Study Of Flight Control Platform And Attitude Fusion Algorithms For Mini Autonomous Helicopter

The unmanned aerial vehicle (UAV) has been playing an important role in "dull, dirty, or dangerous" missions where human intervention is considered difficult or dangerous. Due to the advantage of small size, low cost, vertical take off and landing ability, hovering ability, maneuverability, good concealment ability, no casualties and strong viability in the battlefield, the study of mini autonomous helicopter (MAH) has been one of the most interesting research fields in the world.The development of flight control platform is the linchpin before the realization of MAH's autonomous flight. The main work of this dissertation is giving the systematic and complete theoretic design, realization and experimental validation of a flight control platform and attitude fusion algorithms according to the low cost and low weight requirement for MAH, including the hardware selection and integration of flight control system, sensor calibration, design, realization and experimental validation of two GPS acceleration compensation based low cost MARG sensors attitude fusion algorithms and a low time consuming MARG sensors attitude fusion algorithm based on switch technology, design and realization of cascade GPS/SINS integrated navigation system and engine speed controller for mini UAV. The key parts of this dissertation are the research on attitude fusion algorithms for low cost MARG sensors. We believe that the outcome of this dissertation can provide powerful ensurence for system idenfication and autonomous flight control of MAH. The main work of this dissertation is:1. The background and significance of this dissertation are presented and the current progress of MAH is introduced, then a brief introduction to attitude determination technologies of UAV is given, and finally the research purposes, contents and organization of this dissertation are shown.2. The hardware design and realization scheme of flight control system is presented, then the error models of key sensors are analized, finally a recursive least squares based ellipsoid hypothesis calibration algorithm suitable for low cost strapdown accelerometers and magnometers is presented.3. Because the translational acceleration may affect accelerometer output and result in performance reduction of accelerometers and magnetometers based low cost MARG sensors attitude determination system, the GPS-derived acceleration is introduced to improve the attitude measurement accuracy during maneuvers. Firstly, the translational acceleration is derived from GPS velocity through three order optimal differentiator and its accuracy is experimental validated. Then the GPS-derived acceleration and accelerometers' output are used to form the specific force vector observation equation. Finally two GPS acceleration compensation based low cost MARG sensors attitude fusion algorithms are proposed. The first algorithm employs an iterative least square attitude determination algorithm to determine the MRPs attitude from the specfic force and magnetic field vector observations, then MPRs attitude is then fused with the measurements of rate gyros using complementary filter, the observation delay and singularity of MRPs are also considered. The other algorithm employs linear pseudo-measurement equation to transform the nonlinear system with delayed measurement to a linear system with state dependent noises and temporal correlated observation noises, and gives the corresponding linear kalman filter design.4. A low time consuming MARG sensors attitude fusion algorithm based on switch technology is presented. The algorithm is composed of two complementary filters that estimate gravity and magnetic field vectors, and the filter performance is analyzed. To reduce the undesirable effect of translational acceleration, the gravity field complementary filter may switch to open loop integration using gyros' output during maneuver. Analysis indicates that the estimation error of the proposed switched system is bounded under certain switching condition. Simulations and experiments have been carried out to verify the performance of the proposed algorithms in Chapter 3 and Chapter 4, both simulation and experimental results show that the three algorithms are superior in steady state accuracy and dynamic performance, and can fulfil the autonomous flight requirements of the unmanned autonomous helicopter using low cost MARG sensors.5. The cascaed GPS/SINS integrated navigation structure is adopted on the basis of attitude estimates in Chapter 3 and Chapter 4, and a velocity and position estimate algorithm using complementary filter is given. The algorithm employs two complementary filters to estimate velocity and position of the MAH relative to ground station. This method is easy to realize, low time consuming and suitable for short voyage MAH. The experimental results show that the algorithm possesses good navigation accuracy and can fulfil the autonomous flight requirements of MAH.6. The design and implementation scheme of an engine speed controller that adopts the control algorithms of feed forward and fuzzy tuned PI is presented. The proposed engine speed controller is then applied to the engine speed control of OS MAX 70SZ, YS 91 ST and Rotax 582 engines, the experimental results have shown that the controlled engine possess excellent disturbance rejection peformance and can hold its speed constant well under load disturbance. This method is feasible and can be benfit for engine speed control of other MAHs.7. The main work of the dissertation is summarized and recommendations for future research are presented.