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Desired trajectory generation of a quadrotor helicopter using hybrid control for enhanced situational awareness
Abstract
This paper focuses on a critical component of the situational awareness, the control of autonomous vertical flight for an unmanned aerial vehicle. Autonomous vertical flight is a challenging but important task for tactical unmanned aerial vehicles to achieve high level of autonomy under adverse conditions. With the situational awareness strategy, we proposed a two stage flight control procedure using three autonomous control subsystems to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial nonlinear quadrotor helicopter model. This control strategy for chosen helicopter model has been verified by simulation of hovering manoeuvres using software package Simulink and demonstrated good performance for fast situational awareness in real-time search-and-rescue operations.
... Based on Newton Euler and PID tuning the desired first-order linearization is done for the hovering mode [1]. Two-stage flight control is done for three autonomous sub-systems for a nontrivial nonlinear quadrotor helicopter model [2]. A backstepping adaptive controller (BAC) is used for slow varying mass in the quadrotor used for specific control of position in terms of steady and error correction [3]. ...
... Extensive literature concerns also the specific subject of guidance that has strong connections with flight planning; in fact this latter is a dynamic process of directing an object toward a given point that may be stationary or moving. For example numerous trajectory generation methods for rotorcraft UAVs have been demonstrated in Astrov et al. [2010] and Mellinger et al. [2011]. UAV applications for geomatics, anyway are currently especially used in areas that may be too dangerous for manned aircraft or other surveys; mainly in case of natural emergencies, high-resolution images become a fundamental tool for the assessment of damages impacts on infrastructures and strategic areas. ...
The conflicts in Afghanistan and Iraq and the more recent war in the Gaza Strip have emphasized the need for novel platforms which provide for greater situational awareness in the urban terrain. Without intelligent systems, which can accurately provide real-time information, collateral damage to property will result, together with unnecessary civilian deaths. This situation is exacerbated by the fact that within the next decade 75% of the world's population will be living in urban areas. This paper outlines the current state of unmanned aerial vehicles throughout the world and presents a novel design of a multiple rotary wing platform which has great potential for both military and civilian application areas.
Decentralized command and control settings like those found in the military are rife with complexity and change. These settings typically involve dozens, if not hundreds to thousands, of heterogeneous players coordinating in a distributed fashion in a dynamically networked battlefield laden with sensor data, intelligence reports, communications, and plans emanating from many different perspectives. Consider the concept of team situation awareness in this setting. What does it mean for a team to be aware of a situation or, more importantly, of a critical change in a situation? Is it sufficient or necessary for all individuals on the team to be independently aware? Or is there some more holistic awareness that emerges as team members interact? We re-examine the concept of team situation awareness in decentralized systems beyond an individual-oriented knowledge-based construct by considering it as a team interaction-based phenomenon. A theoretical framework for a process-based measure called 'coordinated awareness of situations by teams' is outlined.
The conflicts in Afghanistan and Iraq and the more recent war in the Gaza Strip have emphasized the need for novel platforms which provide for greater situational awareness in the urban terrain. Without intelligent systems, which can accurately provide real-time information, collateral damage to property will result, together with unnecessary civilian deaths. This situation is exacerbated by the fact that within the next decade 75% of the world’s population will be living in urban areas. This paper outlines the current state of unmanned aerial vehicles throughout the world and presents a novel design of a multiple rotary wing platform which has great potential for both military and civilian application areas
Using the symmetry properties is shown to naturally lead to inverse problems of controlled system dynamics and new effective procedures of algorithm synthesis of the motion control. Control algorithms of a nontraditional structure are synthesized on the basis of combination of the conceptions of dynamic inverse problems with systems functional-optimization. It is shown that Lyapunov function assignment in the form of kinetic or total energy leads to the systems which have the asymptotic stability with respect to the equilibrium state or undisturbed motion trajectories. These questions are considered with applications to systems with the models in the form of Lagrange, Euler and Newton equations.
This paper focuses on a critical component of the situational awareness, the neural control of autonomous vertical flight for an unmanned aerial vehicle. Autonomous vertical flight is a challenging but important task for tactical unmanned aerial vehicles to achieve high level of autonomy under adverse conditions. The fundamental requirement for vertical flight is the knowledge of the height above the ground, and a properly designed controller to govern the process. With the situational awareness strategy, we proposed a two stage flight control procedure using two adaptive neural networks to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial small-scale helicopter model comprising five states, two inputs and two outputs. This control strategy for chosen helicopter model has been verified by simulation of descending and landing manoeuvres using software package Simulink and demonstrated good performance for fast situational awareness in real-time search-and-rescue operations.
The time-optimal control problem of a hovering quad-rotor helicopter is addressed in this paper. Instead of utilizing the Pontryagin's Minimum Principle (PMP), in which one needs to solve a set of highly nonlinear differential equations, a nonlinear programming (NLP) method is proposed. In this novel method, the count of control steps is fixed initially and the sampling period is treated as a variable in the optimization process. The optimization object is to minimize the sampling period such that it will be below a specific minimum value, which is set in advance considering the accuracy of discretization. To generate initial feasible solutions of the formulated NLP problem, genetic algorithms (GAs) are adopted. With the proposed method, one can find a time-optimal movement of the helicopter between two configurations. To show the feasibility of the proposed method, simulation results are included for illustration.