Practical methods of calculation involved in the experimental study of an autopilot and the autopilot-aircraft combination
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Commercially available general aviation autopilots are currently in transition from an analogue circuit system to a computer implemented digital flight control system. Well known advantages of the digital autopilot include enhanced modes, self-test capacity, fault detection, and greater computational capacity. A digital autopilot's computational capacity can be used to full advantage by increasing the sophistication of the digital autopilot's chief function, stability and control. NASA's Langley Research Center has been pursuing the development of direct digital design tools for aircraft stabilization systems for several years. This effort has most recently been directed towards the development and realization of multi-mode digital autopilots for GA aircraft, conducted under a SPIFR-related program called the General Aviation Terminal Operations Research (GATOR) Program. This presentation focuses on the implementation and testing of a candidate multi-mode autopilot designed using these newly developed tools.
Two autopilots providing autonomous flight capabilities are presented herein. The first is the Pico-Pilot, demonstrated for the 12-inch size class of micro air vehicles. The second is the MicroPilot MP2028(sup g), where its integration into a 36-inch Zagi airframe (tailless, elevons only configuration) is investigated and is the main focus of the report. Analytical methods, which include the use of the Advanced Aircraft Analysis software from DARCorp, were used to determine the stability and control derivatives, which were then validated through wind tunnel experiments. From the aerodynamic data, the linear, perturbed equations of motion from steady-state flight conditions may be cast in terms of these derivatives. Using these linear equations, transfer functions for the control and navigation systems were developed and feedback control laws based on Proportional, Integral, and Derivative (PID) control design were developed to control the aircraft. The PID gains may then be programmed into the autopilot software and uploaded to the microprocessor of the autopilot. The Pico-Pilot system was flight tested and shown to be successful in navigating a 12-inch MAV through a course defined by a number of waypoints with a high degree of accuracy, and in 20 mph winds. The system, though, showed problems with control authority in the roll and pitch motion of the aircraft: causing oscillations in these directions, but the aircraft maintained its heading while following the prescribed course. Flight tests were performed in remote control mode to evaluate handling, adjust trim, and test data logging for the Zagi with integrated MP2028(sup g). Ground testing was performed to test GPS acquisition, data logging, and control response in autonomous mode. Technical difficulties and integration limitations with the autopilot prevented fully autonomous flight from taking place, but the integration methodologies developed for this autopilot are, in general, applicable for unmanned air vehicles within the 36-inch size class or larger that use a PID control based autopilot.
The Platform Precision Autopilot is an instrument landing system interfaced autopilot system, developed to enable an aircraft to repeatedly fly nearly the same trajectory hours, days, or weeks later. The Platform Precision Autopilot uses a novel design to interface with a NASA Gulfstream III jet by imitating the output of an instrument landing system approach. This technique minimizes, as much as possible, modifications to the baseline Gulfstream III jet and retains the safety features of the aircraft autopilot. The Platform Precision Autopilot requirement is to fly within a 5-m (16.4-ft) radius tube for distances to 200 km (108 nmi) in the presence of light turbulence for at least 90 percent of the time. This capability allows precise repeat-pass interferometry for the Uninhabited Aerial Vehicle Synthetic Aperture Radar program, whose primary objective is to develop a miniaturized, polarimetric, L-band synthetic aperture radar. Precise navigation is achieved using an accurate differential global positioning system developed by the Jet Propulsion Laboratory. Flight-testing has demonstrated the ability of the Platform Precision Autopilot to control the aircraft within the specified tolerance greater than 90 percent of the time in the presence of aircraft system noise and nonlinearities, constant pilot throttle adjustments, and light turbulence.
The Platform Precision Autopilot is an instrument landing system-interfaced autopilot system, developed to enable an aircraft to repeatedly fly nearly the same trajectory hours, days, or weeks later. The Platform Precision Autopilot uses a novel design to interface with a NASA Gulfstream III jet by imitating the output of an instrument landing system approach. This technique minimizes, as much as possible, modifications to the baseline Gulfstream III jet and retains the safety features of the aircraft autopilot. The Platform Precision Autopilot requirement is to fly within a 5-m (16.4-ft) radius tube for distances to 200 km (108 nmi) in the presence of light turbulence for at least 90 percent of the time. This capability allows precise repeat-pass interferometry for the Unmanned Aerial Vehicle Synthetic Aperture Radar program, whose primary objective is to develop a miniaturized, polarimetric, L-band synthetic aperture radar. Precise navigation is achieved using an accurate differential global positioning system developed by the Jet Propulsion Laboratory. Flight-testing has demonstrated the ability of the Platform Precision Autopilot to control the aircraft within the specified tolerance greater than 90 percent of the time in the presence of aircraft system noise and nonlinearities, constant pilot throttle adjustments, and light turbulence.
Five levels of autopilot complexity were flown in a single engine instrument flight rules (IFR) simulation for several different IFR terminal operations. A comparison was made of the five levels of complexity ranging from no-autopilot to a fully coupled lateral and vertical guidance mode to determine the relative benefits vs. complexity/cost of state of the art autopilot capability in the IFR terminal area. Of the five levels tested, the heading select mode made the largest relative difference in decreasing workload and simplifying the approach task. It was also found that the largest number of blunders was detected with the most highly automated mode. The data also showed that, regardless of the autopilot mode, performance during an IFR approach was highly dependent on the type of approach being flown. These results indicate that automation can be useful when making IFR approaches in a high workload environment, but also that some disturbing trends are associated with some of the higher levels of automation found in state of the art autopilots.
A study was performed under contract with NASA-Langley Research Center to document the state of the art of general aviation (GA) autopilots and provide information about the current status of GA autopilot technology. Results are based on findings obtained from general and product literature, as well as interviews with manufacturers, users and service centers. The autopilot systems are divided into three categories - wing leveler, automatic, and integrated flight control systems, and a listing of currently available autopilots and their available options is presented. Various autopilot components are discussed, such as the display, data entry devices, and computers; gyroscopes, altitude sensors, airspeed sensors and accelerometers are presented as the primary sensor types. Electromechanical servos, pneumatic and hydraulic actuators are compared in their ability to improve airframe response. Recommendations concerning potential areas of further research and possible areas of improvement are also presented.
A simplified theory of aircraft vertical acceleration gust response based on a model including pitch, vertical displacement and control motions due to autopilot operation is presented. High-order autopilot transfer functions are utilized for improved accuracy in the determination of the overall response characteristics. Four representative commercial jet aircraft were studied over a wide range of operating conditions and comparisons of individual responses are given. It is shown that autopilot operation relative to the controls fixed case causes response attenuation of from 10 percent to approximately 25 percent depending on flight condition and increases in crossing number up to 30 percent, with variations between aircraft of from 5 percent to 10 percent, in general, reflecting the differences in autopilot design. A detailed computer program description and listing of the calculation procedure suitable for the general application of the theory to any airplane autopilot combination is also included.
This paper presents the designs of Proportional-Integral-Filter (PIF) autopilots for a General Aviation (NAVION) aircraft. The PIF autopilots use modern control theory to determine heading select and altitude select and hold autopilot modes. The PIF control law uses typical General Aviation sensors for state feedback; command error integration for command tracking; digital complimentary filtering and analog prefiltering for sensor noise suppression; a control filter for computation delay accommodation; and the incremental form to eliminate trim values in implementation. Theoretical developments for the control law are described which combine the sampled-data regulator with command generator tracking for use as a digital flight control system. The digital PIF autopilots are evaluated using closed-loop eigenvalues and simulations. Successful flight test results for the PIF autopilots are presented for different turbulence conditions and quadratic weights.
The designs of Proportional-Integrated-Filter (PIF) auto-pilots for a General Aviation (NAVION) aircraft are presented. The PIF autopilot uses the sampled-data regulator and command generator tracking to determine roll select, pitch select, heading select, altitude select and localizer/glideslope capture and hold autopilot modes. The PIF control law uses typical General Aviation sensors for state feedback, command error integration for command tracking, digital complementary filtering and analog prefiltering for sensor noise suppression, a control filter for computation delay accommodation and the incremental form to eliminate trim values in implementation. Theoretical developments described in detail, were needed to combine the sampled-data regulator with command generator tracking for use as a digital flight control system. The digital PIF autopilots are evaluated using closed-loop eigenvalues and linear simulations. The implementation of the PIF autopilots in a digital flight computer using a high order language (FORTRAN) is briefly described. The successful flight test results for each PIF autopilot mode is presented.
Five levels of autopilot complexity were flown in a single engine IFR simulation for several different IFR terminal operations. A comparison was made of the five levels of complexity ranging from no autopilot to a fully coupled lateral and vertical guidance mode to determine the relative benefits versus complexity/cost of state-of-the-art autopilot capability in the IFR terminal area. Of the five levels tested, the heading select mode made the largest relative difference in decreasing workload and simplifying the approach task. It was also found that the largest number of blunders was detected with the most highly automated mode. The data also showed that, regardless of the autopilot mode, performance during an IFR approach was highly dependent on the type of approach being flown. These results indicate that automation can be useful when making IFR approaches in a high workload environment, but also that some disturbing trends are associated with some of the higher levels of automation found in state-of-the-art autopilots.
An important feature in General Aviation (GA) autopilots is the ability to intercept and hold the glideslope and localizer during a landing approach. Most General Aviation landing approach autopilots available today use analog systems. This paper presents the designs of digital landing approach autopilots for a General Aviation (NAVION) aircraft using modern linear quadratic control theory. Each constant gain, direct digitally designed autopilot operates synchronously at a slow rate (10 samples per second) and has modest memory requirements, i.e., a full state Kalman filter is not used. The autopilot is designed to track desired position trajectories constructed in an ILS or MLS terminal area using command generators. Alternative command errors for intercepting and holding the localizer beam centerline are investigated. Linear simulations and flight test results are presented demonstrating the successful application of the linear quadratic regulator approach.
In this presentation we will explore several distributed consensus algorithms developed to maintain coordination among a fleet of heterogeneous UAS subject to external disturbances. An overview of the network assumptions and autopilot performance bounds required to meet the coordination objective will be provided. In particular, we will leverage passivity-based stability conditions for bidirectional networks that require the communication graph to be connected in an integral sense, but may fail to connect pointwise in time during the entire mission. Non-ideal autopilots that can only track a desired speed profile with a prescribed precision induce an error in vehicle coordination. The autopilot performance bounds will be propagated through the coordination dynamics to understand the limits introduced by autopilots.
Digital autopilots for the manned command module earth orbital and lunar missions using program COLOSSUS 3 are discussed. Subjects presented are: (1) reaction control system digital autopilot, (2) thrust vector control autopilot, (3) entry autopilot and mission control programs, (4) takeover of Saturn steering, and (5) coasting flight attitude maneuver routine.
In Project SKYLAB, the Command and Service Module which ferries astronaut crews to and from the Orbital Workshop is required to have the capability of providing attitude control for the entire Orbital Assembly during docked phases of the mission. A digital autopilot has been designed which meets this requirement. It is a direct descendant of the digital autopilot designed for and used extensively in project Apollo. There is a major difference however. For Apollo, it was reasonable to design an autopilot that treated the roll, pitch, and yaw axes independently. Because of the geometry of the Orbital Assembly, however, it is of considerable advantage to design the jet selection logic for SKYLAB such that the roll and pitch axes are treated as coupled, and also that the roll and yaw axes are treated as coupled. This paper discusses how inter-axis dependence has been incorporated in the Command and Service Module's digital autopilot while working within the limitations of the onboard computer.
Five levels of autopilot complexity were flown in a single engine IFR simulation for several different IFR terminal operations. A comparison was made of the five levels of complexity ranging from no-autopilot to a fully coupled lateral and vertical guidance mode to determine the relative benefits vs. complexity/cost of state-of-the-art autopilot capability in the IFR terminal area. For the levels of progression tested, the heading select mode made the largest difference in decreasing workload and simplifying the approach task. It was also found that the largest number of blunders was detected with the most fully automated mode. The data also showed that, regardless of the autopilot mode, performance during an IFR approach was highly dependent on the type of approach being flown. These results indicate that some level of automation is desirable when making IFR approaches in a high workload environment, but also that some disturbing trends are associated with the higher levels of automation.
The design of advanced Automatic Aircraft Control Systems (AACS's) can be improved upon considerably if the designer can access all models and tools required for control system design and analysis through a graphical user-interface, from within one software environment. This MSc-thesis presents the first step in the development of such an environment, which is currently being done at the Section for Stability and Control of Delft University of Technology, Faculty of Aerospace Engineering. The environment is implemented within the commercially available software package MATLAB/SIMULINK. The report consists of two parts. Part I gives a detailed description of the AACS design environment. The heart of this environment is formed by the SIMULINK implementation of a nonlinear aircraft model in block-diagram format. The model has been worked out for the old laboratory aircraft of the Faculty, the De Havilland DHC-2 'Beaver', but due to its modular structure, it can easily be adapted for other aircraft. Part I also describes MATLAB programs which can be applied for finding steady-state trimmed-flight conditions and for linearization of the aircraft model, and it shows how the built-in simulation routines of SIMULINK have been used for open-loop analysis of the aircraft dynamics. Apart from the implementation of the models and tools, a thorough treatment of the theoretical backgrounds is presented. Part II of this report presents a part of an autopilot design process for the 'Beaver' aircraft, which clearly demonstrates the power and flexibility of the AACS design environment from part I. Evaluations of all longitudinal and lateral control laws by means of nonlinear simulations are treated in detail. The AACS design environment from part I proved to be a very useful tool for designing the control laws of the 'Beaver' autopilot within a very tight time-schedule. The autopilot design process itself will be used as a guideline for future AACS research at the Faculty of Aerospace Engineering. Flight tests of the 'Beaver' autopilot, done after evaluating the control laws in the SIMULINK package, proved to be quite successful. In the future, the AACS design package will evolve into a standardized, integrated design environment which can be applied to virtually any type of aircraft. The AACS design cycle will be shortened further by developing tools for automatically porting control laws from the MATLAB/SIMULINK environment to a piloted real-time flight simulator and the Flight Control Computers of the aircraft.
Aviation and cognitive science researchers have identified situations in which the pilot's expectations for behavior of autopilot avionics are not matched by the actual behavior of the avionics. These "automation surprises" have been attributed to differences between the pilot's model of the behavior of the avionics and the actual behavior encoded in the avionics software. A formal technique is described for the analysis and measurement of the behavior of the cruise pitch modes of a modern Autopilot. The analysis characterizes the behavior of the Autopilot as situation-action rules. The behavior of the cruise pitch mode logic for a contemporary modern Autopilot was found to include 177 rules, including Level Change (23), Vertical Speed (16), Altitude Capture (50), and Altitude Hold (88). These rules are determined based on the values of 62 inputs. Analysis of the rule-based model also shed light on the factors cited in the literature as contributors to "automation surprises."