1,721,892 research outputs found
A Situation-aware Flight Control System Design using Real-time Model Predictive Control for Unmanned Autonomous Helicopters
No full textFlapping flight for biomimetic robotic insects: part II-flight control design
No full textIn this paper, we present the design of the flight control algorithms for flapping wing micromechanical flying insects (MFIs). Inspired by the sensory feedback and neuromotor structure of insects, we propose a similar top-down hierarchical architecture to achieve high performance despite the MFIs' limited on-board computational resources. The flight stabilization problem is formulated as high-frequency periodic control of an underactuated system. In particular, we provide a methodology to approximate the time-varying dynamics caused by the aerodynamic forces with a time-invariant model using averaging theory and a biomimetic parametrization of the wing trajectories. This approximation leads to a simpler dynamical model that can be identified using experimental data from the on-board sensors and the voltage inputs to the wing actuators. The overall control law is a periodic proportional output feedback. Simulations, including sensor and actuator models, demonstrate stable flight in hovering mod
Steering left-invariant control systems on matrix Lie group
No full textIn this paper we generalize a technique for eliminating the drift from the description of a control system on a matrix Lie group with left-invariant vector fields. A diffeomorphism of the state space together with an affine input transformation are used in order to put the system into an equivalent left-invariant drift- free form. Techniques developed for steering drift-free control systems may then be applied. We apply this method to the Lie group of the rigid rotations SO(3) as in the authors' previous work [6], and to a new example, the rigid motions SE(3)
Aircraft conflict prediction in presence of a spatially correlated wind field.
No full textIn this paper, the problem of automated aircraft conflict prediction is studied for two-aircraft midair encounters. A model is introduced to predict the aircraft positions along some look-ahead time horizon, during which each aircraft is trying to follow a prescribed flight plan despite the presence of additive wind perturbations to its velocity. A spatial correlation structure is assumed for the wind perturbations such that the closer the two aircraft, the stronger the correlation between the perturbations to their velocities. Using this model, a method is introduced to evaluate the criticality of the encounter situation by estimating the probability of conflict, namely, the probability that the two aircraft come closer than aminimum allowed distance at some time instant during the look-ahead time horizon. The proposed method is based on the introduction of a Markov chain approximation of the stochastic processes modeling the aircraft motions. Several generalizations of the proposed approach are also discussed
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