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The purpose of this paper is to build nonlinear model of a small rotorcraft‐based unmanned aerial vehicles (RUAV), using nonlinear system identification method to estimate the parameters of the model. The nonlinear model will be used in robust control system design and aerodynamic analysis.

The nonlinear model is built based on mechanism theory, aerodynamics and mechanics, which can reflect most dynamics in large flight envelop. Genetic algorithm (GA) and time domain flight data is adopted to estimate unknown parameters of the model. The flight data were collected from a series of fight tests. The identification results were also analyzed and validated.

The nonlinear model of RUAV has better accuracy, the parameters are physical quantities, and having distinctly recognizable values. The GA is suitable for nonlinear system identification. And the results proved the identified model can reflect the dynamic characteristics in extensive area of flight envelop.

The GA requires much more computing power, to identify 12 unknown parameters with 30 iterations, will takes more than 18 hours of a four cores desktop computer. Because of this is an off‐line identification process, and has more accuracy, extra time is acceptable.

GA method has significantly increased the accuracy of the model. The previous work of system identification used a ten states linear model, and using PEM identified 23 coefficients. By carefully building the nonlinear model, it has only 21 unknown parameters, but if the model is linearized, it will get a linear model more than 35 states, which shows nonlinear model contain more dynamics than linear model.

The purpose of this paper is to investigate the feasibility of controlling a small‐scale helicopter by using the model predictive control (MPC) method.

The MPC control synthesis is employed by considering five linear models representing the flight of a small‐scale helicopter from hover to high‐speed cruise. The internal model principle is employed for the trajectory tracking design.

It is found that the MPC handles well the transition problems between the models, yields satisfactory tracking control performance and produces a suitable control signal. The performance of the tracking control of the helicopter is considerably influenced by the parameter selection in the states and inputs weighting matrices of the MPC. Simulation results also showed that faster dynamics, coupling problems, input and output constraints and changing linearized multi‐inputs multi‐outputs dynamics models in the small‐scale helicopter can be handled simultaneously by the MPC controller.

The present study is limited for the application of MPC for the control of small‐scale helicopters with non‐aggressive maneuvers.

The result can be extended to design a full envelope controller for an autonomous small‐scale helicopter without the need to resort to a conventional gain scheduling technique.

Helicopter control system designs using MPC with a single either linear or non‐linear model have been studied and reported in numerous literatures. The main contribution of the paper is in the application of MPC to handle the control problems of a small‐scale helicopter defined as a mathematical model with several different modes during a flight mission.

The purpose of this paper is to design a model‐based robust controller for autonomous hovering of a small‐scale helicopter.

The model is developed using prediction error minimization (PEM) system identification method implemented to flight data. Based on the extracted linear model, an H_∞ controller is synthesized for robustness against parametric uncertainties and disturbances.

The proposed techniques for modelling provide a linear state‐space model which correlates well with the recorded flight data. The synthesized H_∞ controller demonstrates an effective performance which rejects both sinusoidal and step input disturbances. The controller enables the attitude angle follow the reference target while keeping the attitude rate constant about zero for hover flight condition.

The synthesized controller is effective for hovering and low‐speed flight condition.

This work provides an efficient hovering/low‐speed autonomous helicopter flight control required in many civilian UAV applications such as aerial surveillance and photography.

The paper addresses the challenges of controlling a small‐scale helicopter during hover with inherent modelling uncertainties and disturbances.

The purpose of this paper is to conduct the design, development and testing of a controller for an autonomous small‐scale helicopter.

The hardware in the loop simulation (HILS) platform is developed based on the nonlinear model of JR Voyager G‐260 small‐scale helicopter. Autonomous controllers are verified using the HILS environment prior to flight experiments.

The gains of the multi‐loop cascaded control architecture can be effectively optimized within the HILS environment. Various autonomous flight operations are achieved and it is demonstrated that the prediction from the simulations is in a good agreement with the result from the flight test.

The synthesized controller is effective for the particular test‐bed. For other small‐scale helicopters (with different size and engine specifications), the controller gains must be tuned again.

This work represents a practical control design and testing procedures for an autonomous small‐scale helicopter flight control. The autonomous helicopter can be used for various missions ranging from film making, agriculture and volcanic surveillance to power line inspection.

The research addresses the need for systematic design, development and testing of controller for a small‐scale autonomous helicopter by utilizing HILS environment.

The purpose of this paper is to develop a real‐time simulation environment for the validation of controller for an autonomous small‐scale helicopter.

The real‐time simulation platform is developed based on the nonlinear model of a series of small‐scale helicopters. Dynamics of small‐scale helicopter is analyzed through simulation. The controller is designed based on the extracted linear model.

The model‐based linear controller can be effectively designed and tested using real‐time simulation platform. The hover controller is demonstrated to be robust against wind disturbance.

To use the real‐time simulation environment to test and validate controllers for small‐scale helicopters, basic helicopter parameters need to be measured, calculated or estimated.

The real‐time simulation environment can be used generically to test and validate controllers for small‐scale helicopters.

The paper presents the design and development of a low‐cost hardware in the loop simulation environment using xPC target critical for validating controllers for small‐scale helicopters.

The purpose of this paper was to present the process of building hardware and software for a collision avoidance system of a quadrotor capable of an indoor autonomous flight.

The system development was carried out in two steps. First, the quadrotor system was designed to mount mission equipments for an indoor flight. The prediction error minimization (PEM) method was used for system identification of the quadrotor, and the linear quadratic regulator (LQR) control method was used for the attitude control. Second, a collision detection system was realized by using a Kinect sensor, an embedded board and a ground control system (GCS). A Kinect sensor with embedded board can send the 3D depth information to GCS and then the GCS displays the 3D depth information with a warning message.

As the controller design requires a linear model, the PEM method was used in system identification. The LQR was used in controller design. It was found that the use of the PEM method for system identification was effective for developing a linear model required for a practical control system using LQR. As 3D depth information from a Kinect sensor is quite accurate in an indoor environment, a collision detection system with Kinect was successfully developed.

The step-by-step approach presented in this paper can be used to develop an autonomous aerial vehicle capable of navigating in an indoor environment with obstacles.

The primary contribution of the paper is the presentation of a practical method for developing a low-cost collision avoidance system for a quadrotor vehicle.

The purpose of this paper is to investigate the stability of a small scale six-degree-of-freedom nonlinear helicopter model at translator velocities and angular displacements while it is transiting to hover with different initial conditions.

In this study, model predictive controller and linear quadratic regulator are designed and compared within each other for the stabilization of the open loop unstable nonlinear helicopter model.

This study shows that the helicopter is able to reach to the desired target with good robustness, low control effort and small steady-state error under disturbances such as parameter uncertainties, mistuned controller.

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

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.

The purpose of this paper is to describe the results of investigations of parachute rescue systems (PRS) for light gyrocopters.

Although the investigations were conducted in both stages simultaneously, i.e. experimental mechanics approach and numerical simulations, the paper is focussed mainly on the experimental part of the work. To ensure the safety of experimental works (i.e. for both experimenters and bystanders), the authors applied unmanned, remotely controlled scale models of autogyro for the PRS testing in the air.

The critical problem for successful use of the PRS is that the rotation of the rotor blades must be stopped when the main parachute opens, otherwise the influence of the rotor on the improper opening process of the parachute may cause the whole PRS to become useless.

The existing regulations for the use of unmanned aircraft impose the limitation upon the organisation of in-flight tests of PRS, i.e. the maximum take-off mass of the tested gyrocopter models is limited, and a full-scale test needs the approval of European Aviation Safety Agency (EASA).

The research contributes to increasing the safety level for gyrocopter users. The authors elaborated the original PRS, which currently is in the process of patenting.

Originality of the work consists of both an innovative PRS, which has never been tested before, and the results of experimental investigations, which cover both ground tests carried on static or moving stands and in-flight testing.