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A summary of the YF-16 flight control system is presented. The basic functions of the flight control system are discussed, as well as the unique features such as Relaxed Static Longitudinal Stability (RSS), Fly By Wire (FBW), and Side Stick Pilot's Controller (SSC). In addition, the basic philosophy behind the selection of the flight control system functions and unique features is discussed.
The Autonomous Formation Flight (AFF) project was initiated in 1995 to demonstrate at least 10-percent drag reduction by positioning a trailing aircraft in the wingtip vortex of a leading aircraft. If successful, this technology would provide increased fuel savings, reduced emissions, and extended flight duration for fleet aircraft flying in formation. To demonstrate this technology, the AFF project at NASA Dryden Flight Research Center developed a system architecture incorporating two F-18 aircraft flying in leading-trailing formation. The system architecture has been designed to allow the trailing aircraft to maintain station-keeping position relative to the leading aircraft within +/-10 ft. Development of this architecture would be directed at the design and development of a computing system to feed surface position commands into the flight control computers, thereby controlling the longitudinal and lateral position of the trailing aircraft. In addition, modification to the instrumentation systems of both aircraft, pilot displays, and a means of broadcasting the leading aircraft inertial and global positioning system-based positional data to the trailing aircraft would be needed. This presentation focuses on the design and testing of the AFF Phase 0 research system.
The x-15 flight control and stability system
A flight control actuation system comprises a controller, electromechanical actuator and a pneumatic actuator. During normal operation, only the electromechanical actuator is needed to operate a flight control surface. When the electromechanical actuator load level exceeds 40 amps positive, the controller activates the pneumatic actuator to offset electromechanical actuator loads to assist the manipulation of flight control surfaces. The assistance from the pneumatic load assist actuator enables the use of an electromechanical actuator that is smaller in size and mass, requires less power, needs less cooling processes, achieves high output forces and adapts to electrical current variations. The flight control actuation system is adapted for aircraft, spacecraft, missiles, and other flight vehicles, especially flight vehicles that are large in size and travel at high velocities.
A flight control actuation system comprises a controller, electromechanical actuator and a pneumatic actuator. During normal operation, only the electromechanical actuator is needed to operate a flight control surface. When the electromechanical actuator load level exceeds 40 amps positive, the controller activates the pneumatic actuator to offset electromechanical actuator loads to assist the manipulation of flight control surfaces. The assistance from the pneumatic load assist actuator enables the use of an electromechanical actuator that is smaller in size and mass, requires less power, needs less cooling processes, achieves high output forces and adapts to electrical current variations. The flight control actuation system is adapted for aircraft, spacecraft, missiles, and other flight vehicles, especially flight vehicles that are large in size and travel at high velocities.
The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.
A propulsion-controlled aircraft (PCA) system for emergency flight control of aircraft with no flight controls was developed and flight tested on an F-15 aircraft at the NASA Dryden Flight Research Center. The airplane has been flown in a throttles-only manual mode and with an augmented system called PCA in which pilot thumbwheel commands and aircraft feedback parameters were used to drive the throttles. Results from a 36-flight evaluation showed that the PCA system can be used to safety land an airplane that has suffered a major flight control system failure. The PCA system was used to recover from a severe upset condition, descend, and land. Guest pilots have also evaluated the PCA system. This paper describes the principles of throttles-only flight control; a history of loss-of-control accidents; a description of the F-15 aircraft; the PCA system operation, simulation, and flight testing; and the pilot comments.
The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team is to develop and flight-test control systems that use neural network technology to optimize the performance of the aircraft under nominal conditions as well as stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to the baseline aerodynamic derivatives in flight. This set of open-loop flight tests was performed in preparation for a future phase of flights in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed a pitch frequency sweep and an automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. An examination of flight data shows that addition of the flight-identified aerodynamic derivative increments into the simulation improved the pitch handling qualities of the aircraft.
A flight evaluation was made of the mechanical hydraulic flight control system and the electrohydraulic stability augmentation system installed in the HL-10 lifting body research vehicle. Flight tests performed in the speed range from landing to a Mach number of 1.86 and the altitude range from 697 meters (2300 feet) to 27,550 meters (90,300 feet) were supplemented by ground tests to identify and correct structural resonance and limit-cycle problems. Severe limit-cycle and control sensitivity problems were encountered during the first flight. Stability augmentation system structural resonance electronic filters were modified to correct the limit-cycle problem. Several changes were made to control stick gearing to solve the control sensitivity problem. Satisfactory controllability was achieved by using a nonlinear system. A limit-cycle problem due to hydraulic fluid contamination was encountered during the first powered flight, but the problem did not recur after preflight operations were improved.
The results are presented of application of the methodology of Singular Perturbations and Time Scales (SPATS) to the control of digital flight systems. A block diagonalization method is described to decouple a full order, two time (slow and fast) scale, discrete control system into reduced order slow and fast subsystems. Basic properties and numerical aspects of the method are discussed. A composite, closed-loop, suboptimal control system is constructed as the sum of the slow and fast optimal feedback controls. The application of this technique to an aircraft model shows close agreement between the exact solutions and the decoupled (or composite) solutions. The main advantage of the method is the considerable reduction in the overall computational requirements for the evaluation of optimal guidance and control laws. The significance of the results is that it can be used for real time, onboard simulation. A brief survey is also presented of digital flight systems.
Analysis and design of nonlinear space vehicle flight control systems
Battle damage causing loss of control capability can compromise mission objectives and even result in aircraft loss. The Self Repairing Flight Control System (SRFCS) flight development program directly addresses this issue with a flight control system design that measures the damage and immediately refines the control system commands to preserve mission potential. The system diagnostics process detects in flight the type of faults that are difficult to isolate post flight, and thus cause excessive ground maintenance time and cost. The control systems of fighter aircraft have the control power and surface displacement to maneuver the aircraft in a very large flight envelope with a wide variation in airspeed and g maneuvering conditions, with surplus force capacity available from each control surface. Digital flight control processors are designed to include built-in status of the control system components, as well as sensor information on aircraft control maneuver commands and response. In the event of failure or loss of a control surface, the SRFCS utilizes this capability to reconfigure control commands to the remaining control surfaces, thus preserving maneuvering response. Correct post-flight repair is the key to low maintainability support costs and high aircraft mission readiness. The SRFCS utilizes the large data base available with digital flight control systems to diagnose faults. Built-in-test data and sensor data are used as inputs to an Onboard Expert System process to accurately identify failed components for post-flight maintenance action. This diagnostic technique has the advantage of functioning during flight, and so is especially useful in identifying intermittent faults that are present only during maneuver g loads or high hydraulic flow requirements. A flight system was developed to test the reconfiguration and onboard maintenance diagnostics concepts on a NASA F-15 fighter aircraft.
A flight deflection measurement system is disclosed including a hybrid microchip of a receiver/decoder. The hybrid microchip decoder is mounted piggy back on the miniaturized receiver and forms an integral unit therewith. The flight deflection measurement system employing the miniaturized receiver/decoder can be used in a wind tunnel. In particular, the miniaturized receiver/decoder can be employed in a spin measurement system due to its small size and can retain already established control surface actuation functions.
A viewgraph presentation describing the the six phases of a space mission is shown. The contents include: 1) What Does Planning Involve?; 2) Designing the Flight System; 3) Building the Flight System; 4) Testing the Flight System; 5) Flying the Mission; and 6) Analyzing the Data.
Rotorcraft flight control systems present design challenges which often exceed those associated with fixed-wing aircraft. First, large variations in the response characteristics of the rotorcraft result from the wide range of airspeeds of typical operation (hover to over 100 kts). Second, the assumption of vehicle rigidity often employed in the design of fixed-wing flight control systems is rarely justified in rotorcraft where rotor degrees of freedom can have a significant impact on the system performance and stability. This research was intended to develop a methodology for the design of robust rotorcraft flight control systems. Quantitative Feedback Theory (QFT) was chosen as the basis for the investigation. Quantitative Feedback Theory is a technique which accounts for variability in the dynamic response of the controlled element in the design robust control systems. It was developed to address a Multiple-Input Single-Output (MISO) design problem, and utilizes two degrees of freedom to satisfy the design criteria. Two techniques were examined for extending the QFT MISO technique to the design of a Multiple-Input-Multiple-Output (MIMO) flight control system (FCS) for a UH-60 Black Hawk Helicopter. In the first, a set of MISO systems, mathematically equivalent to the MIMO system, was determined. QFT was applied to each member of the set simultaneously. In the second, the same set of equivalent MISO systems were analyzed sequentially, with closed loop response information from each loop utilized in subsequent MISO designs. The results of each technique were compared, and the advantages of the second, termed Sequential Loop Closure, were clearly evident.
Flight tests conducted with the self-repairing flight control system (SRFCS) installed on the NASA F-15 highly integrated digital electronic control aircraft are described. The development leading to the current SRFCS configuration is highlighted. Key objectives of the program are outlined: (1) to flight-evaluate a control reconfiguration strategy with three types of control surface failure; (2) to evaluate a cockpit display that will inform the pilot of the maneuvering capacity of the damage aircraft; and (3) to flight-evaluate the onboard expert system maintenance diagnostics process using representative faults set to occur only under maneuvering conditions. Preliminary flight results addressing the operation of the overall system, as well as the individual technologies, are included.
Flight tests conducted with the self-repairing flight control system (SRFCS) installed on the NASA F-15 highly integrated digital electronic control aircraft are described. The development leading to the current SRFCS configuration is highlighted. Key objectives of the program are outlined: (1) to flight-evaluate a control reconfiguration strategy with three types of control surface failure; (2) to evaluate a cockpit display that will inform the pilot of the maneuvering capacity of the damaged aircraft; and (3) to flight-evaluate the onboard expert system maintenance diagnostics process using representative faults set to occur only under maneuvering conditions. Preliminary flight results addressing the operation of the overall system, as well as the individual technologies, are included.