Search results

The purpose of this paper is to present the autopilot design for the missile under various disturbances.

In this study, model predictive control (MPC) method has been used for autopilot design for each axis. The aim of autopilot is that to keep the roll angle value around the zero degree and to track pitch/yaw acceleration commands. This three-axes control methodology also takes into consideration the interaction between pitch, yaw and roll motions.

The purpose of using MPC method for three-axes of the autopilot is to decrease the control effort and to make the close-loop system insensitive against modeling uncertainties and stochastic effects.

This study shows that the missile is able to reach to the desired target with good robustness, low control effort and little miss-distance under disturbances such as aerodynamic uncertainties, thrust misalignment and gust affect by using this alternative control method.

THE automatic flight control system (AFCS) for the Concorde has been jointly developed by Elliott‐Automation Ltd. and SFENA (Société Francaise pour la Navigation Aérienne) for the production aircraft. Elliott carry the overall design responsibility and the equipment will be supported in the field by both Elliott and SFENA. The pitch axis of the autopilot and flight director, the autothrottle, all aspects of the control of speed, all pilot/ AFCS interfaces and the landing display are Elliott responsibilities for the pre‐production and production aircraft, while SFENA are responsible for the three‐axis autostabiliser, azimuth axes of the autopilot and flight director, electric trim system and the flight test instrumentation for the AFCS. The Bendix Corporation participated in the programme for the prototype aircraft with the design and manufacture of the azimuth axes of the autopilot and flight director, and the electric trim system.

The purpose of this paper is to develop a novel solution for the predicted error and introduces a systematic method to develop optimal and explicit guidance strategies for different missions.

The predicted error is derived from its basic definition through analytical dynamics. The relations are developed for two classes of systems. First, for systems in which the acceleration commands are truncated at a specified time. Second, for systems in which the corrective maneuvers are cut off at a specified time. The predicted error differential equation is obtained in a way that allows for derivation of several optimal and explicit guidance schemes.

The effect of tangential acceleration in conjunction with autopilot dynamics can be realized in guidance gain and the predicted error. The differential equation of velocity‐to‐be‐gained is obtained assuming the gravitational acceleration to be given as a vectorial function of time. The relations for different velocity profiles are obtained and discussed including the effective navigation ratio.

The guidance/control system is modeled as a linear time‐varying dynamic and of arbitrary‐order. The gravitational acceleration is assumed as a given vectorial function of time.

The presented schemes are applicable to both midcourse and terminal guidance laws with/without velocity constraints.

Providing a new analytical solution of predicted errors with final position and velocity constraints and their differential equations considering the thrust/drag acceleration and autopilot dynamics in the presence of gravity.

The purpose of this paper is to increase flight performance of small unmanned aerial vehicle (UAV) using simultaneous UAV and autopilot system design.

A small UAV is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory. Its wing and tail is able to move forward and backward in the nose-to-tail direction in prescribed interval. Autopilot parameters and assembly position of wing and tail to fuselage are simultaneously designed to maximize flight performance using a stochastic optimization method. Results are obtained are used for simulations.

Using simultaneous UAV and autopilot system design idea, flight performance is maximized.

Permission of Directorate General of Civil Aviation in Turkey is required for testing UAVs in long range.

Simultaneous design idea is very beneficial for improving UAV flight performance.

Creating a novel method to improve flight performance of UAV and developing an algorithm performing simultaneous design idea.

The purpose of this paper is to rise the autonomous flight performance of the small unmanned aerial vehicle (UAV) using simultaneous tailplane of UAV and autopilot system design.

A small UAV is remanufactured in the UAV laboratory. Its tailplane can be changed before the flight. Autopilot parameters and some parameters of tailplane are instantaneously designed to maximize autonomous flight performance using a stochastic optimization method. Results found are applied for simulations.

Benefitting simultaneous tailplane of UAV and autopilot system design process, autonomous flight performance is maximized.

Authorization of Directorate General of Civil Aviation in Turkey is required for UAV flights.

Simultaneous tailplane and autopilot system design process is so useful for refining UAV autonomous flight performance.

Simultaneous tailplane and autopilot system design process fulfills confidence, high autonomous performance, and easy service demands of UAV users. By that way, UAV users will be able to use better UAVs.

Creating a novel technique to recover autonomous flight performance (e.g. less overshoot, less settling time and less rise time during trajectory tracking) of UAV and developing a novel procedure performing simultaneous tailplane of UAV and autopilot system design idea.

THE Super One‐Eleven aircraft of the European Division of British Airways, currently have the ability to operate in Cat 2 conditions (RVR down to 400 metres and decision heights down to 100 ft). They are equipped with a Marconi‐Elliot auto‐pilot which is an extension of the basic E2000 fitted to all but the earliest production One‐Elevens. This auto‐pilot owes its origin to the well‐proven Bendix PB20D which for the 200 Series, was developed and optimised to suit the characteristics of the aircraft and at the same time looked ahead to future lower weather minima operations.

AT the present day the operations of civil transport aeroplanes are severely restricted under conditions of poor visibility and not infrequently flights have to be diverted or cancelled. The work of the Blind Landing Experimental Unit of the Ministry of Aviation in the development of a system of automatic landing for military aircraft has been described elsewhere.1 A flight control system is described in this paper, which given the necessary azimuth guidance signals from ground based installations, will extend the advantages of automatic landings into the civil field.

Unmanned vehicles flight is controlled by embedded circuits in the aircraft, under the remote control of a pilot on the ground. This circuit, called autopilot, represents one of the key elements inside the vehicles. The authors developed one of the smallest autopilot, specifically designed for low-weight low-power applications. The paper aims to discuss these issues.

The system is based on STM32 ARM Cortex M3 microcontroller. It includes an onboard 9 DOF IMU (MPU9150) and a 2.4 GHz wireless transceiver (nRF24L01+).

The embedded lightweight kinematic autopilot (ELKA) can pilot up to eight servomotors, and can be used to monitor more than 100 sensors. The final assembled board is 28×21 mm2 and weighs around 1.2 grams (battery excluded), and has successfully passed initial functionality tests.

The authors presented the design, fabrication and initial tests of a lightweight kinematic autopilot (ELKA board version 1.0). The system has been designed in order to upgrade the state-of-art capability in sensing and processing over a previous autopilot (GINA), which is of similar weight and size. The small size (28×21 mm2) and the lightweight (around 1.2 grams) make ELKA one of the smallest autopilot in the world.

This paper aims to overcome the main obstacle to compare the merits of the different control strategies for fixed-wing unmanned aerial vehicles (UAVs) to assess autopilot performances. Up to now, the published studies of control strategies have been carried out over disperse models, thus being complicated, if not impossible, to compare the merits of each proposal. The authors present a worked benchmark for autopilots studies, consisting of generalized models obtained by merging UAVs’ parameters gathered from selected literature (journals) with other parameters directly obtained by the authors to include some relevant UAVs whose models are not provided in the literature. To obtain them it has been used a dedicated software (from U.S. Air Force).

The proposed models have been constructed by averaging both the main aircraft defining parameters (model derivatives) and pole-zero locations of longitudinal transfer functions. The suitability of the used methodologies has been checked from their capability to fit the short period and the phugoid modes. Previous analytical model arrangement has been required to match a uniform set of parameters, as the inner state variables are neither the same along the different published models nor between the additional models the authors have here contributed. Besides, moving models between the space state representation and transfer function is not just a simple averaging process, as neither the parameters nor the model orders are the same in the different published works. So, the junction of the models to a common set of parameters requires some residual’s computation and transient responses assessment (even Fourier analysis has been included to preserve the dominance of the phugoid) to keep the main properties of the models. The least mean squares technique has been used to have better fittings between SISO model parameters with state–space ones.

Both the SISO (Laplace) and state-space models for the longitudinal transfer function of an “averaged” fixed-wing UAV are proposed.

More complicated situations, such as strong wind conditions, need another kind of models, usually based on finite element method simulation. These particular models apply fluid dynamics to study aerostructural aircraft aspects, such as flutter and other aerolastic aspects, the behavior under icing conditions or other distributed parameter problems. Even some models aim to control other aspects than the autopilot, such as the trajectory prediction. However, these models are not the most suitable for the basic UAV autopilot design (early design), so they are outside the objective of this paper. Obviously, the here-considered UAVs are not all the existing ones, but the number is large enough to consider the result as a reliable and realistic representation. The presented study may be seen as a stepping stone, allowing to include other UAVs in future works.

The proposed models can be used as benchmarks, or as a previous step to produce improved benchmarks, in order to have a common and realistic scenario the compare the benefits of the different control actions in UAV autopilots continuously presented in the published research.

A work with the scope of the presented one, merging model parameters from literature with other (often referred in papers and websites) whose parameters have been obtained by the authors has been never published.

The purpose of this paper is to design a robust angle-of-attack (AOA) tracking control system for the hypersonic reentry vehicle (HRV) based on the linear parameter varying (LPV) theory, as the aerodynamic coefficients of the hypersonic vehicle vary quickly during the reentry phase.

First, longitudinal moment trim is done along the desired flight trajectory. The linearized system at each trim point is built and the dynamic characteristics analysis is made. Then the LPV control law with parameter-dependent quadratic Lyapunov function (PDQLF-LPV) is applied to design the AOA tracking autopilot at each trim point. Frequency performance of the autopilot is assessed and the step response simulation is conducted to validate the effectiveness of the control system. Finally, actual AOA command tracking simulations based on the time-varying nonlinear model are carried out to test the correctness and robustness of the PDQLF-LPV autopilot.

Analysis results demonstrate that the PDQLF-LPV control system can track the AOA command perfectly during the whole flight envelop with dynamics parameter variation or disturbances, which indicates that it is effective to integrate the PDQLF-LPV control theory with a parameter-varying reference model for control system design of HRV.

A reference model with varying parameters is utilized to guarantee the transient performance of the autopilot, and induced L2-norm analysis is introduced to describe and guarantee the robust stability of the autopilot.