Nonlinear Dynamic Inversion Baseline Control Law Flight-Books Pdf

Nonlinear Dynamic Inversion Baseline Control Law Flight
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angular rate vector p q r, fbk angular rate feedback. I Introduction, N onlinear dynamic inversion NDI as a control architecture has been investigated for years and it is now being. applied to new production vehicles 1 2 Therefore the intent of this paper is not to prove the viability of this type. of control scheme but to discuss implementation details for a simple NDI control law for the Full scale Advanced. Systems Testbed FAST F A 18 airplane McDonnell Douglas now The Boeing Company Chicago Illinois The. control law is hosted in a research processor with build in protection restricting the available envelope This. architecture is designed specifically to be a baseline controller upon which advanced control elements can be easily. added and will enable further control research into adaptive controls3 10 and the control of flexible structures 11 12. The NDI control law is a first step toward building a working environment in which design changes and new. research objectives can be quickly brought to flight and their real behavior ascertained The choice of dynamic. inversion was driven by the mathematically and kinematically intuitive architecture explicit model following. behavior the ability to be used to introduce fundamental level simulated failures within the aerodynamic model for. testing the performance of advanced control elements and because it can be included in the stability proofs for many. advanced control schemes 3, The focus of this paper is to present the flight test results for the baseline NDI control law design outlined in. Ref 13 with special attention given to the comparisons between the simulation predictions and flight Additionally. aspects of the design that performed better than expected are presented as well as some simple improvements that. will be suggested for follow on work Flight data are evaluated against the same handling qualities metrics used in. design 13 and flight determined stability margins are presented Finally pilot comments and ratings for two. closed loop tracking tasks are presented and are considered the final necessary piece of the data required to. definitively ascertain the actual handling qualities for the NDI F 18 system and highlight areas where. improvements are warranted, II Background, The control law that is the subject of this paper has been designed to be an available baseline control law for the. FAST platform The FAST platform is fundamentally a single seat F A 18 airplane as shown in Fig 1 and Fig 2. Substantial research instrumentation structural air data and inertial was installed on this airplane to support the. Active Aeroelastic Wing AAW program 14 The robust nature of the testbed structural load capacity spin and. recovery characteristics and reversion to production control laws along with the research instrumentation enable. flight testing of novel control laws with minimal validation testing requirements for a piloted flight vehicle. Figure 1 The Full scale Advanced Systems Testbed F A 18 airplane in flight. American Institute of Aeronautics and Astronautics. Figure 2 The control surfaces of the F A 18 airplane. Figure 3 shows the control computer architecture for FAST The system maintains the advantages of the. production system and utilizes its redundancy management architecture for sensor selection and actuator signal. management The FAST research flight control computer architecture which builds upon legacy F A 18 research. systems consists of two separate research processing capabilities The Research Flight Control System RFCS. provides a minimal delay quad redundant processing environment in which Ada programmed experiments can be. executed The RFCS also performs some envelope protection for restricting where a given research control law. hosted in either the Airborne Research Test System ARTS or RFCS can remain engaged as shown in Fig 4 The. ARTS with its more capable processor and the ability to host Simulink The MathWorks Natick Massachusetts. autocode or C code provides a more flexible environment for novel control laws than does the RFCS however the. ARTS is only dual redundant and imparts one additional frame of delay to commands This extra frame of delay. translates to 0 0125 seconds for the pitch and roll axes and 0 025 seconds for the yaw axis. American Institute of Aeronautics and Astronautics. Figure 3 The Full scale Advanced Systems Testbed Research Flight Control System Airborne Research Test. System control computer architecture, Figure 4 The Full scale Advanced Systems Testbed flight envelope and flight conditions.
American Institute of Aeronautics and Astronautics. The FAST research system has three operational modes disengaged armed and engaged Data passes between. the production and research processors in all three modes but research control laws are only in control of the aircraft. in the engaged state The pilot can disengage the system at any time using the autopilot disengage switch and return. control to the production control laws This architecture provides researchers the opportunity to observe the research. control law behavior in the disengaged and armed states prior to engaging it and allows the reversion to the. well known and robust production control law in the event that the research control law exhibits undesirable. In addition to the flight assets a simulation facility provides a hardware in the loop environment for design and. testing of new control techniques The facility consists of an F A 18 test bench with flight control hardware a full. nonlinear simulation environment and hardware ARTS units Without this facility rapid design and prototyping. would not be possible, III Control Law Description. The NDI control law considered here was implemented in the ARTS and contains a number of distinct. components as depicted in Fig 5 each with their own design goals and functions At the core of the control law is. the actual dynamic inversion which computes the surface positions necessary to achieve the desired aircraft. dynamics using the equations of motion and in this case simplified aerodynamic tables from the simulation These. desired aircraft dynamics are computed from the pilot stick commands via the use of transfer function based. reference models The goal is to give the pilot the type of vehicle response desired and expected however as with. any real system the model used in the inversion cannot be expected to exactly predict the actual behavior of the. vehicle Therefore a compensator must be added to provide the necessary robustness to these modeling. inaccuracies This compensation is accomplished by adding a proportional plus integral compensator that is. intended to drive down the error between the desired dynamics and the actual dynamics Structural filters are also. needed to attenuate the structural vibration from the feedback sensors to prevent any kind of undesirable. aeroservoelastic interactions This basic and simple architecture was chosen based on its applicability to adaptive. flight control research 6 7 however it need not be limited to adaptive control research 11 12 Reference 13 contains a. detailed description of the control law under test and presents the simulation performance predictions. Figure 5 Block diagram of the nonlinear dynamic inversion control law. IV Development Schedule, An aggressive development schedule was executed enabled by the fact that the test system architecture was. designed with rapid prototyping in mind Table 1 shows some of the important milestones for the NDI development. It is worth noting that the NDI was the first closed loop control law designed and implemented by the test team. Despite the team s relative inexperience with the asset the NDI was taken from concept to flight in a little over four. months completing verification and validation testing in just under one month This kind of aggressive schedule is. facilitated by the design of the fourth generation ARTS ARTS IV and RFCS architecture and the fact that the. F A 18 airplane is a robust vehicle especially when operated within the envelope shown in Fig 4. American Institute of Aeronautics and Astronautics. Table 1 The development schedule for nonlinear dynamic inversion. Concept preliminary design review 5 18 2010, Start software verification and validation with NDI version 1 0 8 16 2010. Complete software verification and validation with NDI version 1 4 9 10 2010. First flight version 1 4 flight 112 9 27 2010, First flight version 1 5 flight 114 10 22 2010. Final NDI flight flight 117 11 29 2010, V Flight Test Results.
A total of six research flights were flown with the baseline NDI control law at various flight conditions FCs. within the envelope shown in Fig 4 Three test pilots accumulated approximately five total flight hours on the. control law This limited number of flight hours is in no way sufficient to definitively state that the control law has. been fully explored however a number of different maneuvers and FCs were tested to highlight the strengths and. weaknesses of the NDI These maneuvers included three axis frequency sweeps doublets bank captures. steady heading sideslips 360 rolls wind up turns loaded rolls air to air tracking and in trail formation flight The. following discussions highlight the findings of the limited flight testing performed on the control law along with. comparisons to the predictions from the simulation 13. A Simulation to Flight Comparisons and Handling Qualities Metrics. The nonlinear simulation was used to evaluate the design both from a safety and mission success point of view. It was used to evaluate the predicted handling qualities along with other design requirements Therefore it is. necessary to evaluate the accuracy of these simulation predictions both qualitatively and quantitatively Flight data. can also be evaluated against the handling qualities metrics to evaluate the quality of the handling qualities. predictions The results discussed below highlight the comparisons between the simulation and flight from both an. open and closed loop standpoint All of the analyses presented use piloted frequency sweeps flown through the. pilot stick and rudder pedals The open loop frequency responses are reconstructed from the closed loop responses. by identifying the individual components from Fig 5 and recombining them in the frequency domain to form the. open loop frequency response A method for determining frequency responses from flight data is presented in Ref. 1 Stability Margins and Open Loop Frequency Responses. Open loop frequency responses and stability margins were used to tailor the NDI design Therefore comparisons. between simulator predictions and actual flight determined margins and responses provide valuable insight into the. quality of the design tools and can be used to direct research to improve simulation models The application of linear. stability margins to a nonlinear control law in a nonlinear flight environment does not provide any guarantees of. stability or robustness however it is common practice15 to evaluate fundamentally nonlinear problems in the linear. regimen based on the assumption that the system behaves approximately linearly in a small region around. equilibrium Linear stability margins can be used to quantify the sensitivity of a nonlinear system to a class of linear. uncertainties Larger margins suggest that stability will likely be maintained in the presence of uncertainties that. affect either the loop gain of the system or its phase. Figure 6 shows a representative example of the pitch axis reconstructed open loop frequency response of pitch. rate error to filtered pitch rate Since there are not significant differences between the results for the different FCs. and FC4 had the best overall coherence not plotted it is presented as the example open loop pitch frequency. response in Fig 6 It is clear that the simulation predicted the flight characteristics very well especially the phase. response This high quality phase prediction suggests that the simulation accurately accounts for the primary sources. of delay for the entire system The most obvious discrepancy is the apparent offset in the magnitude plot in Fig 6 It. is clear that the flight pitch loop gain is nearly universally offset by a constant magnitude The fact that this. discrepancy is apparent in the magnitude of the loop and not in the phase suggests that the cause is either the pitch. effectiveness of the pitch surfaces likely symmetric stabilator or arises from the fact that the commanded surface. positions may not exactly match the actual resulting surface positions unlikely but not fully explored In either. case the result is that slightly less pitch rate is being generated for a given command than was predicted by the. American Institute of Aeronautics and Astronautics. simulation In the simulation model an overprediction of stabilator effectiveness of 10 to 20 percent resulted in. responses that look very similar to Fig 6 This result actually has a beneficial effect on most of the stability margins. As can be seen in Fig 6 and Fig 7 the reduced overall magnitude of the open loop response shifts the gain. crossover to the left lower frequency which results in a slight increase in phase margin The fact that the phase plot. in Fig 6 is unaffected means that the phase angle crossover frequency is unchanged and therefore higher gain. margins result from the reduced magnitude plot This gain shift also results in lower bandwidth for pilot control the. control law is hosted in a research processor with build in protection restricting the available envelope This architecture is designed specifically to be a baseline controller upon which advanced control elements can be easily added and will enable further control research into adaptive controls3 10 and the control of flexible structures 11 12

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