450 research outputs found

    Control optimization, stabilization and computer algorithms for aircraft applications

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    The analysis and design of complex multivariable reliable control systems are considered. High performance and fault tolerant aircraft systems are the objectives. A preliminary feasibility study of the design of a lateral control system for a VTOL aircraft that is to land on a DD963 class destroyer under high sea state conditions is provided. Progress in the following areas is summarized: (1) VTOL control system design studies; (2) robust multivariable control system synthesis; (3) adaptive control systems; (4) failure detection algorithms; and (5) fault tolerant optimal control theory

    A survey on fractional order control techniques for unmanned aerial and ground vehicles

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    In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

    Fault tolerant control of a quadrotor using L-1 adaptive control

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    Purpose – The growing use of small unmanned rotorcraft in civilian applications means that safe operation is increasingly important. The purpose of this paper is to investigate the fault tolerant properties to faults in the actuators of an L1 adaptive controller for a quadrotor vehicle. Design/methodology/approach – L1 adaptive control provides fast adaptation along with decoupling between adaptation and robustness. This makes the approach a suitable candidate for fault tolerant control of quadrotor and other multirotor vehicles. In the paper, the design of an L1 adaptive controller is presented. The controller is compared to a fixed-gain LQR controller. Findings – The L1 adaptive controller is shown to have improved performance when subject to actuator faults, and a higher range of actuator fault tolerance. Research limitations/implications – The control scheme is tested in simulation of a simple model that ignores aerodynamic and gyroscopic effects. Hence for further work, testing with a more complete model is recommended followed by implementation on an actual platform and flight test. The effect of sensor noise should also be considered along with investigation into the influence of wind disturbances and tolerance to sensor failures. Furthermore, quadrotors cannot tolerate total failure of a rotor without loss of control of one of the degrees of freedom, this aspect requires further investigation. Practical implications – Applying the L1 adaptive controller to a hexrotor or octorotor would increase the reliability of such vehicles without recourse to methods that require fault detection schemes and control reallocation as well as providing tolerance to a total loss of a rotor. Social implications – In order for quadrotors and other similar unmanned air vehicles to undertake many proposed roles, a high level of safety is required. Hence the controllers should be fault tolerant. Originality/value – Fault tolerance to partial actuator/effector faults is demonstrated using an L1 adaptive controller

    Validation of Quad Tail-sitter VTOL UAV Model in Fixed Wing Mode

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    Vertical take-off and landing (VTOL) is a type of unmanned aerial vehicle (UAV) that is growing rapidly because its ability to take off and land anywhere in tight spaces. One type of VTOL UAV, the tail-sitter, has the best efficiency. However, besides the efficiency offered, some challenges must still be overcome, including the complexity of combining the ability to hover like a helicopter and fly horizontally like a fixed-wing aircraft. This research has two contributions: in the form of how the analytical model is generated and the tools used (specifically for the small VTOL quad tail-sitter UAV) and how to utilize off-the-shelf components for UAV empirical modeling. This research focuses on increasing the speed and accuracy of the UAV VTOL control design in fixed-wing mode. The first step is to carry out analysis and simulation. The model is analytically obtained using OpenVSP in longitudinal and lateral modes. The next step is to realize this analytical model for both the aircraft and the controls. The third step is to measure the flight characteristics of the aircraft. Based on the data recorded during flights, an empirical model is made using system identification technique. The final step is to vali-date the analytical model with the empirical model. The results show that the characteristics of the analytical mode fulfill the specified requirements and are close to the empirical model. Thus, it can be concluded that the analytical model can be implemented directly, and consequently, the VTOL UAV design and development process has been shortened

    Fault Tolerant Super Twisting Sliding Mode Control of a Quadrotor UAV Using Control Allocation

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    In this study, a fault-tolerant super-twisting sliding mode controller with a control allocation system for a quadrotor aircraft is proposed. Super twisting sliding mode control is a robust control technique that handles a system with a relative degree equal to one. A super-twisting sliding mode controller is proposed because of its robustness to uncertainties and perturbations. It increases accuracy and reduces chattering. A control allocation algorithm is developed to cope with the actuator fault. Firstly, a nonlinear model of the quadrotor unmanned aerial vehicle (UAV) is presented. Then, the controller design and type of the actuator fault are explained. The control allocation algorithm is used to optimize the trajectory tracking performance of the quadrotor in the presence of an actuator fault. A control allocation algorithm is an effective approach to implementing fault-tolerant control. When actuator faults are identified, they can be modeled as changes in the B matrix of constraints. Various simulations have been made for situations with and without actuator failure. In normal conditions, the quadrotor can accurately track altitude, roll, pitch and yaw references. In faulty conditions, the quadrotor can follow the references with a small error. Simulations prove the effectiveness of the control allocation algorithm, which stabilizes the quadrotor in case of an actuator fault. Overall, this paper presents a novel fault-tolerant controller design for quadrotor aircraft that effectively addresses actuator faults using a super-twisting sliding mode controller and control allocation algorithm

    Observer-Based Optimal Control of a Quadplane with Active Wind Disturbance and Actuator Fault Rejection

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    Hybrid aircraft configurations with combined cruise and vertical flight capabilities are increasingly being considered for unmanned aircraft and urban air mobility missions. To ensure the safety and autonomy of such missions, control challenges including fault tolerance and windy conditions must be addressed. This paper presents an observer-based optimal control approach for the active combined fault and wind disturbance rejection, with application to a quadplane unmanned aerial vehicle. The quadplane model is linearised for the longitudinal plane, vertical takeoff and landing and transition modes. Wind gusts are modelled using a Dryden turbulence model. An unknown input observer is first developed for the estimation of wind disturbance by defining an auxiliary variable that emulates body referenced accelerations. The approach is then extended to simultaneous rejection of intermittent elevator faults and wind disturbance velocities. Estimation error is mathematically proven to converge to zero, assuming a piecewise constant disturbance. A numerical simulation analysis demonstrates that for a typical quadplane flight profile at 100 m altitude, the observer-based wind gust and fault correction significantly enhances trajectory tracking accuracy compared to a linear quadratic regulator and to a H-infinity controller, which are both taken, without loss of generality, as benchmark controllers to be enhanced. This is done by adding wind and fault compensation terms to the controller with admissible control effort. The proposed observer is also shown to enhance accuracy and observer-based rejection of disturbances and faults compared to three alternative observers, based on output error integration, acceleration feedback and a sliding mode observer, respectively. The proposed approach is particularly efficient for the active rejection of actuator faults under windy conditions.</p

    A FAULT TOLERANT, DATA FUSION SYSTEM FOR NAVIGATION APPLICATIONS TO A DUCTED FAN VTOL UAV

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    A Fault Tolerant, Data Fusion (FTDF) algorithm for a Ducted Fan Unmanned Aerial Vehicle (DFUAV) Navigation System is presented. The algorithm have two parts: Gradient Descent (GD) for the Attitude and Heading Reference System (AHRS) and an Interacting Multiple Model (IMM) for position estimation. The GD methodology was designed to fuse the gyroscope, accelerometer, and geomagnetic sensors. The IMM algorithm is able to identify and compensate for multiple sensors data failures. There are three parts in the presentation. Firstly, system identification and the Allan Variance method is used to build dynamic models and noise models for multiple Sensors and Actuators. Secondly, a GD filter is developed for application to the Inertial Measurement Unit (IMU) consisting of tri-axis gyroscopes, accelerometers and magnetometers. The GD filter implementation incorporates magnetic distortion and gyroscope bias drift compensation. The filter uses a quaternion representation, allowing accelerometer and magnetometer data to be used in an analytically derived and optimized algorithm to compute the direction of the gyroscope measurement error as a quaternion derivative. . Finally, the IMM algorithm is used to combine data from multiple sensors simultaneously. This filter uses multiple models that incorporate sensor failures. The probabilities of these models being correct is generated by the IMM. These probabilities can be used to identify sensor failures and compensate for these failures

    Nonlinear Control of Autonomous Flying Cars with Wings and Distributed Electric Propulsion

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    Hybrid vertical take-off and landing vehicles (VTOL) with lift production from wings and distributed propulsive system present unique control challenges. Existing methods tend to stitch and switch different controllers specially designed for fixed-wing aircraft or multicopters. In this paper, we present a unified framework for designing controllers for such winged VTOL vehicles that are commonly found in recent flying car models. The proposed method is broken down into nonlinear control of both position and attitude with forces and moments as inputs, and real-time control allocation that integrates distributed propulsive actuation with conventional control surface deflection. We also present a strategy that avoids saturation of distributed propulsion control inputs. The effectiveness of the proposed framework is demonstrated through simulation and closed-loop flight experiment with our winged VTOL flying car prototype
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