Helicopter Model Research Articles

Structural dynamics modeling of rectangular rotor blades

This study investigates 1-D and 3-D methods for modeling helicopter rotor blade structural dynamics to better understand the accuracy of current structural modeling based on 1-D beam theory. Natural frequencies are calculated at various rotor angular speeds for a large variety of blades ranging from simple isotropic beams to a realistic composite blade. The blade shape is limited to rectangular planforms, but various lengths are considered. 1-D beam analysis is conducted using the RCAS rotorcraft comprehensive analysis with 2-D cross-sectional properties calculated from VABS. 3-D finite element analysis is based on the commercial code MSC/Marc. Accuracy of both 1-D and 3-D analyses have been assessed through analysis of discretization errors that originate from insufficiently refined meshing. There is very good agreement between 1-D and 3-D predictions for the eight lowest modes of a large variety of blades, when there is no coupling between modes of different nature (flap, torsion) induced by materials and when the blade length is greater than ten times chord. Effects of blade length for isotropic and composite beams with no coupling between modes are similarly predicted by 1-D and 3-D analyses, except for torsion frequency, where 1-D analysis closely follows classical beam theory. With the presence of flap–torsion coupling between modes, the two approaches differ on prediction of the torsion-dominant frequency and significantly on the flap-dominant frequency.

A Self-Repairing Control Scheme for Quadrotor Helicopter via Active Disturbance Rejection Control

In this paper, a self-repairing control scheme for attitude control of a quadrotor helicopter via active disturbance rejection control is proposed. Firstly, a model of the quadrotor helicopter is gained by its dynamic equations with pitch, roll and yaw axis. Then the active disturbance rejection controller is introduced, which is used to design the control system. The control system consists of PID controller in inner-loop and ADRC controller in outer-loop. Disturbances and uncertainties can be compensated by the ADRC to achieve smaller tracking error. Finally, the simulation results of the four-rotor helicopter validate the efficiency and self-repairing capability of the proposed control algorithm, compared with that of the PID control and the separate ADRC control.

An Unmanned Helicopter Model Identification Method Based on the Immune Particle Swarm Optimization Algorithm

An unmanned helicopter dynamic model identification method based on immune particle swarm optimization (PSO) algorithm is approved in this paper. In order to improve the search efficiency of PSO and avoid the premature convergence, the PSO algorithm is combined with the immune algorithm. The unmanned helicopter model parameters are coded as particle, the error of flight test and math simulation model is objective function, and the dynamic model of unmanned helicopter is identified. The simulation result shows that the method has high identification precision and can realistically reflect the dynamic characteristics.

Experimental Performance Evaluation of Coaxial Rotors for a Micro Aerial Vehicle

Because of their potential for application in both civil and military sectors as well as the challenge in designing a tiny flying vehicle, micro aerial vehicles have attracted enormous attention. Several configurations of micro aerial vehicles are under development, namely fixed wing, rotary wing, and flapping wing. Under rotary-wing micro aerial vehicles, coaxial contrarotating configurations with a stabilizer bar seem to provide excellent stability behavior in pitch and roll degrees of freedom. This paper presents the results of an experimental study performed on a coaxial-contrarotor helicopter model to evaluate the performance of the rotor system using different rotor blades. The thrust and power of the rotors in independent and coaxial configurations were observed. The percentage thrust loss in the coaxial configuration was seen to be dependent on the ratio of the upper- and lower-rotor revolutions per minute as well as the spacing between the rotors. A theoretical analysis using a nonuniform inflow model was developed, which corroborated very well with the experimental data. Using low-Reynolds-number drag coefficients for the airfoil, the estimated power consumption of the rotors was found to match very well with the experimental data. A closed-form solution using a uniform inflow model to estimate the thrust performance of a coaxial rotor is proposed, which also matches with the experimental observations.

A finite-state aeroelastic model for rotorcraft–pilot coupling analysis

Rotorcraft–pilot coupling (RPC) denotes interplay between pilot and helicopter (or tiltrotor) that may give rise to adverse phenomena. These are usually divided into two main classes: pilot-induced oscillations driven by flight dynamics and behavioural processes, and pilot-assisted oscillations (PAO) caused by unintentional actions of pilot on controls, owing to involuntary reaction to seat vibrations. The aim of this paper is the development of mathematical helicopter models suited for analysis of RPC phenomena. In addition to rigid-body dynamics, RPCs (especially PAO) are also related to fuselage structural dynamics and servoelasticity; however, a crucial role is played by main rotor aeroelasticity. In this work, the aeroelastic behaviour of the main rotor is simulated through a novel finite-state modeling that may conveniently be applied for rotorcraft stability and response analyses, as well as for control synthesis applications. Numerical results, first are focused on the validation of the proposed novel main rotor model, and then present applications of the developed comprehensive rotorcraft model for the RPC analysis of a Bo-105-type helicopter. Specifically, these deal with the stability of vertical bouncing, which is a PAO phenomenon caused by coupling of vertical pilot seat acceleration with collective control stick, driven by inadvertent pilot actions. Further, considering quasi-steady, airfoil theory with wake inflow correction and three-dimensional, potential-flow, boundary element method approaches, the sensitivity of PAO simulations to different aerodynamic load models applied within the main rotor aeroelastic operator is also investigated.

Stability and Control Analysis on a Small-Scale Coaxial Helicopter with Bell-Hiller Stabilizer Bar

In the paper, we present a linearized mathematical model of a small scale coaxial helicopter with Bell-Hiller stabilizer bar, which is extracted from numerical linearization of a non-linear mathematical model with small perturbation theory. Stability and control derivatives calculated by numerical method are compared and analyzed for stability and control analysis on coaxial helicopters equipped with different type stabilizer bar. The study indicates that the coaxial helicopter with stabilizer bar fixed on the upper rotors has better capability on stability and control.

Pilot's brain waves remotely control the flight of a model helicopter

Pilot's brain waves remotely control the flight of a model helicopter

Impact of pilots' biodynamic feedthrough on rotorcraft by robust stability

The coupling of rotorcraft dynamics with the dynamics of one of the main systems devoted to its control, the pilot, may lead to several peculiar phenomena, known as Rotorcraft–Pilot Couplings (RPCs), all characterized by an abnormal behavior that may jeopardize flight safety. Among these phenomena, there is a special class of couplings which is dominated by the biodynamic behavior of the pilot's limbs that close the loop between the vibrations and the control inceptors in the cockpit. Leveraging robust stability analysis, the inherently uncertain pilot biodynamics can be treated as the uncertain portion of a feedback system, making analytical, numerical or graphical determination of proneness to RPC possible by comparing robust stability margins of helicopter models with experimental Biodynamic Feedthrough (BDFT) data. The application of the proposed approach to collective bounce is exemplified using simple analytical helicopter and pilot models. The approach is also applied to detailed helicopter models and experimental BDFT measurement data.

Effect of Military Conflicts on the Formation of Emergency Medical Services Systems Worldwide

This article briefly reviews the evolution of medical support during wars and conflicts from ancient to modern times and discusses the effect warfare has had on the development of civilian health care and emergency medical services (EMS). Medical breakthroughs and discoveries made of necessity during military conflicts have developed into new paradigms of medical care, including novel programs of triage and health assessment, emergency battlefield treatment and stabilization, anesthesia, and other surgical and emergency procedures. The critical role of organizations that provide proper emergency care to help the sick and injured both on the battlefield and in the civilian world is also highlighted.

Modeling and control of a helicopter slung-load system

This article investigates modeling and modern control for a helicopter and slung-load system. For this purpose complex, physics based, control oriented helicopter models are used. Point mass approach is used to model the external loadʼs dynamics. The resulting nonlinear equations of motion are then trimmed for straight level flights and linearized around these flight conditions. Behaviors of representative trim variable values (i.e. cable angle and longitudinal and lateral cyclic blade pitch angles) and modes (i.e. flight dynamics and load modes) are thoroughly examined while some model parameters (e.g. cable length, load mass, and equivalent flat plate area) change. These behaviors are compared to data found in the literature. Furthermore, variance constrained controllers (i.e. output variance constrained and input variance constrained controllers) are applied for control system design. These controllersʼ performance is examined when they are aware of the slung-loadʼs existence and when they are not aware of the slung-load.

Trajectory linearization control for a miniature unmanned helicopter

Trajectory linearization control (TLC) approach is applied to design a nonlinear trajectory tracking controller for a miniature unmanned helicopter. The controller is based on nonlinear model derived from Newton-Euler equations, with collective and cyclic pitches being regarded as actual controls. Via model simplifications, the nonlinear helicopter model can be transformed into a cascaded form including four subsystems. Corresponding with the simplified cascaded structure, the proposed controller is constructed by synthesizing TLC designs for subsystems. Each of them includes designs of a pseudo-inversion and an error regulator. A summarized TLC algorithm for the unmanned helicopter is listed briefly after the detailed controller design process. Simulation results are provided to demonstrate performances of the closed-loop system.

Nonlinear system modeling and identification of small helicopter based on genetic algorithm

PurposeThe 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.Design/methodology/approachThe 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.FindingsThe 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.Research limitations/implicationsThe 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.Originality/valueGA 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.

Taking the Phenomics Revolution into the Field

Taking the <i>Phenomics Revolution</i> into the Field

Fuzzy-Genetic Identification and Control Stuctures for Nonlinear Helicopter Model

The paper exploits advantages of the genetic algorithm and fuzzy logic in identification and control of 2DOF nonlinear helicopter model. The genetic algorithm is proposed for identification of the helicopter system, which contains a helicopter body, main and tail motors and drivers. The quality of helicopter model achieved was validated through simulation and experimental modes. Then, this model is used to design of elevation and azimuth Mamdani type fuzzy controllers. The main objective of the paper is to obtain robust and stable controls for wide range of azimuth and elevation angles changing during the long time flight. The robustness and effectiveness of both fuzzy controllers were verified through both simulations and experiments. Also, a comparative analysis of proposed fuzzy and traditional PID controllers is performed.

Constrained predictive control of helicopters

PurposeThe purpose of this paper is to show the feasibility of constrained model predictive control (MPC) for sophisticated helicopter models which are derived by physical considerations.Design/methodology/approachPhysics‐based modeling is used to create control‐oriented helicopter models. Advanced constrained controllers are designed and tested for these sophisticated models.FindingsThe helicopter models are valid and constrained MPC shows considerable promise for robust tracking.Practical implicationsMPCs can be implemented for highly constrained helicopter flights.Originality/valueA complete process of control‐oriented, physics‐based model development for helicopters followed by MPC design is developed. It is also proved that constrained MPC can be used and implemented online to robustly track discontinuous helicopter trajectories with heterogeneous constraints, even when the models are sophisticated and physics based.

Mixed Sensitivity H-∞ Control for Helicopter Model

The paper deals with the design of H-∞ robust controller, particularly with mixed sensitivity problem for elevation control. It briefly introduces basic mathematical background concerning robust control approach, which is then applied for typical example of MIMO system, that is a helicopter model. The obtained results are verified on real educational physical model CE 150 by Humusoft, ltd.

2309 スタビライザ付き小型電動ヘリのブレード翼素解析に基づくモデリングと検証実験(OS2-2 鉄道と無人ヘリのダイナミクス,OS2 交通・物流システムのダイナミクス,オーガナイズド・セッション(OS))

Aiming at the flight control design of small helicopters for large flight envelopes, a comprehensive modeling of small electric helicopters, utilizing first principles based on the analyses of main blades divided into elements on which air speeds and aerodynamic forces are calculated, is performed. The precision of dynamics is verified by flight test data. The developed model also makes flight performances and dynamics of the small helicopter clear by using trim calculations and analyses of eigenvalues and the stabilizer motion.

Quadrotor tracking control based on a moving frame

Abstract A model for a quadrotor helicopter, its flatness-based parameterization, and its control are investigated. The model is transformed by expressing the configuration in terms of a reference trajectory and the deviation from the latter. A flat output for the error system is introduced. A dynamic and a quasi-static feedback for asymptotic stabilization of reference trajectories are derived. The approach avoids introducing artificial singularities and provides the possibility for tracking “acrobatic” trajectories. A simulation result with the quadrotor flying a loop is shown.

Hardware Design for State Vector Identification of a Small Helicopter Model

The paper deals with hardware design for sensory system of a small helicopter model that is characterized by a long-term stability and in real time generates data about helicopter state variables during helicopter flight. The sensor system is based on powerful 32-bit processors with the cores ARM7 and Cortex-M3. The main unit for data processing presents an embedded computer built on a mini-ITX motherboard with processor Intel i3. As the helicopter presents a system with six degrees of freedom and in the fact, during the flight, there is not any fixed point that would enable to caliber the sensors placed on the helicopter board, for processing of sensor data complex stochastic calculations are necessary. They are based on the discrete Kalman filter that present a main computing tool of the control system.

The Optimization of a Full State Feedback Control System for a Model Helicopter for Longitudinal Movement

Abstract In this paper, a closed loop pole location and the speed of response for a model helicopter in longitudinal movement is considered. An optimization problem is defined to find the optimal feedback gain matrix in order to access the best settling time. To solve this optimization problem three intelligent optimization methods are utilized: Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) and Bees Algorithm (BA). In addition, an optimal controller based on linear quadratic regulator (LQR) is designed and the results are compared with the optimized full state feedback controller. The results show that using the intelligent optimization methods, better settling time can be obtained and consequently better performance for the system is achieved.