Unmanned Quadrotor Helicopter Research Articles

Conditional integrator sliding mode control of an unmanned quadrotor helicopter

Sliding mode control (SMC) is a widely used control law for quadrotor regulation and tracking control problems. The purpose of this article is to solve the tracking problem of quadrotors using a relatively novel nonlinear control law based on SMC that makes use of a conditional integrator. It is demonstrated by a motivation example that the proposed control law can improve the transient response and chattering shortcomings of the previous approaches of similar SMC based controllers. The adopted Newton–Euler model of quadrotor dynamics and controller design is treated separately in two subsystems: attitude and position control loops. The stability of the control technique is demonstrated by Lyapunov’s analysis and the effectiveness and performance of the proposed method are compared with a similar integral law, also based on SMC, and validated by tracking control problems using numerical simulations. Simulations were developed in the presence of external disturbances in order to evaluate the controller robustness. The effectiveness of the proposed controller was verified by performance indexes, demonstrating less accumulated tracking errors and control activity and improvement in the transient response and disturbance rejection when compared to a conventional integrator sliding mode controller.

Adaptive Fractional-Order SMC Controller Design for Unmanned Quadrotor Helicopter Under Actuator Fault and Disturbances

This paper presented an adaptive and fractional-order sliding mode control(FOSMC) method for the unmanned quadrotor helicopter. The aircraft system includes actuator fault and external disturbances. The switching sliding mode law enables the system to reach the predefined sliding surface from arbitrary states. Then the equation control law keeps the trajectory stay over the sliding hyperplane. In order to make sure sliding motion from the arbitrary states to the surface within limited time, a novel fractional-order power switching control law is developed. System actuator failures are compensated online with adaptive control laws. The controllers are derived from the Lyapunov theory, which guarantees that the controllability and feasibility. This novel control strategy has higher tracking accuracy through the timely faults and disturbances compensation law. The presented fractional-order sliding mode scheme improves the speed of system convergence and shortens the reaching time. The adaptive strategy estimated the bounds of the disturbances and good robustness has been achieved. Simulation results shown that the presented strategy has numerous advantages in terms of attitude and position tracking.

Sensor Fault Detection and Diagnosis for an Unmanned Quadrotor Helicopter

This paper proposes a new nonlinear fault detection and diagnosis (FDD) scheme for the inertial measurement unit (IMU) sensor of an unmanned quadrotor helicopter (UQH). To mitigate the impact of model uncertainties, the kinematic model of an UQH rather than the dynamic model is employed to design the FDD scheme. A two-stage extended Kalman filter (TSEKF) is developed for detecting, isolating and identifying IMU sensor faults. Considering that the TSEKF is insensitive to time-varying faults, two adaptive two-stage extended Kalman filters are further proposed by integrating TSEKF with different forgetting factor schemes. Several experiments have been designed and implemented on an UQH platform to test the proposed FDD scheme, where bias fault, drift fault and oscillatory fault are considered. The results demonstrate that the proposed FDD methods are effective for detecting and estimating the IMU sensor faults in different fault scenarios.

Payload dropping control of an unmanned quadrotor helicopter based on backstepping controller

Quadrotors have generated considerable interest in both the control community due to their simple dynamics and widely applications because of their advantages over regular air vehicles. Unlike other control algorithms that tend to linearize nonlinear systems, backstepping control does not work to cancel the nonlinearities in the system. This leads to more flexible designs since some of the nonlinear terms can contribute to the stability of the system. The backstepping control is implemented in this paper for the robustness of the quadrotor helicopter in the payload dropping process. This control algorithm is implemented on the parameters of an unmanned quadrotor helicopter platform known as Qball-X4 available at the Networked Autonomous Vehicles Lab of Concordia University. Simulation results carried out using a nonlinear model, and wherein the performance achieved with this control strategy is shown.

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.

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.

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.

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.

Hierarchy robust control for unmanned quadrotor helicopter without linear velocity measurement

Considering the parameter measurement errors of a low-cost quadrotor system and the constant wind disturbance during flight, a hierarchy robust control strategy for unmanned quadrotor helicopter is constructed. The hierarchy robust control strategy is that the attitude and position loops of the quadrotor adopt different robust control strategy. The integral backstepping controller is applied to stabilise the attitude angles of the quadrotor with parameter errors. The linear robust controller with a compensator for the constant wind is applied to fulfil the position tracking. Sliding mode observer for the quadrotor position subsystem is founded to estimate the linear velocity when the direct measurement is unavailable. The simulating test is implemented and the simulation test results show that the control algorithm is stable and can effectively reject the constant wind disturbance and have strong robustness to the parameter errors.

Payload Drop Application Using an Unmanned Quadrotor Helicopter Based on Gain-Scheduled PID and Model Predictive Control

Two useful control techniques are investigated and applied experimentally to an unmanned quadrotor helicopter for a practical and important scenario of using an Unmanned Aerial Vehicle (UAV) for dropping a payload in circumstances where search and rescue and delivery of supplies and goods is dangerous and difficult to reach environments such as forest or high building fires fighting, rescue in earthquake, flood and nuclear disaster situations. The two considered control techniques for such applications are the Gain-Scheduled Proportional-Integral-Derivative (GS-PID) control and the Model Predictive Control (MPC). Both the model-free (GS-PID) and model-based (MPC) algorithms show a very promising performance with application to taking-off, height holding, payload dropping, and landing periods in a payload dropping mission. Finally, both algorithms are successfully implemented on an unmanned quadrotor helicopter testbed (known as Qball-X4) available at the Networked Autonomous Vehicles Lab (NAVL) of Concordia University for payload dropping tests to illustrate the effectiveness and performance comparison of the two control techniques.

Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed

As the first part, this paper presents an overview on the existing works on fault detection and diagnosis (FDD) and fault-tolerant control (FTC) for unmanned rotorcraft systems. Considered faults include actuator and sensor faults for single and multi-rotor systems. As the second part, several FDD and FTC techniques developed recently at the Networked Autonomous Vehicles Lab of Concordia University are detailed along with experimental application to a unique and newly developed quadrotor helicopter testbed.

Experimental Test of a Two-Stage Kalman Filter for Actuator Fault Detection and Diagnosis of an Unmanned Quadrotor Helicopter

This paper addresses the problem of Faut Detection and Diagnosis (FDD) of a quadrotor helicopter system in the presence of actuator faults. To this end a Two-Stage Kalman Filter (TSKF) is used to simultaneously estimate and isolate possible faults in each actuator. The faults are modelled as losses in control effectiveness of rotors. Three fault scenarios are investigated: loss of control effectiveness in one single actuator, simultaneous loss of control effectiveness in all motors, and loss of control effectiveness in three motors with different magnitudes. The developed FDD algorithm is evaluated through experimental application to an unmanned quadrotor helicopter testbed available at the Department of Mechanical and Industrial Engineering of Concordia University, called Qball-X4. The obtained results show the effectiveness of the proposed FDD method.

On Trajectory Tracking Model Predictive Control of an Unmanned Quadrotor Helicopter Subject to Aerodynamic Disturbances

AbstractIn this article a model predictive control (MPC) strategy for the trajectory tracking of an unmanned quadrotor is presented. The quadrotor's dynamics are modeled using a hybrid systems approach and, specifically, a set of piecewise affine (PWA) systems around different operating points of the translational and rotational motions. The proposed control scheme is dual and consists of an integral MPC for the translational motions, followed by an MPC scheme for the tracking of the quadrotor's attitude motions. By the utilization of PWA representations, the controller is computed for a larger part of the quadrotor's flight envelope, which provides more control authority for aggressive maneuvering. The proposed dual control scheme is able to calculate optimal control actions with robustness against atmospheric disturbances (e.g. wind gusts) and with respect to the physical constraints of the quadrotor (e.g. maximum lifting forces or fixed thrust limitations in order to extend flight endurance). Extended simulation studies indicate the efficiency of the MPC scheme, both in trajectory tracking and aerodynamic disturbance attenuation.

An Efficient Model Predictive Control Scheme for an Unmanned Quadrotor Helicopter

In this paper, an efficient Model Predictive Control (eMPC) algorithm deploying fewer prediction points and less computational requirement is presented in order to control a small or miniature unmanned quadrotor helicopter. A model reduction technique associated with the dynamics of an unmanned quadrotor helicopter is also put forward so as to minimize the burden of calculations in application of MPC into an airborne platform. For three-dimensional tracking control of the quadrotor helicopter, simulation results corresponding to the algebraic formulation--presented in this paper--versus the standard MPC formulation commonly found in the literature further illustrate effectiveness of this study. Unsuccessful implementation of the standard formulation on the testbed due to computational burden proves the necessity and advantages of this new approach. Eventually, to demonstrate effectiveness of the developed MPC algorithm, the suggested algebraic-based MPC framework is successfully implemented on an unmanned quadrotor helicopter testbed (known as Qball-X4) available at the Networked Autonomous Vehicles Lab (NAVL) of Concordia University for tracking control of the unmanned aerial vehicle.

Switching model predictive attitude control for a quadrotor helicopter subject to atmospheric disturbances

In this article a switching model predictive attitude controller for an unmanned quadrotor helicopter subject to atmospheric disturbances is presented. The proposed control scheme is computed based on a piecewise affine (PWA) model of the quadrotor's attitude dynamics, where the effects of the atmospheric turbulence are taken into consideration as additive disturbances. The switchings among the PWA models are ruled by the rate of the rotation angles and for each PWA system a corresponding model predictive controller is computed. The suggested algorithm is verified in experimental studies in the execution of sudden maneuvers subject to forcible wind disturbances. The quadrotor rejects the induced wind disturbances while performing accurate attitude tracking.

Switching Model Predictive Control for a Quadrotor Helicopter under Severe Environmental Flight Conditions

AbstractIn this article a switching Model Predictive Controller for the attitude and hovering control of a prototype Unmanned quadrotor Helicopter (UqH) subject to atmospheric disturbances is presented. The control scheme is computed based on Piecewise Affine (PWA) models of the UqH's attitude and altitude dynamics, where the effects of the atmospheric turbulence are taken into consideration as additive disturbances. The switching of the MPC scheme is ruled by the estimation and the rate of the rotation angles, for the altitude and attitude control correspondingly. Extended experimental studies indicate the overall scheme's efficiency in hovering scenarios despite the applied wind–disturbances.