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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 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 develop a hybrid algorithm using differential evolution (DE) and prediction error modeling (PEM) for identification of small-scale autonomous helicopter state-space model.

In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis.

The proposed hybrid algorithm improves the performance of the PEM algorithm in the identification of an autonomous helicopter model. It gives better results when compared with conventional PEM algorithm inside MATLAB toolboxes.

This study is applicable to only linearized state-space model.

The identification algorithm is expected to facilitate the required model development for model-based control design for autonomous helicopter development.

This study presents a novel hybrid algorithm for system identification of an autonomous helicopter model.

The purpose of this paper is to develop a multiobjective differential evolution (MODE)-based extended H-infinity controller for autonomous helicopter control.

Development of a MATLAB-based MODE suitable for controller synthesis. Formulate the H-infinity control scheme as an extended H-infinity loop shaping design procedure (H _∞ -LSDP) with incorporation of v-gap metric for robustness to parametric variation. Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance.

The proposed optimized H-infinity control was able to yield set of Pareto-controller candidates with optimal compromise between conflicting stability and time-domain performances required in autonomous helicopter deployment. The result of performance evaluation shows robustness to parameter variation of up to 20 per cent variation in nominal values, and in addition provides satisfactory disturbance rejection to wind disturbance in all the three axes.

The formulated H-infinity controller is limited to hovering and low speed flight envelope. The optimization is focused on weighting function parameters for a given fixed weighting function structure. This thus requires a priori selection of weighting structures.

The proposed MODE-infinity controller algorithm is expected to ease the design and deployment of the robust controller in autonomous helicopter application especially for practicing engineer with little experience in advance control parameters tuning. Also, it is expected to reduce the design cycle involved in autonomous helicopter development. In addition, the synthesized robust controller will provide effective hovering/low speed autonomous helicopter flight control required in many civilian unmanned aerial vehicle (UAV) applications.

The research will facilitate the deployment of low-cost, small-scale autonomous helicopter in various civilian applications.

The research addresses the challenges involved in selection of weighting function parameters for H-infinity control synthesis to satisfy conflicting stability and time-domain objectives. The problem of population initialization and objectives function computation in the conventional MODE algorithm are addressed to ensure suitability of the optimization algorithm in the formulated H-infinity controller synthesis.