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A Dynamic Surface Control (DSC) technique combined with Neural Network adaptive framework is presented, to design a robust longitudinal dynamics controller for a generic nonlinear air-breathing hypersonic flight vehicle (AHFV) model. The dynamic model of the AHFV is transformed into a pure feedback form with uncertainties included in the formulation. A detailed stability analysis is carried out to...
The work presented herein describes an application of Evolutionary Robotics controller design methodologies to the domain of Micro-unmanned Aerial Vehicles (MAVs). The aim of this paper is to extend and validate preliminary results obtained through a simplified 2D simulator, to a more realistic 3D model. After a technical introduction of the newly developed simulation model, the results generated...
In this paper, we proposed a nonlinear robust control design combined with neural network for a 3 degree of freedom (DOF) helicopter test-bed which may be subjected to unknown external disturbance and contains structure uncertainties. Regulation and tracking control design are proposed for the angles of elevation, pitch and travel axes. Numerical simulation results are provided to illustrate that...
For an aircraft flying in atmosphere a BP neural network controller based on the active control technology is designed. The design goal is to reject the influence of a rotary gust disturbance to the normal overload of the aircraft. In order to improve the dynamic response of such aircraft, the active control technology which will act on the longitudinal control is proposed. The designed controller...
The objective of this paper is to design an optimized controller for the tri-turbofan airship model. In lieu of using the traditional controller analysis method, the particle swarm optimization algorithm for controller optimization has been implemented. For more accurate results, this research used an updated neural network model to approximate the actual tri-turbofan airship dynamics. The effectiveness...
Artificial Neural Networks (ANNs) are widely applied nowadays for classification, identification, control, diagnostics, recognition, etc. They can be implemented for identification of dynamic systems. The concept of ANN is highly used in design and simulation of control system of Unmanned Aerial Vehicles (UAVs). Controller design for UAV is subject to time varying and non-linear model parameters....
This paper proposes the implementation of fuzzy cerebellar model arithmetic computer (FCMAC) neural network for altitude and velocity tracking control of the longitudinal model of an airbreathing hypersonic cruise vehicle (AHCV) which has an integrated airframe-propulsion system configuration. A set of nonlinear longitudinal equations of motion for the vehicle which include the CFD-generated aerodynamic,...
A discrete time neural network adaptive inversion controller design for a supermaneuverable aircraft nonlinear model is presented. The singular perturbation theory is used to separate the nonlinear dynamics into fast and slow sub-systems; The dynamic inversion is applied to design the control laws for the two sub-systems separately; The neural network adaptive control is based on the dynamic inversion,...
The MAV is very little, so it is easily disturbed by the environment and has week stability. Due to its low Reynolds number, it is easy to be affected by the unstable air (turbulence and gusts), and other outside interference. Recent work in dynamic inversion with neural network may be applied to control a MAV where the reference commands include position, velocity, attitude and angular rate. This...
This paper presents output feedback neural control for helicopters in single-channel modes of operation with dynamics in single-input single-output (SISO) nonlinear nonaffine form. A constructive approach for adaptive NN control design with guaranteed stability is proposed based on the use of the Implicit Function Theorem, Mean Value Theorem, and high gain observer. It is shown that the output tracking...
The current and on-going research on small-scale autonomous helicopter flight control system (FCS) design is introduced, various control methodologies included classical control, robust multi-variable control( Hinfin loop shaping and structured singular value mu - synthesis), dynamic inversion and neural-based adaptive control are described and compared from a standpoint of engineering implementation,...
The paper considers the problem of wing load control problems. To stabilize and control the wing load of the aircraft, an active wing load control system is designed. The dynamic model inversion is used as the feedback linearization method of choice. To dispose the model drift and instability of the aerodynamic model, an on line adaptive neural networks is introduced to reconstruct the inversion error...
The paper presents a design technique using adaptive backstepping method for the aircraft longitudinal flight path control laws. This control method constructs the Lyapunov function using backstepping loops, and designs on-line GCMAC neural networks used to study and compensate the unknown aerodynamic uncertainties in the plant model. Then, the neural network weights turn laws are designed based on...
Considered influence of nonlinear system and disturbance, a new adaptive fault-tolerant control method based on neural network model-following adaptive inversion control is introduced for flight control system in the presence of control surface damage. To restrain modeling uncertainties caused by fault system, neural network PID and inversion controllers are design for fault-tolerant flight control...
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