Abstract
In this paper, a complete nonlinear dynamic unmanned helicopter model considering wind disturbance is proposed to achieve realistic simulations and teasing out the effect of wind on the control system. The wind velocity vector which is horizontal as seen in the inertial frame can be obtained by subtracting the airspeed measured by atmospheric data computer from the inertial speed measured by GPS. The design of the controller fully considers the existence of wind, and the wind disturbance is suppressed by the method of hierarchical control combined with the integral sliding mode control (SMC). The stability proof is given. Hardware in the loop (HIL) tool is employed as a practical engineering solution, and it is an essential step in validating the new algorithm before moving to real flight experiments.
Highlights
Automatic flight control has been generally studied for unmanned helicopters including Proportional Integral Derivative (PID) [1], Linear Quadratic Regulator (LQR), and Linear Quadratic Gaussian (LQG) [2], H2 [3], H∞ [4], Model Predictive Control (MPC) [5], Backstepping Control [6], robust control [7,8,9], Fuzzy Control [10], hierarchical control [11], Nonlinear Control [12], sliding mode control (SMC) [13, 14], optimal control [15], Adaptive Control [16], and Disturbance Observer-Based control [17]; few works discussed the trajectory tracking flight of unmanned helicopters in the presences of strong wind
Two sets of experiments are performed on the Hardware in the loop (HIL) simulation platform of the Ultrasport 496 (U496) unmanned helicopter, which is the experimental verification of the PID control strategy and the new flight control strategy on the mathematical model
A trajectory tracking flight controller is proposed for unmanned helicopters in longtime flight
Summary
Automatic flight control has been generally studied for unmanned helicopters including Proportional Integral Derivative (PID) [1], Linear Quadratic Regulator (LQR), and Linear Quadratic Gaussian (LQG) [2], H2 [3], H∞ [4], Model Predictive Control (MPC) [5], Backstepping Control [6], robust control [7,8,9], Fuzzy Control [10], hierarchical control [11], Nonlinear Control [12], sliding mode control (SMC) [13, 14], optimal control [15], Adaptive Control [16], and Disturbance Observer-Based control [17]; few works discussed the trajectory tracking flight of unmanned helicopters in the presences of strong wind. Since the uncertainties and disturbances are usually supposed unknown, the balance between robustness and conservation is hard to achieve This problem is especially important when the UH is flying at different speed with strong wind. He and Han use a new acceleration feedback control as a robust enhancement for the H∞ algorithm to attenuate uncertainties and external disturbances involved in the tracking control of an unmanned helicopter [20]. The presence of time-varying airflow imposes higher requirements on the accuracy, rapidity, and stability of the trajectory tracking control for large-scale unmanned helicopters, especially when it is flying at high altitude and with long flight time.
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