performance in the presence of actuator magnitude and rate limits and that account for the interaction of a pilot with the airframe and control system. The results of this research are documented in the 22 papers that are listed in this report. These papers present the development of numerous new analysis tools for nonlinear control systems with an emphasis on disturbance attenuation and sampled data control. These algorithms were applied to the manual flight control problem for open loop unstable fighter aircraft.




Fully Tuned Radial Basis Function Neural Networks for Flight Control


Book Description

Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. A Lyapunov synthesis approach is used to derive the tuning rules for the RBF controller parameters in order to guarantee the stability of the closed loop system. Unlike previous methods that tune only the weights of the RBF network, this book presents the derivation of the tuning law for tuning the centers, widths, and weights of the RBF network, and compares the results with existing algorithms. It also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks. Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.




Model Predictive Control Synthesis for the Innovative Control Effector Tailless Fighter Aircraft


Book Description

A nonlinear model predictive control law was developed for the Lockheed Martin Innovative Control Effector tailless fighter aircraft to track way points. In general, aircraft are described by nonlinear dynamics that are dependent on the regime of flight. Additionally strict requirements on state and actuator constraints are common to all aircraft. Tailless aircraft are usually overdetermined systems, meaning solutions to control problems are not unique, and the system is non-affine. The proposed nonlinear control law considers those constraints during run-time, and solves the nonlinear control problem for a range of points within different flight regimes. The control law was developed using a computer simulation of the tailless fighter aircraft, and further simulation was used to validate the control law when applied to the aircraft. It was found that the controller was able to track reference step commands in altitude anywhere from sea level to 50,000 ft and remain stable. It is also shown that the single nonlinear controller is able to handle lateral translations at the same time as altitude commands, demonstrating its authority over the entire 6 degree of freedom system. The controller is not real time applicable but research indicates that it is possible to apply such a technique in real time. It was concluded that nonlinear model predictive control is a viable control synthesis technique for tailless fighter aircraft if real-time algorithms can be developed.