Unmanned Quadrotor Research Articles

A Novel Sensor Fault Detection in an Unmanned Quadrotor Based on Adaptive Neural Observer

Prompt detection and isolation of faults and failures in flight control systems are crucial to avoid negative impacts on human and environmental systems, and to the system itself. In this study, a new scheme based on a nonlinear dynamic model is designed for sensor fault detection and isolation in an unmanned aerial vehicle (UAV) system. In the proposed design, a neural network is used as an observer for faults in the UAV sensors. The weighting parameters of the neural network are updated by the Extended Kalman Filter (EKF). The designed fault detection (FD) system is applied to an unmanned quadrotor model, and the simulation results show that the proposed design is capable of the prompt detection of sensor faults.

Adaptive Sliding Mode Fault-Tolerant Control for an Unmanned Aerial Vehicle

Sliding mode control (SMC) is known as a robust control method to maintain system performance and keep it insensitive to system uncertainties. To achieve this objective, the knowledge of the uncertainty bound is usually needed, but sometimes it could be a hard task. Hence, the adaptive technology is introduced to be synthesized with SMC. In this paper, a novel adaptive SMC (ASMC) scheme is proposed to accommodate system uncertainties caused by actuator faults. An integral sliding mode controller is used as the baseline controller. When actuator faults occur, there is no need to know the exact bound of the uncertainties in control effectiveness matrix. The post-fault control effectiveness matrix can be estimated by the proposed adaptive control scheme, and the control inputs will be changed accordingly. In such a way, the robustness of the controller to actuator faults is improved. With the help of adaptive change of both continuous and discontinuous control parts, a minimum value of the discontinuous control gain can be guaranteed. In this case, the resulting control effort is reduced accordingly to avoid control chattering effect. Owing to the minimized control effort to accommodate uncertainties compared to the conventional SMC, the proposed ASMC can still maintain the system performance when severer faults occur. The effectiveness of the developed algorithm is demonstrated by the simulation results based on an unmanned quadrotor helicopter under various faulty conditions.

System Identification and Controller Optimization of a Quadrotor Unmanned Aerial Vehicle in Hover

System Identification and Controller Optimization of a Quadrotor Unmanned Aerial Vehicle in Hover

Modeling, System Identification and PID-A Controller for Tethered Unmanned Quad-Rotor Helicopter

In this paper, a strategy for the preliminary design of Quad-Rotor problem with emphasis on utilizing system identification methods for system modeling. The algorithm of forgetting least square is applied for the realtime prediction of the system parameters. The presented strategy is applied to the mass-varying tethered Quad-Rotor. The presented system identification method provides the model parameters while the adaptive (Proportional, Integral, Derivative, and Accelerator) PID-A controller controls the system response in real-time flight. In this paper, a mathematical model for the Quad-Rotor is derived. The sensitivity analys is of the system is provided in detail. Then, a system identification algorithm is applied to study the change in parameters during flight. PID-A controller is designed to stabilize the system with mass-varying consideration. Finally, Simulation results of the full system are presented.

Retrofit fault‐tolerant tracking control design of an unmanned quadrotor helicopter considering actuator dynamics

SummaryThis paper presents a retrofit fault‐tolerant tracking control (FTTC) design method with application to an unmanned quadrotor helicopter (UQH). The proposed retrofit fault‐tolerant tracking controller is developed to accommodate loss‐of‐effectiveness faults in the actuators of UQH. First, a state feedback tracking controller acting as the normal controller is designed to guarantee the stability and satisfactory performance of UQH in the absence of actuator faults, while actuator dynamics of UQH are also considered in the controller design. Then, a retrofit control mechanism with integration of an adaptive fault estimator and an adaptive fault compensator is devised against the adverse effects of actuator faults. Next, the proposed retrofit FTTC strategy, which is synthesized by the normal controller and an additional reconfigurable fault compensating mechanism, takes over the control of the faulty UQH to asymptotically stabilize the closed‐loop system with an acceptable performance degradation in the presence of actuator faults. Finally, both numerical simulations and practical experiments are conducted in order to demonstrate the effectiveness of the proposed FTTC methodology on the asymptotic convergence of tracking error for several combinations of loss‐of‐effectiveness faults in actuators.

Path Following Control Tuning for an Autonomous Unmanned Quadrotor Using Particle Swarm Optimization

The goal of this work is to present the particle swarm optimization application for quadrotor attitude and path following control tuning. To perform this task a path following feed-forward plus proportional-derivative control strategy was implemented, using particle swarm for tuning gains, and root mean square error for validating. The basic of quadrotor kinematics and dynamics model will be presented. Path planning will be executed through Euler-Lagrange equations to minimize the snap cost function and guarantee a soft trajectory through a set of intermediary waypoints. The reliability of this approach will be tested through several simulations.

Nonlinear robust adaptive sliding mode control design for miniature unmanned multirotor aerial vehicle

This paper addresses the stability and tracking control problem of miniature unmanned multirotor aerial vehicle (MUMAV) in the presence of bounded uncertainty. The uncertainty may appear from unmodeled dynamics, underactuated property, input disturbance and flying environment. Nonlinear robust adaptive sliding mode control algorithm is designed by using Lyapunov function. Robust adaptation laws are designed to learn and compensate the bounded parametric uncertainty. Lyapunov analysis shows that the proposed algorithms can guarantee asymptotic stability and tracking control property of the linear and angular dynamics of MUMAV system. Compared with other existing control methods, the proposed design is very simple and easy to implement as it does not require multiple design steps, augmented auxiliary signals and exact bound of the uncertainty. Experimental results on a miniature unmanned quadrotor aerial vehicle are presented to illustrate of effectiveness of the proposed design for real-time applications.

Gaussian Process Model Predictive Control of an Unmanned Quadrotor

The Model Predictive Control (MPC) trajectory tracking problem of an unmanned quadrotor with input and output constraints is addressed. In this article, the dynamic models of the quadrotor are obtained purely from operational data in the form of probabilistic Gaussian Process (GP) models. This is different from conventional models obtained through Newtonian analysis. A hierarchical control scheme is used to handle the trajectory tracking problem with the translational subsystem in the outer loop and the rotational subsystem in the inner loop. Constrained GP based MPC are formulated separately for both subsystems. The resulting MPC problems are typically nonlinear and non-convex. We derived 15 a GP based local dynamical model that allows these optimization problems to be relaxed to convex ones which can be efficiently solved with a simple active-set algorithm. The performance of the proposed approach is compared with an existing unconstrained Nonlinear Model Predictive Control (NMPC). Simulation results show that the two approaches exhibit similar trajectory tracking performance. However, our approach has the advantage of incorporating constraints on the control inputs. In addition, our approach only requires 20% of the computational time for NMPC.

Image-Based Visual Servoing With Unknown Point Feature Correspondence

This paper presents a new image-based visual servoing approach that simultaneously solves the feature correspondence and control problem. Using a finite-time optimal control framework, feature correspondence is implicitly solved for each new image during the control selection, alleviating the need for additional image processing and feature tracking. The proposed approach demonstrates mild robustness properties and leads to acceptable or improved image feature behaviour and robot trajectories compared to classical image-based visual servoing, particularly for under-actuated robots. As such, preliminary experimental results using a small unmanned quadrotor are also presented.

Active Fault-Tolerant Control of Unmanned Quadrotor Helicopter Using Linear Parameter Varying Technique

By adopting the linear parameter varying (LPV) control technique, this paper presents an active fault-tolerant control (FTC) strategy with application to unmanned quadrotor helicopter (UQH). Adverse effects from payload grasping and dropping caused variations of system dynamics as well as battery drainage induced loss of actuator effectiveness are expected to be counteracted in this study. First, the UQH is manipulated by a well designed baseline controller. In the presence of either payload grasping/dropping or battery drainage, their magnitudes are then obtained from a LPV-based fault detection and diagnosis (FDD) scheme. Next, based on the estimated values, a fault-tolerant tracking controller, which is linear parameter dependent, is devised in a convex polytopic LPV representation schedules to a new status in corresponding to the system variations, so that the negative impacts can be compensated. The parameters that change with system variations are specified as scheduling scalars for the LPV controller, while the ultimate control rule is obtainable by employing a set of well-established linear matrix inequality (LMI) conditions. Finally, both numerical simulations on a nonlinear model of UQH and experiments on a real UQH are conducted so as to testify the effectiveness of proposed methodology.

Implementation of Swarm Social Foraging Behavior in Unmanned Aerial Vehicle (UAV) Quadrotor Swarm

One of the novel approaches in multiple quadrotor control is swarm robotics. It aims to mimic social behaviors of animals and insects. This paper presents the physical implementation of the swarm social foraging behavior in unmanned aerial vehicle quadrotors. To achieve this, it first explores the basic behavior of aggregation. It is implemented over a quadrotor swarm test-bed that makes use of external motion capture cameras. The completed algorithm makes use of the artificial potential function model combined with the environment resource profile model. Results show successful demonstration of the social foraging algorithm with minimal error in position. Also, the proposed algorithm’s performance presents an increase in aggregation speed and time as the number of swarm member increases.

Utilization of the Physicomimetics Framework for Achieving Local, Decentralized, and Emergent Behavior in a Swarm of Quadrotor Unmanned Aerial Vehicles (QUAV)

This paper presents the implementation of the physicomimetics framework in governing the behavior of a swarm of quadrotors. Each quadrotor uses only local information about itself and the neighboring quadrotors to determine its own movement by applying the principles of physicomimetics. Through these localized and relatively simple interactions, the swarm of quadrotors was able to organize itself into various structures and exhibit different swarm behaviors such as aggregation, obstacle avoidance, lattice formation, and dispersion.

Smoothed Particle Hydrodynamics Approach to Aggregation of Quadrotor Unmanned Aerial Vehicle Swarm

This paper uses a fluid mechanics approach to perform swarming aggregation on a quadrotor unmanned aerial vehicle (QUAV) swarm platform. This is done by adapting the Smoothed Particle Hydrodynamics (SPH) technique. An algorithm benchmarking is conducted to see how well SPH performs. Simulations of varying set-ups are experimented to compare different algorithms with SPH. The position error of SPH is 30% less than the benchmark algorithm when a target enclosure is introduce. SPH is implemented using Crazyflie quadrotor swarm. The aggregation behavior exhibited successfully in the said platform.

Decentralized Approaches to Antiwindup Design With Application to Quadrotor Unmanned Aerial Vehicles

This paper considers the design of structured antiwindup (AW) compensators for open-loop stable plants that themselves have a particular structure: a diagonal dynamic part cascaded with a static invertible part. Two approaches to the design of such compensators are proposed. The first one is a pseudodecentralized AW compensator that is a direct extension of a similar scheme in the literature. The second approach allows the AW compensators to be designed individually for each control channel and, provided that a certain linear program is satisfied, allows the compensators to be implemented in such a way that the nonlinear closed loop is asymptotically stable. The design approaches are applied to a quadrotor UAV, which inspired the work, and results from both simulations and flight tests are reported.

Quadrotor Actuator Fault Diagnosis with Real-Time Experimental Results

Quadrotor Unmanned Aerial Vehicles (UAVs) have attracted significant attention in recent years due to their potentials in various military and commercial applications. Four propellers mounted on the shafts of four brushless DC motors generate the required thrust and torques needed for altitude and attitude control of quadrotors. However, structural damage to the propellers and rotor degradation can lead to actuator faults in the form of a partial loss of effectiveness in a rotor, which may result in degraded tracking performance or even loss of stability of the control system. This paper presents the systematic design, analysis, and real-time experimental results of a fault detection and isolation algorithm for quadrotor actuator faults using nonlinear adaptive estimation techniques. The fault diagnosis architecture consists of a nonlinear fault detection estimator and a bank of nonlinear adaptive fault isolation estimators designed based on the functional structures of the faults under consideration. Adaptivethresholds for fault detection and isolation are systematically designed to enhance the robustness and fault sensitivity of the diagnostic algorithm. Using an indoor quadrotor test environment, real-time experimental flight test results are shown to illustrate the effectiveness of the algorithms.

Design and implementation of a vision-based hovering and feature tracking algorithm for a quadrotor

This paper demonstrates an approach to the vision-based control of the unmanned quadrotors for hover and object tracking. The algorithms used the Speed Up Robust Features (SURF) algorithm to detect objects. The pose of the object in the image was then calculated in order to pass the pose information to the flight controller. Finally, the flight controller steered the quadrotor to approach the object based on the calculated pose data. The above processes was run using standard onboard resources found in the 3DR Solo quadrotor in an embedded computing environment. The obtained results showed that the algorithm behaved well during its missions, tracking and hovering, although there were significant latencies due to low CPU performance of the onboard image processing system.

Development of collision avoidance system for useful UAV applications using image sensors with laser transmitter

The main goal of this study is to demonstrate the approach of achieving collision avoidance on Quadrotor Unmanned Aerial Vehicle (QUAV) using image sensors with colour- based tracking method. A pair of high definition (HD) stereo cameras were chosen as the stereo vision sensor to obtain depth data from flat object surfaces. Laser transmitter was utilized to project high contrast tracking spot for depth calculation using common triangulation. Stereo vision algorithm was developed to acquire the distance from tracked point to QUAV and the control algorithm was designed to manipulate QUAV's response based on depth calculated. Attitude and position controller were designed using the non-linear model with the help of Optitrack motion tracking system. A number of collision avoidance flight tests were carried out to validate the performance of the stereo vision and control algorithm based on image sensors. In the results, the UAV was able to hover with fairly good accuracy in both static and dynamic collision avoidance for short range collision avoidance. Collision avoidance performance of the UAV was better with obstacle of dull surfaces in comparison to shiny surfaces. The minimum collision avoidance distance achievable was 0.4 m. The approach was suitable to be applied in short range collision avoidance.

Active disturbance rejection and predictive control strategy for a quadrotor helicopter

In this study, an active disturbance rejection and predictive control strategy is presented to solve the trajectory tracking problem for an unmanned quadrotor helicopter with disturbances. The proposed control scheme is based on the quadrotor's dynamic model, where effects of wind gust are considered as additive disturbances on six degrees of freedom. The predictive controller solves the path following problem with extended state observers to estimate and compensate disturbances. The active disturbance rejection control scheme is used for the stabilisation of rotational movements. The suggested control structure is verified in simulation studies with the presence of external disturbances and parametric uncertainties. The proposed method improves the robustness for the modelling error and disturbances while performing a smooth tracking of the reference trajectory.

Disturbance observer-based feedback linearization control of an unmanned quadrotor helicopter

Feedback linearization is widely used for the purpose of quadrotor control. Unfortunately, feedback linearization is highly sensitive to any quadrotor model uncertainties. This paper provides feedback linearization-based control with robustness by integrating it with a disturbance observer. The proposed approach maintains the simplicity of the control structure without ignoring the high nonlinearities existing in the model by considering these nonlinearities as disturbances to be attenuated by the disturbance observer. Thus, the requirement to include complex high-order Lie derivatives in the controller is eliminated even in the presence of the high nonlinearities. Simulation results show that the proposed controller successfully force the quadrotor to follow the desired position and heading trajectories in the presence of different types of disturbances including ignored nonlinear dynamics, wind disturbances and partial actuator failure.

Attitude regulation for unmanned quadrotors using adaptive fuzzy gain-scheduling sliding mode control

This paper addresses the problem of attitude regulation for unmanned quadrotors with parametric uncertainties and external disturbances. A novel adaptive fuzzy gain-scheduling sliding mode control (AFGS-SMC) approach is proposed for attitude regulation of unmanned quadrotors. First, the kinematics model and dynamics model of attitude motion are derived, and the problem of attitude regulation is formulated. Second, a sliding mode controller is designed to regulate the attitude motion for its invariant properties to parametric uncertainties and external disturbances. The global stability and error convergence of the closed-loop system are proven by using the Lyapunov stability theorem. In order to reduce the chattering induced by continual switching control of SMC, the fuzzy logic system (FLS) is employed to design the AFGS-SMC, in which the control gains related to sign function are scheduled adaptively according to fuzzy rules, with sliding surface and its differential as FLS inputs and control gains as FLS outputs. Finally, the effectiveness and robustness of the proposed control approach are demonstrated via simulation results.