Search Results (206)

This paper addresses the problem of controlling quadcopters operating in an environment characterized by unpredictable disturbances such as wind gusts. From a control point of view, this is a nonstandard, highly challenging problem. Fundamentally, these quadcopters are high-order dynamical systems characterized by an under-actuated and highly nonlinear model with coupling between several state variables. The main objective of this work is to achieve a trajectory by tracking desired altitude and attitude. The problem was tackled using a robust control approach with a multi-loop nonlinear controller combined with extended Kalman filtering (EKF). Specifically, the flight control system consists of two regulation loops. The first one is an outer loop based on the backstepping approach and allows for control of the elevation as well as the yaw of the quadcopter, while the second one is the inner loop, which allows the maintenance of the desired attitude by adjusting the roll and pitch, whose references are generated by the outer loop through a standard PID, to limit the 2D trajectory to a desired set path. The investigation integrates EKF technique for sensor signal processing to increase measurements accuracy, hence improving robustness of the flight. The proposed control system was formally developed and experimentally validated through indoor tests using the well-known Parrot Mambo unmanned aerial vehicle (UAV). The obtained results show that the proposed flight control system is efficient and robust, making it suitable for advanced UAV navigation in dynamic scenarios with disturbances. Full article

This paper presents a composite disturbance-tolerant control framework for quadrotor unmanned aerial vehicles (UAVs). By constructing an enhanced dynamic model that incorporates parameter uncertainties, external disturbances, and actuator faults and considering the inherent underactuated and highly coupled characteristics of the UAV, a novel robust adaptive sliding mode controller (RASMC) is designed. The controller adopts a hierarchical adaptive mechanism and utilizes a dual-loop composite adaptive law to achieve the online estimation of system parameters and fault information. Using the Lyapunov method, the asymptotic stability of the closed-loop system is rigorously proven. Simulation results demonstrate that, under the combined effects of external disturbances and actuator faults, the RASMC effectively suppresses position errors (<0.05 m) and attitude errors (<0.02 radians), significantly outperforming traditional ADRC and LQR control methods. Further analysis shows that the proposed adaptive law enables the precise online estimation of aerodynamic coefficients and disturbance boundaries during actual flights, with estimation errors controlled within ±10%. Moreover, compared to ADRC and LQR, RASMC reduces the settling time by more than 50% and the tracking overshoot by over 70% while using the ($tanh(·)$) approximation to eliminate chattering. Prototype experiments validate the fact that the method achieves centimeter-level trajectory tracking under real uncertainties, demonstrating the superior performance and robustness of the control framework in complex flight missions. Full article

This paper tackles the challenge of achieving robust and precise control for a novel quadrotor featuring continuously variable arm lengths (15 cm to 19 cm), enabling enhanced adaptability in complex environments. Unlike conventional fixed-geometry or discretely morphing unmanned aerial vehicles, this design’s continuous structural changes introduce significant complexities in modeling its time-varying moment of inertia. To address this, we propose a control strategy that decouples dynamic motion from the evolving geometry, allowing for the development of a robust control model. A sliding mode control algorithm, optimized using particle swarm optimization, is implemented to ensure stability and high performance in the presence of uncertainties and noise. Extensive MATLAB 2016 simulations validate the proposed approach, demonstrating superior tracking accuracy in both fixed and variable arm-length configurations, achieving root mean square error values of 0.05 m (fixed arms), 0.06 m (variable arms, path 1), and 0.03 m (variable arms, path 2). Notably, the PSO-tuned SMC controller reduces tracking error by 30% (0.07 m vs. 0.10 m for PID) and achieves a 40% faster settling time during structural transitions. This improvement is attributed to the PSO-optimized SMC parameters that effectively adapt to the continuously changing inertia, concurrently minimizing chattering by 10%. This research advances the field of morphing UAVs by integrating continuous geometric adaptability with precise and robust control, offering significant potential for energy-efficient flight and navigation in confined spaces, as well as applications in autonomous navigation and industrial inspection. Full article

In view of the difficulties encountered when tuning parameters and the lack of anti-interference capabilities exhibited by high-precision trajectory-tracking control of quadrotor UAVs in complex dynamic environments, this paper proposes a fusion control framework based on an improved crowned pig optimisation algorithm (ICPO) and preset performance anti-disturbance control (PPC-ADRC). Initially, this paper addresses the limited convergence efficiency of the traditional crowned pig algorithm (CPO) by introducing a dynamic time threshold mechanism and an adaptability-based directed elimination strategy to balance the algorithm’s global exploration and local development capabilities. This results in a significant improvement in the convergence speed and optimisation accuracy. Secondly, a hierarchical control architecture is designed, with the outer loop using a PPC-ADRC controller to dynamically constrain the tracking error boundary using an exponential performance funnel function and a combined state observer (ESO) to estimate the compound disturbance in real time. The inner-loop attitude control uses ADRC, and the 24-dimensional parameters of the ADRC (including the ESO bandwidth and non-linear feedback gain) are optimised autonomously using the ICPO to achieve efficient parameter tuning. The simulation experiments demonstrate that, in comparison with the original CPO, the ICPO attains an average fitness ranking that is superior in the CEC2014–2022 benchmark test, thereby substantiating its global optimisation capability. In the PPC-ADRC controller parameter optimisation, the preset performance of the ICPO-tuned PPC-ADRC controller (PPC-ADRC) is superior to that of the particle swarm optimisation (PSO), genetic algorithm (GA) and original CPO. The ICPO-based PPC-ADRC controller is shown to reduce the total error by more than 45.6% compared to the ordinary ADRC controller in the task of tracking a spiral trajectory, and it effectively reduces the overshoot. Its capacity to withstand complex wind disturbances is notably superior to that of the traditional PID and ADRC architectures. Stability analysis further proves that the system satisfies the Lyapunov convergence condition in a finite time. This research provides a theoretical foundation for the high-precision control of UAVs in complex dynamic environments. Full article

This paper addresses the challenges of cooperative formation control and prescribed-time tracking for networked quadrotor UAVs under speed and input saturation constraints. A hierarchical control framework including position formation layer and attitude tracking layer is proposed, which achieves full drive control of an underactuated UAV formation system by introducing the expected tracking Euler angle. For the outer-loop position control, a distributed consensus protocol with restricted state and control inputs is designed to ensure formation stability with customizable spacing and bounded velocity. The inner-loop attitude control employs a prescribed-time sliding mode attitude controller (PTSMAC) integrated with a prescribed-time extended state observer (PTESO), enabling rapid convergence within user-defined time and compensating for unmodeled dynamics, wind disturbances, and actuator saturation. The effectiveness of the proposed algorithm was demonstrated through Lyapunov stability. Comparative simulations show that the proposed method has significant advantages in high-precision formation control, convergence time, and input saturation. Full article

This study addresses the gap in the experimental validation of the tilt-rotor vertical take-off and landing (VTOL) UAVs by developing a novel prototype that integrates fixed-wing and multi-rotor advantages. A dynamic model based on the “X” quadrotor configuration was established, and Euler parameters were employed to derive the attitude transformation matrix. Structural optimization using hybrid meshing and inertia release methods revealed a maximum deformation of 57.1 mm (2.82% of half-wingspan) and stress concentrations below material limits (379.21 MPa on fasteners). The landing gear was optimized using the unified objective method, and the stress was reduced by 32.63 MPa compared to the pre-optimization stress. Vibration analysis identified hazardous frequencies (11–12 Hz) to avoid resonance. Stable motor speed tracking (±5 RPM) and rolling attitude control (less than 10% error) are achieved using a dual-serial PID control system based on the DSP28377D master. Experimental validation in low-altitude flights confirmed the prototype’s feasibility, though ground effects impacted pitch/yaw performance. This work provides critical experimental data for future tilt-rotor UAV development. Full article

In this study, we propose an innovative inner–outer loop control framework for a quadcopter unmanned aerial vehicle (UAV) that significantly enhances the trajectory-tracking speed and accuracy while enhancing robustness against external disturbances. The inner loop employs a Linear Active Disturbance Rejection Controller (LADRC) and the outer loop a proportion integral differential (PID) controller, unified within a fuzzy control scheme. We introduce a Self-Adaptive Bald Eagle Search Optimization algorithm to optimize the initial controller settings, thereby accelerating convergence and improving parameter-tuning precision. Simulation results show that our proposed controller outperforms the conventional two-loop cascade PID configuration, as well as alternative strategies combining an outer-loop PID with a second-order inner-loop LADRC or a fuzzy-enhanced PID-LADRC approach. Moreover, the system maintains the desired position and attitude under external perturbations, underscoring its superior disturbance-rejection capability and stability. Full article

Unmanned Surface Vehicles (USVs) are commonly used as mobile docking stations for Unmanned Aerial Vehicles (UAVs) to ensure sustained operational capabilities. Conventional vision-based techniques based on horizontally-placed fiducial markers for autonomous landing are not only susceptible to interference from lighting and shadows but are also restricted by the limited Field of View (FOV) of the visual system. This study proposes a method that integrates an improved minimum snap trajectory planning algorithm with an event-triggered vision-based technique to achieve autonomous landing on a small USV. The trajectory planning algorithm ensures trajectory smoothness and controls deviations from the target flight path, enabling the UAV to approach the USV despite the visual system’s limited FOV. To avoid direct contact between the UAV and the fiducial marker while mitigating the interference from lighting and shadows on the marker, a landing platform with a vertically placed fiducial marker is designed to separate the UAV landing area from the fiducial marker detection region. Additionally, an event-triggered mechanism is used to limit excessive yaw angle adjustment of the UAV to improve its autonomous landing efficiency and stability. Experiments conducted in both terrestrial and river environments demonstrate that the UAV can successfully perform autonomous landing on a small USV in both stationary and moving scenarios. Full article

The flight dynamics of quadrotor UAVs are characterized by significant nonlinearity and inter-axis coupling, posing challenges for the direct application of linear control theory in flight control system design. This paper proposes a feedback linearization transformation method to reduce the computational burden of MPC while addressing the nonlinear coupled flight dynamics in attitude control. The quadrotor UAV’s attitude motion is transformed via feedback linearization into a linear decoupled model, consisting of three independent second-order systems. MPC theory is then employed to design the attitude control system. By solving the constrained optimal control problem within the MPC framework, control inputs for each second-order system are derived, enabling precise attitude tracking through receding horizon control theory. Simulation verifications were subsequently conducted, with the experiment comparing FLMPC, LMPC and AMPC. The results indicate that FLMPC outperforms both the other controllers in terms of control precision, computational efficiency and robustness to disturbances, suggesting its effectiveness for real-time UAV operations where both performance and computational resource constraints are critical. Full article

In response to the inherent nonlinearity and complex coupling of quadrotor UAV systems, as well as the challenge of maintaining a stable flight attitude under external disturbances, this paper proposes a UAV pose control method based on a fusion of Active Disturbance Rejection Control (ADRC) and Super-Twisting Sliding Mode Control (ST-SMC). By combining the strengths of ADRC and the super-twisting sliding mode algorithm, this approach achieves complementary performance—enhancing the system’s disturbance rejection capability and response speed while effectively mitigating the high-frequency chattering problem commonly caused by switching functions in traditional sliding mode control. Under random airflow disturbances, the designed fusion algorithm leverages the dynamic compensation characteristics of ADRC to stabilize external perturbations, while the robustness of ST-SMC suppresses the effects of system nonlinearities and uncertainties on control accuracy. Finally, MATLAB simulation experiments validate the effectiveness of this method, showing significantly better performance in terms of response speed, overshoot, and settling time compared to traditional control algorithms. This approach greatly improves the UAV’s pose stability and self-balancing capability in complex environments, ensuring strong dynamic and static control performance under random disturbances while maintaining high real-time performance and control efficiency. Full article

The energy consumption of rotary-wing unmanned aerial vehicles has become an important factor restricting their long-term application. This article focuses on decoupling the motion channel and reducing control energy consumption, and proposes a decoupling controller based on dynamic inversion for the complete dynamics of quadcopter unmanned aerial vehicles. Firstly, we design a direct closed-loop feedback controller for the z-channel to exhibit second-order linear dynamic characteristics with adjustable parameters. Then, the specific functions of pitch angle and yaw angle are combined as virtual control variables for the comprehensive decoupling design of the x-direction and y-direction, so that the x-channel and y-channel also exhibit independent parameter-adjustable second-order linear dynamic characteristics. Next, by solving the actual control variables, a fast convergence system is dynamically formed by the deviation between the virtual control variables and their actual values, ensuring that the specific function combination of pitch angle and yaw angle quickly converges to the expected value. Finally, the effectiveness and low energy consumption control characteristics of the decoupling control scheme were demonstrated through simulation comparison with other control methods (such as classical PID) in terms of energy consumption. Full article

Traditional multirotor UAVs (unmanned aerial vehicles) are inherently underactuated, with coupled position and attitude control, which limits their maneuverability in specific applications. This paper presents a fully actuated quadrotor design based on a swashplateless rotor mechanism. Unlike existing fully actuated UAV designs that rely on servo-driven tilt mechanisms, this approach minimizes additional weight and simplifies the structure, resulting in a more maintainable system. The design, modeling, and control strategies for the quadrotor are presented. Furthermore, we propose a decoupled control method to address the need for both fully actuated and underactuated modes. The control architecture employs parallel attitude and position control structures and decouples the two subsystems using a nonlinear dynamic inversion (NDI) method. A compensation module is introduced to address the constraints imposed by the maximum rotor deflection angle and the corresponding feasible force set. This compensation module actively adjusts the attitude to mitigate the saturation of the required thrust, effectively overcoming the impact of rotor deflection angle limitations on trajectory tracking performance. The approach facilitates seamless switching between fully actuated and underactuated modes, enhancing the system’s flexibility and robustness. Simulation and flight experiments demonstrate the effectiveness and performance of the proposed design. Full article

This study addresses the problem of attitude and altitude tracking for a quadrotor system in the presence of parameter uncertainties. The goal is to develop a robust control strategy that can handle the nonlinear, strongly coupled dynamics of the quadrotor. To achieve this, we propose a fractional-order sliding mode control (FOSMC) scheme, which is specifically designed to improve system performance under uncertain parameters. The FOSMC approach is combined with additional adaptive laws to further enhance the robustness of the control system. We derive the necessary control laws and apply them to the quadrotor’s state-space representation, ensuring that the system remains stable and performs accurately in the presence of uncertainties. Numerical simulations are conducted to evaluate the effectiveness of the proposed control strategy. The results show that the FOSMC-based controller successfully achieves precise tracking of both attitude and altitude, demonstrating significant robustness against parameter variations and disturbances. In conclusion, the proposed FOSMC scheme provides a reliable solution for controlling quadrotor systems in uncertain environments, offering the potential for real-world applications in autonomous UAV operations. Full article

This article proposes an observer-based predefined-time robust formation controller for uncertain multi-UAV systems with external disturbances by integrating the sliding-mode technique with neural networks. The predefined-time strategy is developed to enhance formation tracking performance, including faster convergence speed, higher accuracy, and better robustness, while the sliding-mode scheme, integrated with the neural network, is effectively utilized to handle uncertain dynamics and external disturbances, ensuring adaptivity, availability, and robustness. Furthermore, the stability of the closed-loop control system is analyzed using Lyapunov’s method applied to the formulation of the quadrotor Newton–Euler model. This analysis fully guarantees that the desired formation position tracking and attitude stabilization goals for multi-UAV (quadrotor) systems can be achieved. Finally, the effectiveness of the theoretical results is validated through comprehensive simulations. Full article

Aiming at the problem of the nonlinear, strongly coupled, and underdriven trajectory tracking instability of a quadrotor unmanned aerial vehicle (UAV), this thesis proposes a feedback linearization and fractional order model predictive control strategy based on feedback linearization by modeling the dynamics of the UAV control system and linearizing the nonlinear model of attitude control. A dual closed-loop control structure, feedback linearization control (FLC) for a position loop, and fractional order model predictive control (FOMPC) for an attitude loop are adopted to realize fast position tracking and attitude response. In addition, considering that the fractional order method has the advantage of flexible regulation, the fractional order integral operator is added to the cost function of model predictive control. Finally, the simulation results and the calculation of the root mean square error verify that the proposed method has a fast response speed, small overshoot, stable flight, and good track tracking performance in UAV track tracking. Full article