Mark R. Anderson

Closed-loop pilot vehicle analysis of the approach and landing task

Optimal-control-theoretic modeling and frequency-domain analysis is the methodology proposed to analytically evaluate the handling qualities of higher-order manually controlled dynamic systems. Fundamental to the methodology is evaluating the interplay between pilot workload and closed-loop pilot /vehicle performance and stability robustness. The model-based metric for pilot workload is the required pilot phase compensation. Pilot/vehicle performance and loop stability is then evaluated using frequency-domain techniques. When these techniques were applied to the flight-test data for thirty-two highly-augmented fighter configurations, strong correlation was obtained between the analytical and experimental results.

PILOT-INDUCED OSCILLATIONS INVOLVING MULTIPLE NONLINEARITIES

A pilot-induced oscillation is a type of instability caused by dynamic couplingbetween the pilot and the aircraft. Linear system analysis reveals that the pilot/aircraft system is unstable during the oscillation event. However, nonlinearities in the feedback system can limit the response variables so that a sustained, constant amplitude limit cycle results. A method is presented to analyze the limit cycle behavior of pilot/aircraft systems as a means of understanding pilot-inducedoscillations and their causes. A new computationaltechnique is considered and a new methodof testing limit cycle stability is presented. An analysisof the YF-12 pilot-inducedoscillation characteristics is used to demonstrate the method.

Mixed H2/H-infinity optimal control for an elastic aircraft

A mixed //2/floo optimal control design and its application to a flight control problem of B-l aircraft is studied. The mixed #2/ 00 optimal control design is one of finding an internally stabilizing controller that minimizes the //2/#oo performance index subject to an inequality constraint on H^ norm. The application is a linear model of longitudinal motion of B-l aircraft. A standard eigenvalue problem that involves linear matrix inequalities is formulated, and efficient interior point algorithms are used to solve this problem numerically. Results show that this mixed //2/#oo optimal design leads the designer into a tradeoff between HI and HQQ objectives. Through this method, a designer can determine the controllers that result in the desired closed-loop noise rejection properties and stability robustness.

Error dynamics and perfect model following with application to flight control

The role of the system error dynamics in model-following control systems is presented in a unified theoretical framework. The approach clearly exposes the requirements for perfect model-following control laws to exist. The error dynamics selected are shown to determine if implicit or explicit following results, and the effects of these error dynamics and plant and model dynamics on the closed-loop stability, performance, and control system architecture are exposed. The importance of model and plant transmission zeros is also revealed. A new linear quadratic formulation is offered that can yield perfect model-following controllers, but guarantees internal system stability, unlike algebraic solutions for the control law. Further, the case of finite actuation bandwidth may be treated with the linear quadratic approach. The error dynamics are also shown to be key in this linear quadratic model-following formulation. The paper concludes with an example involving an unstable forward-swept-wing elastic aircraft, which demonstrates that high-fidelity model-following control laws can be synthesized for statically unstable aircraft with nonminimum phase transmission zeros.

ROBUSTNESS EVALUATION OF A FLEXIBLE AIRCRAFT CONTROL SYSTEM

The structured singular value analysis technique is used to generate stability and performance robustness guidelines for inultivariable, flexible aircraft flight control systems. A stability augmentation and structural mode control system, designed using the same classical technique as on the original production aircraft, is evaluated to produce the new guidelines. Stability margins are computed for simultaneous gain and phase uncertainty in each of the control system feedback loops. Performance weighting filters are chosen specifically from military flying qualities specifications. The results of this research define exactly how robust a control system of this type should be, such that any performance improvements achieved using more advanced design techniques can be compared directly.

Evaluation Methods for Complex Flight Control Systems

Flight conpol system verification requires an analytical comparison of system characteristics to the control system specification MIL-F-9490 and the appropriate flying quality specifications MIL-F-8785, MIL-F-8330, or MILSTD-1797. These evaluations become increasingly difficult, however, as the design trend towards increased control system integration, sophistication, and coupling continues. This paper documents several extensions to existing methods for evaluating system stability margins and producing low order equivalent models (for flying qualities evaluations) of complex aircraft flight control systems which may include over one-hundred states. I. Introduction Safety is the motivation for extensive analytical control system evaluations prior to first flight. Flight control system verification requires a comparison of system characteristics to the control system specification[1] and the appropriate flying quality ~~ecifications[~ *~~~]. However, these control system evaluations become increasingly difficult as the design trend towards increased control system integration, sophistication, and coupling continues. For example, propulsion and airframe control systems used to be reasonably decoupled; therefore, their control systems could be evaluated separately. Future generation aircraft will incorporate improved performance integrated flight and propulsion control systems and decoupling for evaluation purposes will not be possible. Undoubtedly, future generation aircraft will require specialized methods to evaluate their characteristics with the applicable military specification. The models which are needed to describe these aircraft will be very high order, perhaps over one hundred states, and will be very complex. Therefore, algorithms needed for specification evaluation must be able to handle very large order models efficiently. Two computationally burdensome tasks in flight control specification evaluation are calculating stability margins and producing low order equivalent system models. Both tasks require manipulation of the highest fidelity linear aircraft models available for accurate results. This paper will therefore concentrate on the modifications and extensions to existing methods necessary to

The significance of error dynamics in model-following for flight control design

The role of the system error dynamics in model-following control systems is discussed, along with the use of handling quality specifications, actuation bandwidth constraints, stability, and closed-loop performance requirements in flight control design. The model-following problem is formulated using both direct state-space and linear, quadratic, optimization techniques. The results are then demonstrated using several examples involving a generic forward-swept-wing vehicle and a conventional flight vehicle with large parameter uncertainty in order to illustrate the trade-off in closed-loop performance and control law complexity.

Analytical development of an equivalent system mismatch function

A mismatch function is used to check the validity of a low-order equivalent system model that has been derived from a high-order system representation. If the difference between the low- and high-order models is greater than allowed by the mismatch function, the flying qualities predictions obtained from parameters of the low-order equivalent system may not be representative of the ratings a pilot would give the actual aircraft. A methodology is developed in this paper to derive equivalent system mismatch functions analytically. The methodology is used to analytically determine a mismatch function for the longitudinal axis of a class IV fighter aircraft in the category A, nonterminal flight phase.

Drag function modeling air traffic simulation

VII. Conclusions The control design problem of an automatic pilot for formation flight control has been analyzed and decomposed into two uncoupled linear single-input, two-output dynamic tracking control system design problems, which correspond to the y and x channels, respectively. This, in turn, results in the efficient design of a PI formation-hold autopilot that uses a mix of separation errors and maneuver errors. The formation-hold autopilot is an extension of the conventional heading-hold and Mach-hold autopilots. However, the formation control problem involves two flight vehicles and their accurate relative positions. The formation flight control problem considered here is significant in view of its direct operational importance: It affords the automation of the coordination of a leader/wingman flight, the design of a robotic wingman, and the automatic control of aircraft during maneuvers such as aerial refueling. It is also interesting in view of the novel and nontrivial control theoretic problems that it poses.

Aircraft threat modeling from performance data

A procedure is developed to construct simplified dynamic aircraft models for use as threats in air combat training simulators. Performance data in the form of excess power and energy maneuverability curves are used to define the lift and drag characteristics of the models. A parameter identification method is used to extract model parameters directly from the performance curves. The method therefore insures that the threat model performance matches that of the actual threat. Simplified threat models of two modern fighter aircraft are used to demonstrate the modeling procedure.