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Fault tolerant control of a small helicopter with Tail Rotor Failures in hovering mode
Abstract
Tail rotor failure is one of the major failures occurring frequently and causing accidents. In this paper we investigate Tail Rotor Control Failure(TRCF) based on helicopter dynamic models. There is no notable work reported in the literature on control of a small helicopter with TRCF. In contrast to hover mode, forward flight improves yaw damping naturally. So it is a challenging task to retain the control during TRCF in hovering mode. Multi-loop PID controller is designed as per ADS-33PRF requirements to control the helicopter when the tail rotor control failure occurs in hovering flight. Robustness in terms of stabilizing ability of developed controllers is also analyzed. All developed control schemes are tested in Matlab/Simulink environment including linear as well as non-linear simulations.
... The testing of fault-tolerant control schemes of air vehicles has been extensively studied by the safety of unmanned air vehicles especially vertically taking off and landing vehicles. The most critical failures that would be able to occur to these vehicles are motor and tail rotor failures, among others [17]. ...
In this work, a tail rotor is modelled with the aid of a multibody software to provide an alternative tool in the field of helicopter research. This advanced application captures the complex behaviour of tail rotor dynamics. The model has been built by using VehicleSim software (Version 1.0, Mechanical Simulation Corporation, Ann Arbor, MI, USA) specialized in modelling mechanical systems composed of rigid bodies. The dynamic behaviour and the control action are embedded in the code. Thereby, VehicleSim does not need an external link to another software package. The rotors are articulated, the tail rotor considers flap and feather degrees of freedom for each of the equispaced blades and their dynamic couplings. Details on the model’s implementation are derived, emphasising the modelling aspects that contribute to the coupled dynamics. The obtained results are contrasted with theoretical approaches and these have displayed to agree with the expected behaviour. This rotorcraft model helps to study the performance of a tail rotor under certain dynamic conditions.
This paper studies the optimal landing trajectory and control strategy for helicopter in tail rotor pitch lockup. A flight dynamics model of a single rotor helicopter with a tail rotor is established. The optimal safe landing and control problem is formulated into a nonlinear optimal control problem, and solved numerically using direct multiple shooting and sequential quadratic programming algorithms. The optimal safe landing process and control strategies for the sample helicopter encountering high tail rotor pitch lockup and low tail rotor pitch lockup are investigated respectively. Simulation results show that when the tail rotor is stuck at high pitch, it provides a large lateral force, which is beneficial for a high-power state landing with low forward speed and descent rate. When the tail rotor is stuck at low pitch, it provides a small lateral force, which is beneficial for flying at an economic speed (low-power state), but is not conducive to a safe landing afterwards. If a conventional landing is attempted in this situation, the yaw rate at touchdown would be very high and could be dangerous. If an autorotation landing is applied, the landing will be safer with a much lower yaw rate at touchdown.
Tail rotor failure is the main reason for a variety of helicopter accidents throughout aviation history. It is troublesome to control and navigate the helicopter to a predefined landing point with a non-functioning tail rotor especially if the number of available landing sites is limited. The objective of this thesis is to generate flight trajectories for a helicopter with a failed tail rotor and to track the trajectories by a controller. In this work, the generic helicopter model in FLIGHTLAB software is utilized and a tail rotor failed model is created. The path generation process is performed offline in MATLAB environment with an open-source trajectory optimization tool, OptimTraj. The trajectories are obtained for different scenarios by defining several constraints. An inversion-based controller is designed in order to bring the helicopter to a specified point in space by position trajectory tracking. An LQI controller is designed in order to change the trim condition of the helicopter by state trajectory tracking. The trajectories are given as a reference to the tracking controllers and simulations are performed with both linear and nonlinear models by communicating FLIGHTLAB and SIMULINK.
For several decades, researchers’ attention has been directed to the need for air safety. This has been a trailing concern for the engineering community and in particular the control engineers, who, due to the complex nature of aeronautical systems have to creatively grapple with requirements for aircraft safety and comfortability, flexibility, precision, speed and efficiency based on data obtained from such systems. Motivated by the impact modern control systems and modern technologies have on the present aeronautical/aerospace industry, a survey is carried out. It focuses on the nonlinear underactuated couplings of the decoupled Single-Degree-of Freedom and coupled Two-Degree-of-Freedom motion control of the ubiquitous rotorcraft, Twin Rotor Multi-Input Multi-Output System (TRMS) test bed. As a proven benchmark, it is employed for exploring, testing and validating flight control and optimization schemes. It brings to fore the recent developments of control laws, strategies and methods. They are deployed for physical system modelling, stability behavior (exponential and asymptotic), numerical simulations and real-time implementations in modern aerodynamic plants-(systems and technologies). These technologies include helicopters, airplanes, spacecraft, Unmanned Aerial Surveillance Vehicles, as well as main-stream and broad-ranging Multiple-Input Multiple-Output systems with varying degrees of nonlinearities and complexities. Of utmost importance, the methods are first validated on the TRMS test bed using the real-world online sensors’ (optical shaft encoders) data.
This paper studies helicopter optimal landing and control procedure after tail rotor control failure (TRCF) in different collective pitch. The optimal control problem of landing after tail rotor control failure was solved numerically by direct multiple shooting method and sequential quadratic programming. A sample helicopter optimal landing procedures after tail rotor control failure in large collective pitch and small collective pitch were investigated respectively. As can be seen from the results, when the tail rotor is stuck at large collective pitch, the tail rotor provides a large lateral force, which facilitates landing with small forward speed and descent rate in a large power state. The pilot can maintain stability of heading by side slipping. When the tail rotor is stuck at small collective pitch, the tail rotor provides a small lateral force, which is favorable for flying near economic speed, but difficult for a safe landing. A normal landing maneuver will cause a high yaw rate at touchdown, which is dangerous. Therefore, autorotation is preferred during touchdown because the landing is more secure with small yaw rate. The trajectory optimization method of helicopter safe landing after tail rotor control failure can provide a reference for flight test.
On August 25, 2004, a series of final experiments were flown at the McKenna urban operations complex at Ft. Benning, GA. These experiments represented the culmination of the rotary wing segment of the DARPA Software Enabled Control program. To support these efforts, an open system Unmanned Aerial Vehicle testbed architecture was developed for the GTMax and GTSpy research aircraft. This paper includes a description of these systems, and then discusses results from the final experiments. This includes: fault-tolerant flight control, adaptive flight control, fault detection and accommodation, reconfigurable control, trajectory generation, envelope protection, vision-aided inertial navigation, vision-based obstacle avoidance, and the first air-launching of a hovering aircraft.
This paper presents a fuzzy controller capable of waypoint navigation under tail rotor failure on a small unmanned helicopter. Helicopters, or Vertical Takeoff and Landing (VTOL) vehicles, have shown great success in military, humanitarian, and commercial endeavors and their increased use as Unmanned Aerial Vehicles (UAVs) have brought up great concerns as to the safety of these vehicles. The presented controller offers navigation possibilities to a situation that would typically results in an autorotation (emergency landing without power) or crashed vehicle. This is most beneficial in situations where the terrain, safety, or security do not allow for landing. The concepts, as well as the implementation, of the controller along with simulation experiments are presented.
The use of flight simulation tools to reduce the schedule, risk, and required amount of flight testing for complex aerospace systems is a well-recognized benefit of these approaches. However, some special challenges arise when one attempts to obtain these benefits for the development and operation of an Experimental Uninhabited Aerial Vehicle (UAV) system. These types of UAV systems are characterized by the need for the need for continual checkout of experimental software and hardware. Also, flight-testing can be further leveraged by complementing research results with flight-test validated simulation results for the same experimental UAV. In this paper, flight simulation architectures for system design, integration, and operation of an experimental helicopter-based UAV, the GTMax, are explored, and the development of a simulation tool described. The chosen helicopter-based UAV platform (a Yamaha R-Max) is well instrumented: differential GPS, inertial measurement unit, sonar altimeter, radar altimeter, and a 3-axis magnetometer. One or two flight processors can be utilized.
Safe operations of unmanned rotorcraft hinge on successfully accommodating failures during flight, either via control reconfiguration or by terminating flight early in a controlled manner. This paper focuses on autorotation, a common maneuver used to bring helicopters safely to the ground even in the case of loss of power to the main rotor. A novel nonlinear model predictive controller augmented with a recurrent neural network is presented that is capable of performing an autonomous autorotation. Main advantages of the proposed approach are on-line, real-time trajectory optimization and reduced hardware requirements.
In order for Unmanned Aerial Vehicles (UAVs) to exhibit increasing
degrees of autonomy; heterogeneous control system software needs to be
able to collaborate and reconfigure to varying mission conditions.
Currently this ability is very limited due to inadequate software
architectures on which the control systems are implemented. This paper
describes an integration platform that adopts an open systems approach
to integrating heterogeneous control algorithms. This platform was
applied to real-time piloted and unpiloted simulations of a helicopter
UAV while testing the performance of an adaptive controller as well as
the ability to reconfigure during a main rotor collective actuator
failure. Results indicate that the chosen architecture can greatly
increase the ability to integrate heterogeneous components in a seamless
fashion into a collaborating set of resources that achieve the desired
mission functionality. This paper describes the integration of flight
modeling and visualization with control algorithms
Flight Simulation for the development of an experiment UAV, AIAA Modelling and Simulation Technologies Conference and Exhibit
- E Johnson
- S Mishra
Johnson, E., Mishra, S. Flight Simulation for the development of an experiment UAV, AIAA Modelling and Simulation Technologies Conference and Exhibit, 2002.
Rotary Wing Final Experiments for the Software Enabled Control Program Autonomous Autorotation of an Rotorcraft using non linear Model Predictive Control System Identification Modelling of a Model-scale Helicopter
- E Johnson
- D Schrage
- G K Vachtsevanos
- K Valavanis
- P Pigel
- A Kanade
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Gudiance System for Automatic Approach to a Ship
- M Storvik
System Identification Modelling of a Model-scale Helicopter
- B Metter
- M Tishler
- B Kanade
Autonomous autorotation of an rotorcraft using non linear model predictive control
- K Dalamagkidis
- K Valavanis
- P Pigel