Small-scale Unmanned Helicopter Research Articles

Nonlinear adaptive tracking control for a small-scale unmanned helicopter using a learning algorithm with the least parameters

This paper puts forward a new nonlinear adaptive controller for a small-scale unmanned helicopter with unknown mass. The controller is developed under the framework of backstepping technique, with the unknown mass estimated by a novel identifier and the internal and external uncertainties approximated by radial basis function neural networks (RBFNNs). The overall closed-loop system, which consists of three parts: longitudinal–lateral subsystem, heave subsystem, and heading subsystem, is proved to be semi-globally uniformly ultimately bounded by the strict Lyapunov stability theory. Furthermore, the proposed method is more practical in actual applications with an improved online learning algorithm of the least parameters used in the RBFNNs. Finally, the effectiveness and the robustness of the proposed strategy are exhibited through two simulations compared with the classic PID method.

System Identification and Design of a Robust Controller for a Small-scale Unmanned Helicopter

The purpose of this paper is devoted to design a robust controller for the small-scale unmanned helicopter. After the system modeling and identification, a linear model was established. Considering the external disturbances, the static output feedback control of the helicopter using H-Infinity approach has been proposed. The proposed controller is analyzed using a series of simulation, and all the results demonstrate the good performance and robustness of the controller.

Robust Nonlinear Control Based on Disturbance Observer for a Small-Scale Unmanned Helicopter

A robust nonlinear controller based on disturbance observer for the trajectory tracking control of a small-scale unmanned helicopter with nonlinear structure under external disturbances and parameter uncertainties is designed. The control objective is to let the helicopter track a predefined trajectory. The proposed robust nonlinear controller is based on the backstepping sliding mode control technique which combines both the capabilities of backstepping control and sliding mode control. The control performance developed based on a time-varying disturbance observer. In order to obtain an efficient control law design, the nonlinear model of the helicopter is reformulated as an affine nonlinear system. The mathematical proof using Lyapunov stability theorem shows that the closed loop system is asymptotically stable in the presence of this controller. To verify the robustness and stability of the proposed controller, it is compared with conventional sliding mode controller. The chattering phenomenon is attenuated significantly and the tracking error is also alleviated. The simulation results confirm the desirable performance of proposed robust nonlinear controller.

Robust Adaptive Control for Unmanned Helicopter with Stochastic Disturbance

In this paper, the problem of robust adaptive control is concerned for a class of small-scale unmanned helicopter systems in the presence of system uncertainty, stochastic disturbance and output constraint. The adaptive neural network approximator is introduced to handle the unknown system function. Meanwhile, a prescribed performance function is employed to deal with output constraint. It is proved that the proposed control method is able to guarantee the ultimately bounded convergence of all closed-loop system signals in mean square via Lyapunov stability theory. The effectiveness of the developed robust controller are illustrated and confirmed by numerical simulations for a class of unmanned helicopter systems.

A System Identification Strategy for Nonlinear Model of Small-Scale Unmanned Helicopters

A System Identification Strategy for Nonlinear Model of Small-Scale Unmanned Helicopters

Robust control of small-scale unmanned helicopter with matched and mismatched disturbances

In this paper, a novel robust control method for small-scale unmanned helicopter with matched and mismatched disturbances is investigated. The control objective is to make the helicopter track the predefined position and yaw angle reference trajectories. First, the helicopter model is linearized with approximate feedback linearization technique. Then, by using the estimation of the mismatched disturbances and their derivatives, the helicopter system is reconstructed to an equivalent system, where the mismatched disturbances are turned into the major matched component and minor mismatched component. These disturbances are suppressed by feedforward technique and H∞ feedback control algorithm. Finally, simulation results demonstrate the effectiveness and robustness of the proposed control strategy for small-scale unmanned helicopter in the presence of both matched and mismatched disturbances. The proposed novel robust control method can attenuate the mismatched disturbances from the state variables of the reconstructed system.

Disturbance rejection control of yaw channel of a small-scale unmanned helicopter via Takagi–Sugeno disturbance modeling approach

In this article, the disturbance estimation and rejection problem are discussed for the yaw channel dynamics of small-scale unmanned helicopter subject to mismatched disturbances. Following Takagi–Sugeno fuzzy description for unknown nonlinear disturbances, a composite control input is designed to attenuate the influence of mismatched disturbances in system output channel by combining state feedback control law, disturbance observer, and well-designed disturbance compensator. The satisfactory control performances can be verified using linear inequality optimization algorithm. Simulation results on a yaw channel dynamical system can reflect the feasibility and effectiveness of the proposed disturbance rejection approach.

A novel sliding mode controller for small-scale unmanned helicopters with mismatched disturbance

This paper presents a novel sliding mode control (SMC) strategy based on approximate feedback linearization and enhanced nonlinear disturbance observer for small-scale unmanned helicopters with high-order time-varying matched and mismatched disturbance. The novel SMC method is developed by designing a new sliding surface with the estimation of mismatched disturbance and its derivative. The proposed novel SMC method possesses following two appealing traits. First, it is robust with both matched disturbance and mismatched disturbance. Second, the chattering problem can be attenuated significantly. Moreover, the uniformly ultimately bounded stability of the closed-loop helicopter system is proved by theoretical analysis. Finally, the excellent tracking performance and robustness of the proposed flight control scheme are demonstrated by simulation results.

The Attitude Control Based on Active Disturbance Rejection Control for the Small-Scale Unmanned Helicopter

This paper presents a design of three channel controller based on active disturbance rejection control which has a fast response, high control precision, good robustness, strongly adaptability. This design approach does not need accurate mathematics model of the small unmanned helicopter. Input-output feedback linearization is intended primarily for the system output and system control input to establish a direct relation. The final aim is to develop a robust tracking control scheme which ensures that the outputs of closedloop system track the given expectations. There results of simulations show the satisfactory tracking performance and the great ability to suppress disturbances.

Robust Control for Lateral and Longitudinal Channels of Small-Scale Unmanned Helicopters

Lateral and longitudinal channels are two closely related channels whose control stability influences flight performance of small-scale unmanned helicopters directly. This paper presents a robust control approach for lateral and longitudinal channels in the presence of parameter uncertainties and exogenous disturbances. The proposed control approach is performed by two steps. First, by performing system identification in frequency domain, system model of lateral and longitudinal channels can be accurately identified. Then, a robustH∞state feedback controller is designed to stabilize the helicopter in lateral and longitudinal channels simultaneously under extraneous disturbances situation. The proposed approach takes advantages that it reduces order of the controller by preestimating some parameters (like flapping angles) without sacrificing control accuracy. Numerical results show the reliability and effectiveness of the proposed method.

Chaotic Artificial Bee Colony Algorithm for System Identification of a Small-Scale Unmanned Helicopter

The purpose of this paper is devoted to developing a chaotic artificial bee colony algorithm (CABC) for the system identification of a small-scale unmanned helicopter state-space model in hover condition. In order to avoid the premature of traditional artificial bee colony algorithm (ABC), which is stuck in local optimum and can not reach the global optimum, a novel chaotic operator with the characteristics of ergodicity and irregularity was introduced to enhance its performance. With input-output data collected from actual flight experiments, the identification results showed the superiority of CABC over the ABC and the genetic algorithm (GA). Simulations are presented to demonstrate the effectiveness of our proposed algorithm and the accuracy of the identified helicopter model.

An Effective System Identification Method of Small-Scale Unmanned Helicopter

In order to control an unmanned helicopter accurately and reliably, it is necessary to have a precise mathematical model of its dynamics. This paper presents a new timedomain identification method and process for full state space model of small-scale unmanned helicopters. The identification method is called ISAcwPEM (Improved Simulated Annealing combined with Prediction Error Method), which is not sensitive to initial point selection and doesn’t require frequency-sweeping inputs. Firstly, the primary parameters to be identified are selected by model sensitivity analysis. After that, the improved simulated annealing algorithm runs in a distributed computing platform to figure out a 13-order state space model of the SJTU T-REX700E small-scale unmanned helicopter (consisting of a cruise modal and a hover modal). Then the iterative Prediction Error Method (PEM) is used to optimize the model. In addition, the time-delay term and the trim term are estimated and added to the model. Finally, the effectiveness of the identification method is well validated by real outdoor flight experimental results.

Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution

The need for a high fidelity model for design, analysis and implementation of an unmanned helicopter system (UHS) in various emerging civil applications cannot be underestimated. However, going by a first principle approach based on physical laws governing the dynamics of the system, this task is noted to be highly challenging due to the complex nonlinear characteristics of the helicopter system. On the other hand, the problem of determining network architecture for optimal/sub-optimal performances has been one of the major challenges in the use of the nonparametric approach based on Nonlinear AutoRegressive with eXogenous inputs Network (NARX-network). The performance of the NARX network in terms of complexity and accuracy is largely dependent on the network architecture. The current approach in the literature has been largely based on trial and error, while most of the reported optimization approaches have limited the domain of the problem to a single objective problem. This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data. The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. The performance of the proposed optimized model is benchmarked with one of the previously reported architectures for a similar system. The optimized model outperformed the previous model architecture with up to 55% performance improvement. Apart from the effectiveness of the optimized model, the proposed design algorithm is expected to facilitate timely development of the nonparametric model of the helicopter system.

Frequency-domain identification of a small-scale unmanned helicopter with harmony search algorithm

This paper presents a new method to identify the model of a small-scale helicopter in frequency domain using harmony search HS algorithm. The dynamics of the small-scale helicopter are simplified to four single-input/single-output SISO linear subsystems near the hover point, and the HS optimisation algorithm is used to identify each subsystem's parameters. Time-domain verification is made to check the validity of the identified models. The verification results show that the identified models are accurate and effective enough to describe the dynamics of the helicopter. The identified models show that the dynamics of the roll, pitch and yaw channels are mainly dominated by the lightly damped second-order modes. Identification and verification results show that the application of HS algorithm in system identification is suitable and useful.

Nonlinear system identification of a small-scale unmanned helicopter

This paper presents a comprehensive method for identifying the nonlinear model of a small-scale unmanned helicopter. The model structure is obtained by first principles derivation, and the model parameters are determined by direct measurement and system identification. A new adaptive genetic algorithm is proposed to identify the parameters that cannot be directly measured. To simplify the identification process, the overall system is divided into two subsystems for identification: the heave–yaw dynamics and the lateral–longitudinal dynamics. On the basis of the input–output data collected from actual flight experiments, these two subsystems are identified using the proposed algorithm. The effectiveness of the identified model is verified by comparing the response of the simulation model with the actual response during the flight experiments. Results show that the identified model can accurately predict the response of the small-scale helicopter. Furthermore, the identified model is used for the design of an attitude controller. The experiment results show that the identified model is suitable for controller design.

Design of the Flight Control System for a Small-Scale Helicopter

Compared with the fixed-wing aerial vehicles, small-scale unmanned helicopter (SUH) has the advantages of taking off and landing vertically, cruising under ultra low speed, and sustained hovering in the air. SUH has properties of nonlinear, unstable, strongly coupling, and applying control system for SUH is considered as a challenging task. This paper presents the design of the flight control system for a SUH. This flight control system consists of two parts, namely, ground station and onboard part. Various experiments have been conducted to test the performance of this flight control system, and some of the results are presented at the end.

Robust attitude tracking control of small-scale unmanned helicopter

Robust attitude control problem for small-scale unmanned helicopters is investigated to improve attitude control performances of roll and pitch channels under both small and large amplitude manoeuvre flight conditions. The model of the roll or pitch angular dynamics is regarded as a nominal single-input single-output linear system with equivalent disturbances which contain nonlinear uncertainties, coupling-effects, parameter perturbations, and external disturbances. Based on the signal compensation method, a robust controller is designed with two parts: a proportional-derivative controller and a robust compensator. The designed controller is linear and time-invariant, so it can be easily realised. The robust properties of the closed-loop system are proven. According to the ADS-33E-PRF military rotorcraft standard, the controller can achieve top control performances. Experimental results demonstrate the effectiveness of the proposed control strategy.

Robust Motion Controller Design and Implementation for Unmanned Helicopter

In this paper a novel robust controller is investigated for unmanned helicopter. Based on signal compensation theory, robust controllers are designed to enhance both rotational and translational tracking performance, as well as robust performance over parameter uncertainty and external disturbance. The designed robust controllers are time invariant and easy to realize. The full controllers are implemented on onboard avionics of a small scale unmanned helicopter THeli260 developed by Tsinghua University. Real flight experiments are successfully carried out, which shows advantage of designed robust controller.

Special Section on Intelligent Unmanned Systems

There has been increased worldwide interest in the research on intelligent unmanned systems in recent decades. The unmannedsystem technologies have been implemented in the underwater, ground, aerial, and space domains within an ever-extending operational envelope. The miniaturization of the hardware footprint coupled with exponentially increased computing power has enabled more efficient application of a wide range of unmanned vehicles. The papers in this special section represent recent contributions to several aspects of intelligent unmanned systems. The papers were largely an extension of select papers presented at the ICIUS2010 held in Bali, Indonesia, in October 2010. Three papers deal with the development of intelligent algorithms for unmanned aerial vehicles, while two papers focus on the software and hardware integration. The rest of the papers cover the application of aerospace technology for unmanned-vehicle design. The paper by Manathara and Ghose addresses the problem of multiple unmanned aerial vehicle (UAV) rendezvous when the UAVs have to perform maneuvers to avoid collisions with other UAVs. The authors proposed a solution that consists of velocity control and a wandering maneuver of the UAVs based on a consensus among them on the estimated time of arrival at the point of rendezvous. This simple algorithm was shown to be useful in tracking stationary or slowly moving targets with a standoff distance. Kim et al. paper present an automatic landing control design using adaptive, integrated guidance and control (IGC) logic. The proposed IGC design uses a combination of an adaptive output feedback inversion and backstepping techniques. The authors formulated the problem as an adaptive output feedback control problem for a line-of-sight–based chasing-flight configuration. The automatic landing system using IGC logic was evaluated using a sophisticated six-degrees-of-freedom nonlinear simulation program with the approach and landing scenario. Jeong et al. focused on the design of a robust H-infinity attitude controller for an unmanned small-scale helicopter. It was demonstrated that the H-infinity controller works amiably when applied to the nonlinear model, even though it is designed using a linear model approximation. The time-domain simulation with the nonlinear model demonstrated that the proposed controller was very robust to the uncertainties as expected, overcoming large gain uncertainties and time delay in each input channel. Formal verification currently plays an important role in guaranteeing the correctness of the operation of safety-critical systems, for example, in UAVs. Lee et al. discuss formal modeling and verification of operational flight programs (OFPs) in a small-scale unmanned helicopter. Two different formal models for the OFP were developed and verified using SPIN and UPPAAL model checkers. Real-time behavior of theOFPwas specified using a timed-automata model. Their verification of the OFP found several safety-critical faults to be reported to and fixed by the development team. One of the key features of autonomous flight of UAVs is the ability to perform localization and map building of flight environments simultaneously. Park et al. present vision-based simultaneous localization and mapping (SLAM) for small UAVs in global-positioningsystem–denied environments. A method that combines onboard and on-ground localization and mapping was proposed. The paper by Thu et al. investigates the nature of vortex structure developed by a double-delta wing. Dye-flow visualization in a small-scale water tunnel was used for the study. The authors identified two types of flow interaction, which are enveloping and coiling-up modes. Characteristics of the two modes were examined for various angles of attack (AOAs) at relatively low Reynolds numbers of 10,000 and 15,000. The authors found that the wing vortex became stronger and the enveloping mode was dominant for a low AOA, while the coiling-up mode was dominant at a high AOA. They also reported that the transition of these two modes occurred at around an AOA of 20 . Another paper in the special section studied the unsteady flow field of a flapping model butterfly under the zero-advance ratio (J 5 0) condition using timeresolved stereoscopic particle image velocimetry. The effect of feathering on thrust generation because of chordwise wing flexibility was identified by focusing on the ejection of airflow from the gap between two wings. Ghosh et al. found that the wing flexibility adds a feathering effect and enhances net lift and thrust generation through ejection of vortex pairs during the downstroke-to-upstroke–motion reversal. They also reported that the thrust produced was positive all over the cycle, even at J 5 0, because of the feathering motion. The special section editors would like to express their sincerest gratitude to all the contributing authors. We hope that the readers will find the content of this section not only relevant but also stimulating and beneficial for their ongoing research endeavors.

Linear Tracking Control for Small-Scale Unmanned Helicopters

This paper presents a model-based tracking control design for small-scale unmanned helicopters. The design objective is for the helicopter to track predefined inertial position (or velocity) and heading reference trajectories. The controller is based on a nominal linear state-space model that successfully captures the small-scale helicopter coupled multivariable dynamics. The flight controller is composed of two feedback loops that regulate the tracking error of the longitudinal-lateral and heading-heave motion of the helicopter, respectively. The tracking error is determined by constructing a reference state generator based on the linear helicopter model and the reference outputs. The state generator can be systematically designed using the backstepping approach for systems in feedback form and by applying a physically meaningful approximation to the linear helicopter model. The controller performance is successfully tested using a realistic flight simulator.