We have been working for some time on a way to estimate and display important flight parameters such as angle of attack, estimated airspeed (on UAVs that do not have Pitot tubes), side slip angle or flight path vector (FPV) using a simple, robust dynamical model of the UAV and a computational method that is both fast and has computational time guarantees.

Using a hybrid systems approach, the problem boils down to finding a set of analytical solutions to least squares problems, and to identify which solution is the most likely based on an analysis of the residuals. The method executes in real time, at 50 Hz, on an APM. We tested it using hardware-in-the-loop simulation (with X-Plane). As you can see from the video, the real and estimated airspeed closely match (we added some noise to the X-Plane generated IMU data to simulate the actual performance of the APM's IMU), and the FPV/AOA/sideslip evolve realistically.

Because the dynamical model used in this algorithm is fairly robust, it requires only a small number of parameters to work. More details on our WIP paper at RTAS 2014: https://www.mpi-sws.org/~bbb/proceedings/rtas14-wip-proceedings.pdf

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  • Understood. Anyway I rather use a static device to get rid of the inertia related issues.


    Note the second hole. It provides the information needed to have an AOA indication.

    If you have some manufacturing capabilities you can Do It Yourself.

    Parameters identification is more fascinating to me, anyway I figure it's all down to personal taste.

  • T3

    The first one looks very well suited to model airplanes. I think the low airspeed in combination with rotation resistance is the largest obstacle to overcome, but I imagine it is do-able. You would need a very lightweight flying surface attached to the potentiometer. Really, knowing the exact AOA is not all that important, what IS important is knowing the reference (indicated) AOA that the airplane stalls at. Many useful calculations could be derived from that. 

  • Nevertheless you can buy this kind of sensor 


    Or alfa beta vanes of reduced dimensions


  • It's hard to find a proper installation position. Sensor operation is affected by plane flight condition. Sensor need calibration.

  • There are a few reasons why making a vane like this isn't trivial.

    1. Aircraft dynamics scale inversely with aircraft size. As you might expect, a Jumbo Jet does wobble in the air and takes minutes to perform turns. This isn't just a pilot option: The mechanical system that makes the plane has slower responses and its dynamic response spans only a few Hz. As a rule of thumb, each time you scale a model down in half, its dynamics scale upwards by four. That allows your RC plane to do a full roll in less than a second, but it also means that the relative quantities change much faster. It is considered in bibliography that in small scale UAVs (2m wingspan) you need to sample your sensors at about 100Hz, in order to capture the full dynamic content of changes. This requires much faster and accurate sensors.
    2. While the model can scale down, the atmosphere around it doesn't. That means that a wind vane must have enough of a surface to capture the wind characteristics while moving at a considerable speed, for the steady flow to dominate the turbulence. This just isn't practical in a scale model which spans a few inches and flies at a few m/s.
    3. While the model scales down, the individual components can't follow as easily. What you showed in your picture is a sensor which weighs a few kg total, a big part of which is just the precision rotary encoder and its interface. While this was negligible in a multi-ton aircraft, it's a serious payload in a foam plane. Let alone the cost ratios. Another example of this is the fact that mechanical and laser gyros never scaled down enough to be mounted on rc planes. We had to wait for MEMS technology to have access to IMU data.
  • T3

    Why is it so hard to have a direct measurement of AoA? What if we made a vane like the one below? 


  • Thank you all for sharing.

    As Georacer previously stated angle of attack direct measurement can be a problem for little airframes. That problem is also present for real size planes, at high flight speeds.

    The base for this kind of estimation is the accurate knowledge of real plane dynamics. The issue is to reduce at minimum the flight test activities.

    For a small plane, with a simple reliable Pitot, is possible to get a good AOA indication.  

    As soon as Open Air Data Computer project produces a reliable data system I hope it will be possible to work on AOA identification also on DIY little platforms.

    Suppose you have the whole airplane polar. You flight at 100 km/h at 50 m altitude and the plane weight is 2 kg. With that data you can look-up the angle of attack. The problem is how hard you should work to have that information.

    I can lend a hand on the topic

  • Thanks for the response, SHAQURMZ. It's good to hear that X-Plane is a viable asset for research, as well.

    I have experienced the problem with response and parameter mismatch in FlightGear, so this is why I asked: I had fully defined the parameters of the aerodynamic coefficients and the motor thrust in a custom airplane, made test flights with manual control, accessed all possible data via the data server which FlightGear can raise and then ran Least Squares estimation on the responses, eg on the longitudinal axis.

    The resulting aerodynamic coefficients came up different than the ones specified! Given that the dynamic model was supposed to be fully known and the estimation procedure still coming out flowed, I took this as a bad sign. So I built a simulator from scratch in ROS, which was the right step towards robotic system integration anyway.

    Thanks for the interesting thread guys.

  • Hi Georacer, An analytical expression of the airspeed is copmuted offline before implenting in the code. It is the one that minimizes the L2 norm of the difference between the nonlinear (actual model) and the linear mode or the error as you mentioned in your comment. What is implemented in the code is an anlytical function of airspeed as a function of model parameters, IMU measurements and control inputs.

    Yes you are right the knowledge of the aerodynamical model is required. X-Plane has several capabilities in designing your aircraft. I know it is not open as flightgear but it is still good enough to give you good representation of your aircraft. For, example, X-plane has the capability to specify the airfoil characteristic (lift, drag, pitching moment), Engine/throttle specifications, mass properties and some other parameters related to forces and torques (I didnn't explore them all yet). In X-plane you want find a place where you just input your 6-dof model, but you can express your dynamics by chosing the correct values for the parameters set by x-plane. This is how x-plane is built, to make it more user friendly I think. One good approach is to use the actual flight data and the x-plane flight data like in our case. We use flight data from flight tests using RC C17 airframe and x-plane data. Then you go into a process of dual tuning in order to make your x-plane model as much as possible describing your actual airframe. We are currently working on developing a system for fast, low computation in flight model identification that can be a good feature in arduplane code. We will keep you posted whenever we have updates related to this.

  • Andrew, looking to hear from you more about your work.

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