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The purpose of this paper is to introduce an improved system identification method for small unmanned helicopters combining adaptive ant colony optimization algorithm and Levy’s method and to solve the problem of low model prediction accuracy caused by low-frequency domain curve fitting in the small unmanned helicopter frequency domain parameter identification method.

This method uses the Levy method to obtain the initial parameters of the fitting model, uses the global optimization characteristics of the adaptive ant colony algorithm and the advantages of avoiding the “premature” phenomenon to optimize the initial parameters and finally obtains a small unmanned helicopter through computational optimization Kinetic models under lateral channel and longitudinal channel.

The algorithm is verified by flight test data. The verification results show that the established dynamic model has high identification accuracy and can accurately reflect the dynamic characteristics of small unmanned helicopter flight.

This paper presents a novel and improved frequency domain identification method for small unmanned helicopters. Compared with the conventional method, this method improves the identification accuracy and reduces the identification error.

The purpose of this paper is to introduce a new danger‐aware Operational Flight Program (OFP) for the unmanned helicopter's auto‐navigation based on the well‐known time‐triggered message‐triggered object (TMO) model.

In this design with the TMO, the danger‐awareness means two things. First, an unmanned helicopter maneuvers on safe altitudes to avoid buildings or mountains when navigating to the target position. It is assumed that minimum safe altitudes are given on evenly spaced grids and on the center points of every four adjacent grids. A three‐dimensional (3D) path‐finding algorithm using this safe‐altitude information is proposed. Second, a helicopter automatically avoids a zone with very high temperature caused by a fire.

Since the auto‐flight control system requires componentized real‐time processing of sensors and controllers, the TMO model that has periodic and sporadic threads as members, has been used in designing the OFP. It has been found that using the TMO scheme is a way to construct a very flexible, well‐componentized and timeliness‐guaranteed OFP.

As the RTOS, RT‐eCos has been used. It was developed a few years ago based on the eCos3.0 to support the real‐time thread model of the TMO scheme. To verify this navigation system, a hardware‐in‐the‐loop simulation (HILS) system also has been developed.

Designing an OFP by using the real‐time object model TMO and the proposed 3D safe path finding algorithm is a whole new effective deadline‐based approach. And the developed OFP can be used intensively in the phase of disaster response and recovery.

This paper aims to review the AUVSI Conference and show held in Denver, Colorado with emphasis on unmanned vehicles or service robots, their application on the ground, in the air and in the water.

In‐depth interviews with exhibitors of unmanned vehicles and the providers of the technologies which are fundamental to their design and deployment. Also attendance at conference presentations.

The unmanned vehicle industry is largely driven by government requirements, both military and civilian. Unmanned service robots are also found in applications such as crop monitoring and fish school location at sea.

Unmanned vehicles continue to address air ground and marine application needs where human safety is important. The vehicles continue to become more and more autonomous, ever better to address a wider range of application requirements.

In the previous decade, unmanned aerial vehicles (UAVs) have turned into a subject of enthusiasm for some exploration associations. UAVs are discovering applications in different regions going from military applications to activity reconnaissance. The purpose of this paper is to overview a particular sort of UAV called quadrotor or quadcopter.

This paper includes the dynamic models of a quadrotor and the distinctive model-reliant and model-autonomous control systems and their correlation.

In the present time, focus has moved to outlining autonomous quadrotors. Ultimately, the paper examines the potential applications of quadrotors and their part in multi-operators frameworks.

This investigation deals with the review on various quadrotors, their applications and motion control strategies.

This paper aims to propose output feedback-based control algorithms for the flight control system of a scaled, un-crewed helicopter in its hover flight mode.

The proposed control schemes are based on H_∞ control and composite nonlinear control. The gains of the output feedback controllers are obtained as the solution of a set of linear matrix inequalities (LMIs).

In the proposed schemes, the finite-time convergence of system states to trim condition is achieved with minimum deviation from the steady-state. As the proposed composite nonlinear output feedback design improves the transient response, it is well suited for a scaled helicopter flight. The use of measured output vector instead of the state vector or its estimate for feedback provides a simple control structure and eliminates the need for an observer in real-time application. The proposed control strategies are relevant to situations in which a simple controller is essential due to economic factors, reliability and hardware implementation constraints.

The proposed control strategies are relevant to situations in which a simple controller is essential due to economic factors, reliability and hardware implementation constraints. They also have significance in applications where the number of measurement quantities needs to be minimized such as in a fully functional rotor-craft unmanned aerial vehicle.

The developed output feedback control algorithms can be used in small-scale helicopters for numerous civilian and military applications.

This work addresses the LMI-based formulation and solution of an output feedback controller for a hovering un-crewed helicopter. The stability and robustness of the closed-loop system are proved mathematically and the performance of the proposed schemes is compared with an existing strategy via simulation studies.

To investigate the use of centre of gravity location on reducing cyclic pitch control for helicopter UAV's (unmanned air vehicles) and MAV's (micro air vehicles). Low cyclic pitch is a necessity to implement the swashplateless rotor concept using trailing edge flaps or active twist using current generation low authority piezoceramic actuators.

An aeroelastic analysis of the helicopter rotor with elastic blades is used to perform parametric and sensitivity studies of the effects of longitudinal and lateral center of gravity (cg) movements on the main rotor cyclic pitch. An optimization approach is then used to find cg locations which reduce the cyclic pitch at a given forward speed.

It is found that the longitudinal cyclic pitch and lateral cyclic pitch can be driven to zero at a given forward speed by shifting the cg forward and to the port side, respectively. There also exist pairs of numbers for the longitudinal and lateral cg locations which drive both the cyclic pitch components to zero at a given forward speed. Based on these results, a compromise optimal cg location is obtained such that the cyclic pitch is bounded within ±5° for a BO105 helicopter rotor.

The reduction in the cyclic pitch due to helicopter cg location is found to significantly reduce the maximum magnitudes of the control angles in flight, facilitating the swashplateless rotor concept. In addition, the existence of cg locations which drive the cyclic pitches to zero allows for the use of active cg movement as a way to replace the cyclic pitch control for helicopter MAV's.

The purpose of this paper is to propose a control approach for small unmanned helicopters, and a novel swarm intelligence algorithm is used to optimize the parameters of the proposed controller.

Small unmanned helicopters have many advantages over other unmanned aerial vehicles. However, the manual operation process is difficult because the model is always instable and coupling. In this paper, a novel optimized active disturbance rejection control (ADRC) approach is presented for small unmanned helicopters. First, a linear attitude model is built in hovering condition according to small perturbation linearization. To realize decoupling, this model is divided into two parts, and each part is equipped with an ADRC controller. Finally, a novel Levy flight-based pigeon-inspired optimization (LFPIO) algorithm is developed to find the optimal ADRC parameters and enhance the performance of controller.

This paper applies ADRC method to the attitude control of small unmanned helicopters so that it can be implemented in practical flight under complex environments. Besides, a novel LFPIO algorithm is proposed to optimize the parameters of ADRC and is proved to be more efficient than other homogenous methods.

The model of proposed controller is built in the hovering action, whereas it cannot be used in other flight modes.

The optimized ADRC method can be implemented in actual flight, and the proposed LFPIO algorithm can be developed in other practical optimization problems.

ADRC method can enhance the response and robustness of unmanned helicopters which make it valuable in actual environments. The proposed LFPIO algorithm is proved to be an effective swarm intelligence optimizer, and it is convenient and valuable to apply it in other optimized systems.

This study aims to learn the dynamic radar cross-section (RCS) of a deflection air brake.

The aircraft model with delta wing, V-shaped tail and blended wing body is designed, and high-precision unstructured grid technology is used to deal with the surface of air brake and fuselage. The calculation method based on multiple tracking and dynamic scattering is presented to calculate RCS.

The fuselage has a low scattering level, and the opening air brake will bring obvious dynamic RCS effects to itself and the whole machine. The average indicator of air brake RCS can be lower than –0.6 dBm² under the tail azimuth, while that of forward and lateral direction is lower. The mean RCS of fuselage is obviously higher than that of air brake, while the deflected air brake and its cabin can still provide strong scattering sources at some azimuths. When the air brake is opening, the change amplitude of the aircraft forward RCS can exceed 19.81 dBm².

This research has practical significance for the dynamic electromagnetic scattering analysis and stealth design of the air brake.

The calculation method for aircraft RCS considering air brake dynamic deflection has been established.

The purpose of this paper is to use an ABC algorithm to improve the thrust–torque ratio of a rotating-wing unmanned aerial vehicle (UAV) model.

The design of UAVs, such as aircraft, drones, helicopters, has become one of the popular engineering areas with the development of technology. This study aims to improve the value of thrust–torque ratio of an unmanned helicopter. For this purpose, an unmanned helicopter was built at the Faculty of Aeronautics and Astronautics, Erciyes University. The maximum thrust–torque ratio was calculated considering the blade length, blade chord width, blade mass density and blade twist angle. For calculation, artificial bee colony (ABC) algorithm was used. By using ABC algorithm, the maximum thrust–torque ratio was obtained against the optimum input values. For this purpose, a model with four inputs and a single output is formed. In the generated system model, optimum thrust–torque ratio was calculated by changing the input values used in the ±5% range. As a result of this study, approximately 31% improvement was achieved. According to these results, the proposed approach will provide convenience to the designers in the design of the rotating-wing UAV.

According to these results, approximately 31% improvement was achieved, and the proposed approach will provide convenience to the designers in the design of the rotating-wing UAV.

It takes a long time to obtain the optimum thrust–torque ratio value through the ABC algorithm method.

Using ABC algorithm provides to improve the value of thrust–torque ratio of an unmanned helicopter. With this algorithm, unmanned helicopter flies more than ever. Thus, the presented method based on the ABC algorithm is more efficient.

The application of the ABC algorithm method can be used effectively to calculate the thrust–torque ratio in UAV.

Providing an original and penetrating a method that saves time and reduces the cost to improve the value of thrust–torque ratio of an unmanned helicopter.

The purpose of this paper is to review the 2008 AUVSI Conference and Show held in San Diego, California with emphasis on unmanned vehicles or service robots, their application on the ground, in the air and in the water.

The approach takes the form of in‐depth interviews with exhibitors of unmanned vehicles and the providers of the technologies which are fundamental to their design and deployment.

The unmanned robotic vehicle industry is largely driven by government requirements, both military and civilian. Unmanned service robots are also found in commercial applications such as pipeline surveillance, crop monitoring and fish school location at sea.

Developers will be challenged to meet the need for improvements in speed, payload, sensor capabilities, autonomous operation and command and control of fleets of unmanned vehicles.

The paper offers insights into trends and new products in the unmanned robotic vehicle industry.