Quadrotor Control Research Articles

Dual Model Predictive Control of Multiple Quadrotors With Formation Maintenance and Collision Avoidance

Dual Model Predictive Control of Multiple Quadrotors With Formation Maintenance and Collision Avoidance

Optimal Sliding Gaussian Control of Quadrotor with a Flexible Structure

Optimal sliding Gaussian control of a quadrotor aerial vehicle with a flexible structure has been demonstrated in six-degree-of-freedom flight simulation to be more robust to structural excitation than a standard proportional-derivative control scheme. A general derivation of the optimal sliding Gaussian controller, including an optimal gain selection algorithm and observer design, is presented. Additionally, a brief development of the equations of motion for a quadrotor with a flexible structure is provided as background for the nonlinear six-degree-of-freedom flight simulation results. Robustness properties of the optimal sliding Gaussian controller are evaluated using singular value analysis of linearized models of the closed-loop quadrotor with a flexible structure. Flight simulation and singular value analysis results illustrate the robustness improvements of optimal sliding Gaussian control over the standard proportional-derivative controller design.

Aggressive and robust low-level control and trajectory tracking for quadrotors with deep reinforcement learning

Aggressive and robust low-level control and trajectory tracking for quadrotors with deep reinforcement learning

Adaptive fuzzy gain-scheduling robust control for stability of quadrotors

To solve the instability problem in quadrotor control system subject to parametric uncertainties and external disturbances, an attitude control approach integrated with adaptive fuzzy gain-scheduling desired model compensation robust integral of the sign of the error is proposed. Firstly, the original cascade model of attitude motion is transformed into a strict feedback form with lumped disturbances. Secondly, a desired model compensation robust integral of the sign of the error controller is designed to regulate attitude motion for its invariant properties to lumped disturbances, replacing the velocity state in model-based feedforward control with expected value to ensure the robustness of the system against uncertainties without velocity information. To mitigate the chattering caused by continuous switching control, the fuzzy logic system is used to construct the proposed robust control algorithm, in which robust integral feedback gains associated with the sign function based on fuzzy rules are adaptive scheduled, with the filter tracking error and its derivative as inputs to the fuzzy logic system and robust integral feedback gains as outputs. The stability of the designed closed-loop system is verified by analyzing the convergence of output errors. Finally, the effectiveness and robustness of the proposed method in dealing with the stability of the control system are fully demonstrated by extensive simulations and platform experiments.

Research on Quadrotor Control Based on Genetic Algorithm and Particle Swarm Optimization for PID Tuning and Fuzzy Control-Based Linear Active Disturbance Rejection Control

The control system of a quadrotor aircraft is characterized by nonlinearity, strong coupling, and underactuation, making it susceptible to external disturbances that can affect flight performance. To address this issue, this paper proposes a novel control system based on inner–outer loop architecture. In this system, the outer loop position control adopts a PID controller optimized by Genetic Algorithm-based Particle Swarm Optimization (GA-PSO), while the inner loop attitude control employs a Linear Active Disturbance Rejection Controller (LADRC) with fuzzy algorithm-based adaptive tuning, forming a dual-loop control structure. Comparisons with traditional dual-loop cascaded PID controllers, conventional PID in the outer loop with LADRC in the inner loop, and conventional PID in the outer loop with fuzzy algorithm-based adaptive tuning in the inner loop demonstrate that the proposed control system can stably track the desired position and attitude angles under certain external disturbances, exhibiting excellent anti-disturbance capability and stability.

Robust Visual Landing Control of Quadrotor on a Moving Platform: A Sampled-Data Approach With Delayed Output and Disturbances

Robust Visual Landing Control of Quadrotor on a Moving Platform: A Sampled-Data Approach With Delayed Output and Disturbances

Enhancing quadrotor robustness control using image-based visual servoing (IBVS) with fuzzy logic

Visual servoing is a commonly employed approach in robotics and unmanned aerial vehicles (UAVs) that facilitates accurate object positioning and movement control by utilizing visual feedback. As quadrotors gain popularity, more control methods have been developed. This article presents a method for enhancing quadrotor robustness control using image-based visual servoing (IBVS) with fuzzy logic. Unlike traditional visual servoing, which relies on a fixed gain and often encounters challenges with velocity convergence and maintaining the object in the field of view, this method is designed to enhance the visual servo control of quadrotors by dynamically adjusting the gain of the IBVS system through a fuzzy logic controller. This controller adaptively adjusts the servo gain in response to feature errors and the depth of the object's feature points. MATLAB simulations clearly demonstrate the superior performance of this fuzzy logic integrated method compared to classical approaches, showcasing enhanced control capabilities in challenging environments.

Position and reduced attitude trajectory tracking control of quadrotors: Theory and experiments

Multirotor aerial vehicles are versatile flying robots that perform hovering, vertical take-off and landing, and aggressive maneuvers in a 3D environment. Due to their underactuated nature, the aerial vehicles' position and orientation cannot be controlled independently. For this reason, most of the quadrotors' tasks involved position tracking or regulation tasks. This paper focuses on the position-tracking problem of quadrotors using the reduced orientation of the vehicle, meaning that only two degrees of freedom of the robot's orientation are controlled. We propose an almost global exponential reduced attitude control law that aligns the aerial robot's thrust direction with the desired force that drives the robot along the desired position trajectory. For the translational subsystem, we propose a dynamic control law that drives the position and velocity of the quadrotors asymptotically to the desired trajectories. The proposed attitude control law is computationally simple, and thus, it is suitable to run on board. Finally, we provide experimental results performed on a low-cost quadrotor and a comparison study with a full-attitude controller to illustrate the performance and advantages of the proposed control laws.

A Novel Tailsitter UAV with Configurable Wings

In this study, we propose a novel tailsitter unmanned aerial vehicle with configurable wings using a parallel link mechanism. It has two flight modes: a hover mode and a forward flight mode by pitching, similar to conventional tailsitters. In addition, it can deform its airframe in each flight mode. In the hover mode, it can tilt the frame in the pitch direction while hovering. In the forward flight mode, it can change the configuration of the wings during forward flight. In experiments, we show that it can transition from the hover mode to the forward flight mode with three wing configurations: non-staggered wings (biplane) and positively and negatively staggered wings (tandem wing plane), using an attitude controller for conventional quadrotors.

Flight Control Based on Adaptive Output Feedback for Quadrotors Using Quaternions

Quadrotors are expected to play an active role in out-of-sight areas such as equipment inspection and transportation of supplies to disaster areas. However, ensuring stable and highly accurate automatic flights has become a significant challenge. Trajectory tracking control methods that combine adaptive output feedback control based on almost strictly positive real characteristics and backstepping strategy have been proposed for a quadrotor control system with nonlinearities. These methods have simple structures and are robust. However, existing adaptive control methods have the problem of singularities, owing to the use of Euler angles in the modeling of quadrotors. In this paper, we propose an adaptive control method that enables a wider range of attitude changes using quaternions. The effectiveness of the proposed method is validated through numerical simulations.

Unmanned Surface Vessel–Unmanned Aerial Vehicle Cooperative Path Following Based on a Predictive Line of Sight Guidance Law

This paper explores the cooperative control of unmanned surface vessels (USVs) and unmanned aerial vehicles (UAVs) in maritime rescue and coastal surveillance. The USV-UAV system faces challenges of disturbances and substantial inertia-induced overshooting during path following. A novel position prediction line of sight (LOS) guidance law is proposed to address these issues for USV path following control. Radial basis function-based neural networks (RBF-NNs) are used to estimate disturbances, and a high-order differentiator is used to design a velocity observer for unknown USV velocity. The UAV control system employs proportional–derivative (PD) control with feedforward compensation for quadrotor control design and utilizes a finite-time converging third-order differentiator to differentiate non-continuous functions. The simulation results demonstrate strong robustness in the proposed USV-UAV cooperative control algorithm. It achieves path following control in the presence of wind and wave disturbances and exhibits minimal overshoot.

Nonlinear scenario‐based model predictive control for quadrotors with bidirectional thrust

AbstractThe control of quadrotor vehicles under state and parameter uncertainty is a well studied problem that is vitally important to the deployment of these systems under real world conditions. In this article, we propose a linearization‐based extension to nonlinear systems of the existing scenario model predictive control (MPC) framework, which quantifies the impact of uncertainty on the vehicle dynamics through repeated sampling of the uncertainty space. Given the computational costs of such an approach, we also propose two simplifications of the scenario MPC algorithm that are significantly more tractable. In order to evaluate the performance of the algorithms, the specific problem of the control of a bidirectionally actuated quadrotor vehicle is considered. Simulations are carried out for each scenario MPC scheme as well as for a reference deterministic MPC scheme. When a sufficiently large sample count is considered, each of the scenario MPC algorithms achieves safer performance than the deterministic formulation without sacrificing any optimality. Additionally, the approximate solution techniques conclusively outperform the original nonlinear scenario MPC formulation for the same computational cost.

Quadrotor attitude control with a modified fixed‐time synergetic controller: A geometric analysis and experimental validation

AbstractThis article proposes a novel modified fixed‐time synergetic control (MFTSC) approach to address the quadrotor control problem in the presence of external disturbances. In contrast to previous fixed‐time synergetic control (FTSC) methods, the proposed approach employs an aggregate macrovariable expression with independent fractional powers. This expression expands the set of real numbers that the parameters of the fractional power can take, leading to a significantly higher rate of convergence toward optimal control parameters (more than 28‐fold), as demonstrated through geometric analysis. The stability of the proposed control system is established, and numerical simulations and experimental validation are conducted using a quadrotor test bench to corroborate the theoretical results.

On Robust Stabilization of Motion of a Quadrotor with Slung Load

One of the important tasks that can be performed by quadrotors is the transportation of various payloads. If the load is suspended from the quadrotor and can move relative to the quadrotors body, this motion must be taken into account in the control system, in particular, in order to suppress and prevent unwanted oscillations of the load. In the present paper, a mechanical system is considered that consists of a quadrotor and a load suspended to it with a weightless rod. It is assumed that the cross-sectional area of the load is large enough so that the aerodynamic forces acting on it cannot be neglected. It is known that for a number of shapes of payload casing, this aerodynamic force is not reduced only to the drag force, but also contains a component orthogonal to the drag force, that is, the lift force. In order to these forces, the quasi-steady approach is used. At the same time, accurate information about the aerodynamic capabilities for each particular payload is, generally speaking, not available. However, it is known that the values of aerodynamic coefficients for a fairly wide class of body shapes are lie in a specific range. Here we discuss the problem of developing the quadrotor control that would ensure robust stabilization of the ascent and descent of the system in the conditions of incomplete information about the aerodynamic load. A method is proposed for constructing the quadrotor control for robust stabilization of uniform vertical ascent and descent of the system as a whole. It is shown that this control ensures stabilization of the target mode within a fairly wide range of system parameters. Restrictions on the target speed of quadrotor motion are determined, violation of which makes the robust stabilization impossible.

Neural Network-Based Robust Guaranteed Cost Control for Image-Based Visual Servoing of Quadrotor.

In this article, a neural network (NN)-based robust guaranteed cost control design is proposed for image-based visual servoing (IBVS) control of quadrotors. According to the dynamics of three subsystems (yaw, height, and lateral subsystems) derived from the quadrotor IBVS dynamic model, the main control design is to solve the robust control problem for the time-varying lateral subsystem with angle constraints and uncertain disturbances. Considering the system dynamics, a two-loop structure is conducted. The outer loop uses the linear quadratic regulator to solve the Riccati equation for the lateral image feature system, and the inner loop adopts the optimal robust guaranteed cost control to solve the lateral velocity system. For the lateral velocity system, the optimal robust control problem is transformed to solve the modified Hamilton-Jacobi-Bellman equation of the corresponding optimal control problem utilizing adaptive dynamic programming. The implementation is accomplished with the time-varying NN and the designed estimated weight update law. In addition, the stability and effectiveness are proved by the theoretic proof and simulations.

Modeling and Control of Reconfigurable Quadrotors Based on Model Reference Adaptive Control

To expand the application prospects of quadrotors in challenging scenes such as those with dense obstacles and narrow corridors, task-driven reconfigurable quadrotors are highly desirable. Aiming to address hazard missions, in this paper, translational reconfigurable quadrotors and rotational reconfigurable quadrotors are proposed with their assumptions and mathematical models. Related motion control laws were designed using model reference adaptive control (MRAC) theory based on Lyapunov stability theory, whose validity was demonstrated by sufficient numerical simulations. The simulation results verify the feasibility of the proposed control laws and reveal the important effect of time delay on the stability of the motion control system. Additionally, the dependence of motion control’s stability on the time constant of reference system was discussed.

Hybrid offline–online neural identification-based robust adaptive tracking control for quadrotors

This paper proposes a novel hybrid offline–online neural identification-based robust adaptive control strategy for quadrotors subject to parameter uncertainties and external disturbances. A new method of using hybrid offline–online neural identification is developed to compensate for the residual force and moment caused by parameter uncertainties. Unlike previous methods that ignore the relevance of uncertainties in the time dimension, the proposed neural identification method mines temporal features of states from historical data by introducing long short-term memory (LSTM) networks, resulting in high identification accuracy. Furthermore, an online adaptation update law is designed to optimize the weights of the network estimates for strong robustness. Consequently, based on the identification of the network, a robust tracking controller on SE(3) is constructed, which is capable of attenuating the bounded disturbances by introducing anti-disturbance components. Finally, numerical simulations and experiments in the real physical world are carried out to verify the performance. The experimental results demonstrate that the proposed strategy not only achieves more accurate uncertainty identification in comparison to the existing methods, but also realizes a 44.28% reduction in the root-mean-square error (RMSE) of the position under the lump uncertainties, which illustrates enhanced robustness and generalizability. Video: https://youtu.be/3kIG5fcQaVE.

Fully Distributed Edge-Based Dynamic Event-Triggered Control for Multiple Quadrotors

Fully Distributed Edge-Based Dynamic Event-Triggered Control for Multiple Quadrotors

End-to-end control of quadrotor based on preference learning

End-to-end control of quadrotor based on preference learning

An improved switched prescribed finite time attitude control for quadrotors

SummaryThe paper is devoted to the prescribed finite time attitude control for quadrotors. A novel prescribed finite time function is introduced, which is independent of initial conditions and design parameters. And a switched prescribed finite time controller is firstly designed, such that the quadrotor can not only converge to the desired attitude in a prescribed time, but also guarantee the stability of the quadrotor after the settling time. Simultaneously, it effectively avoids chattering issues at the controller's switching points. Finally, the simulation comparisons are carried out between the proposed control strategy and infinite time, finite time, traditional prescribed finite time control schemes to demonstrate the superiority of the developed controller.