Control Of Unmanned Helicopter Research Articles

Extended State Observer-Based Command-Filtered Safe Flight Control for Unmanned Helicopter under Time-Varying Path Constraints and Disturbances

Extended State Observer-Based Command-Filtered Safe Flight Control for Unmanned Helicopter under Time-Varying Path Constraints and Disturbances

FTDO-based adaptive fuzzy fixed-time tracking control for uncertain unmanned helicopter with output constraints

During the actual flight of unmanned helicopters, there are widespread output constraints, system uncertainties and external disturbances, which bring significant threats to their safe flight. To keep the output constraints from violating predefined boundaries, the barrier Lyapunov function (BLF) is utilized in this paper. The system uncertainties are estimated by the fuzzy logic system (FLS). The compound disturbances composed of the external disturbances and the approximation errors caused by FLS are approximated by the fixed-time disturbance observers (FTDOs). According to the analysis of FTDOs and fixed-time stability theory, the observer errors and state errors converge to a region of the origin in fixed-time, and the appropriate parameters of FTDOs and controller are designed to ensure that the disturbance convergence time is faster than the one of the proposed controller, which further improves the stability of the system. Moreover, the convergence time of the FTDOs FTDOs and the proposed approach only depends on the design parameters under any initial conditions with constrained outputs. The performance of the proposed control approach is verified through the simulation results.

Time-varying gain extended state observer-based adaptive optimal control for disturbed unmanned helicopter

In this paper, the robust adaptive optimal tracking control problem is addressed for the disturbed unmanned helicopter based on the time-varying gain extended state observer (TVGESO) and adaptive dynamic programming (ADP) methods. Firstly, a novel TVGESO is developed to tackle the unknown disturbance, which can overcome the drawback of initial peaking phenomenon in the traditional linear ESO method. Meanwhile, compared with the nonlinear ESO, the proposed TVGESO possesses easier and rigorous stability analysis process. Subsequently, the optimal tracking control issue for the original unmanned helicopter system is transformed into an optimization stabilization problem. By means of the ADP and neural network techniques, the feedforward controller and optimal feedback controller are skillfully designed. Compared with the conventional backstepping approach, the designed anti-disturbance optimal controller can make the unmanned helicopter accomplish the tracking task with less energy. Finally, simulation comparisons demonstrate the validity of the developed control scheme.

Fully Actuated System Approach Based Prescribed-Time Fault-Tolerant Formation Control for Unmanned Helicopters Under Fixed and Switching Topologies

Fully Actuated System Approach Based Prescribed-Time Fault-Tolerant Formation Control for Unmanned Helicopters Under Fixed and Switching Topologies

Formation control of unmanned helicopters using the sliding mode controller method

Formation control of unmanned helicopters using the sliding mode controller method

Disturbance Observer-Based Safe Tracking Control for Unmanned Helicopters with Partial State Constraints and Disturbances

In this paper, a disturbance observer-based safe tracking control scheme is proposed for a medium-scale unmanned helicopter with rotor flapping dynamics in the presence of partial state constraints and unknown external disturbances. A safety protection algorithm is proposed to keep the constrained states within the given safe-set. A second-order disturbance observer technique is utilized to estimate the external disturbances. It is shown that the desired tracking performance of the controlled unmanned helicopter can be achieved with the application of the backstepping approach, dynamic surface control technique, and Lyapunov method. Finally, the availability of the proposed control scheme has been shown by simulation results.

Sliding mode tracking control for unmanned helicopter using extended disturbance observer

Sliding mode tracking control for unmanned helicopter using extended disturbance observer

Attitude tracking backstepping control for small unmanned helicopters based on adaptive neural network under unknown environment disturbances

To solve the attitude tracking control problem of small unmanned helicopters under unknown bounded disturbances, an attitude tracking backstepping controller based on adaptive radial basis function (RBF) neural network disturbance compensation is proposed in this paper. The unknown disturbance is estimated online and in real time through RBF neural network with a novel gradient descent weight update rate. A novel attitude tracking backstepping controller based on virtual control variables is designed, and the system stability is analyzed using the Lyapunov method. The experimental verification of the backstepping controller is carried out on the three-degrees-of-freedom helicopter. The experiments show the effectiveness and advancedness of the proposed adaptive neural network backstepping controller in suppressing unknown external disturbances compared with the robust adaptive integral backstepping.

Trajectory tracking control for unmanned helicopter based on RBFNN

This paper proposes a nonlinear adaptive radial basis function neural network (RBFNN) control method for Unmanned Helicopter. The control objective is to reduce the trajectory tracking error of the unmanned helicopter in the presence of system uncertainty and external disturbances. Based on the backstepping control technique, the controller of the unmanned helicopter are designed in order of position kinematics, position dynamics, attitude kinematics and attitude dynamics, and the block processing is used in the last three steps above.Then, RBFNN is added to compensate the error caused by external interference. Meanwhile, the derivatives of virtual controls are obtained by second-order command filter, and the stability of the system is analyzed by Lyapunov stability theorems. Finally, the simulation results verify the stability and robustness of the control method.

Decentralized modular hybrid supervisory control for the formation of unmanned helicopters

Formation control of Unmanned Aerial Vehicles (UAVs) requires them to tightly cooperate to reach and keep the formation, while avoiding collision. This paper proposes a novel decentralized hybrid supervisory control approach for the formation control of multiple UAVs. This is achieved by developing a symbolic motion planning technique to polarly partition the motion space resulting in a finite state discrete event model for the motion dynamics of each UAV. Then, a modular discrete supervisor is designed for different components of the formation mission including reaching the formation, keeping the formation, and collision avoidance. Further, for the collision avoidance mechanism, a novel top-down decomposition-based approach is developed to design local supervisors decentralizedly. It is formally proved that with the proposed top-down decomposition-based approach, the (locally) supervised UAVs, as a whole, can cooperatively satisfy the desired (global) collision avoidance specification. The proposed decentralized supervisory control algorithm is also verified through a hardware-in-the-loop simulator for the formation control of unmanned helicopters.

Design of Yaw Controller for a Small Unmanned Helicopter Based on Improved ADRC

Yaw control is significant to the attitude control of small unmanned helicopters (SUHs). Since the existing robust control method cannot be applied to the SUH with unknown dynamics and disturbances, this paper proposes an improved active disturbance rejection control (IADRC) to solve the problem. The IADRC obtains the optimal solution of the actuator gain ([Formula: see text]) by gradient descent. Besides, this paper summarizes some experiences during the tuning process of ADRC, which significantly reduces the difficulty of designing ADRC. Finally, the experimental results show that the proposed method is better than the traditional PID in robust and tracking control performance.

Attitude control of mine inspection unmanned helicopter based on cellular membrane computing

Attitude control of mine inspection unmanned helicopter based on cellular membrane computing

Attitude and height tracking control of unmanned helicopters with disturbances via disturbance observer-based composite dynamic surface control

In this paper, the attitude and height tracking control problem is studied for unmanned helicopters with disturbances. To solve the problem, a composite control scheme is proposed based on the combination of dynamic surface control and disturbance observer-based control techniques. The control design includes two parts. In the first part, some nonlinear disturbance observers are designed to accurately estimate the helicopter’s disturbances in different channels. In the second part, based on the disturbance estimates and dynamic surface control technique, a composite dynamic surface tracking controller is designed. Under the proposed composite controller, the attitude and height tracking errors are uniformly ultimately bounded and they can be regulated to be very small by selecting proper controller parameters. For one thing, the proposed control scheme avoids “explosion of terms”, which generally exists in conventional backstepping control and provides a simpler control design. For another thing, without sacrificing the nominal control performances, the anti-disturbance ability of the closed-loop helicopter system is enhanced by using disturbance observers and feedforward compensations. Numerical simulations demonstrate the effectiveness and advantages of the proposed composite tracking controller.

Flight Control System Design and Autonomous Flight Control of Small-Scale Unmanned Helicopter Based on Nanosensors

Due to the limitation of the size and power, micro unmanned aerial vehicle (MUAV) usually has a small load capacity. Aiming at the problems of limited installation space and easy being interfered in flight attitude measurement of the small-scale unmanned helicopter (SUH), a low-cost and lightweight flight control system of the SUH based on ARM Cortex-M4 core microcontroller and Micro-Electro-Mechanical Systems (MEMS) sensors is developed in this paper. On this basis, in order to realize the autonomous flight control of SUH, firstly, the mathematical model of the SUH is given by using the Newton-Euler formulation. Secondly, a cascade flight controller consisting of the attitude controller and the position controller is developed based on linear active disturbance rejection control (LADRC) and proportional-integral-derivative (PID) control. Furthermore, simulations are conducted to validate the performance of the attitude controller and the position controller in MATLAB/SIMULINK simulation environment. Finally, based on the Align T-REX 470L SUH experimental platform, the hovering experiment and the route flight experiment are also carried out to validate the performance of the designed flight control system hardware and the proposed control algorithm. The results show that the flight control system designed in this paper has high reliability and strong anti-interference ability, and the control algorithm can effectively and reliably realize the attitude stabilization control and route control of the SUH, with high control accuracy and small error.

Attitude control of an unmanned patrol helicopter based on an optimised spiking neural membrane system for use in coal mines

For the attitude control of unmanned helicopters used in the intelligent patrolling of coal mines, a spiking neural membrane system is introduced for attitude optimisation control. First, a geometr...

Attitude control of an unmanned patrol helicopter based on an optimised spiking neural membrane system for use in coal mines

For the attitude control of unmanned helicopters used in the intelligent patrolling of coal mines, a spiking neural membrane system is introduced for attitude optimisation control. First, a geometry-based attitude dynamics model suitable for coal mine scenarios is constructed. Second, in accordance with the attitude dynamics model, an extended spiking neural membrane system (ESNMS) is constructed, and an optimised spiking neural membrane system (OSNMS) and accompanying algorithm are designed to optimise the ESNMS. Then, the attitude control performance of the developed system is theoretically analysed. Finally, through the simulation of a semiphysical experimental platform, trajectory tracking is effectively realised. Under normal and wind disturbance conditions, comparisons with the traditional synovium controller (TSC) and linear feedback controller (LFC) show that the performance of the designed OSNMS is greatly improved, and the experimental results show that the OSNMS has good stability and effectiveness.

Attitude Tracking Control of Small-Scale Unmanned Helicopters Using Quaternion-Based Adaptive Dynamic Surface Control

In this paper, a quaternion-based adaptive dynamic surface control method is proposed for attitude tracking control for small-scale unmanned helicopters with external disturbance and uncertain dynamics. The quaternion formalism is introduced and a quaternion-based multi-input-multi-output nonlinear model is derived from the attitude dynamics of a small-scale helicopter. The low-complexity controllers are designed by the dynamic surface control method as it eliminates the problem of the explosion of items. The singularity problem is avoided by substituting Euler kinematic equations in the nonlinear model with quaternion expressions and integrating the quaternion expressions into the design process of the dynamic surface control. For improving the robustness of the control system, the radial basis function networks are applied to approximate the uncertain dynamics. The external disturbance is also compensated in the controllers’ design. This paper proves that the proposed method can guarantee the uniformly ultimate boundness of this attitude system. Simulation results are presented finally and show the effectiveness of this control approach.

Randomized probabilistic approach for parametric uncertainties in unmanned helicopters

SummaryParametric uncertainties and the problems associated with the design of robust state feedback control tends to be a major concern for achieving stable operation of nonlinear systems. To overcome these drawbacks, this article provides a perspective on a randomized algorithm based probabilistic control for nonlinear systems. The control approach aims at development of randomized algorithms for control of unmanned helicopters which are subjected to uncertainties. A controller gain is synthesized by developing a robust probabilistic approach using sequential randomized algorithm with the two degree of freedom helicopter system. Subsequently, the stability and reachability for the action of developed controller is validated with the help of Lyapunov asymptotic stability and reach tube analysis, and the corresponding results were analyzed. A comparative assessment of simulation and real‐time control results of projected approaches on helicopter model are presented for validation of the controller response.

Robust formation control for unmanned helicopters with collision avoidance

A systematic framework is proposed which addresses fully distributed formation control of under actuated unmanned helicopters (UHs) with resisting the external disturbances and model uncertainty capability. In this paper, a hierarchical control strategy for the whole closed-loop under-actuated UHs system is applied. The adaptive terminal sliding mode (TSM) control technique is employed to design an continuous fast robust controller in each loop and an integral filter is introduced between the position loop and the attitude loop to ensure that the attitude controller can track the desired attitude command. The stability of the whole closed-loop system is guaranteed through Lyapunov theory and input-to-state stability (ISS). Compared to the previous related works, our main contribution is that the proposed adaptive control strategy is fully distributed and scalable, which is independent any global information of the network graph and is independent of the UHs’s scale and we proved the stability of the closed-loop. Finally, the effectiveness and superiority of the designed strategy are demonstrated by numerical simulations.

Disturbance observer-based autonomous landing control of unmanned helicopters on moving shipboard

In this paper, the autonomous landing control issue on moving shipboard is investigated for unmanned helicopters subject to disturbances. The issue is studied by stabilizing the error system of the helicopter and the shipboard. The landing process is divided into two phases, i.e., homing phase, where a hierarchical double-loop control scheme is developed such that the helicopter is forced to hover synchronously at a certain altitude over the shipboard, and landing phase, where a composite landing control scheme is proposed such that the helicopter lands vertically on the shipboard in synchronization with its attitudes. The velocity and acceleration information of the shipboard as well as lump disturbances is estimated through joint state and disturbance observers. The estimates are then incorporated into the baseline feedback controller, formulating composite active anti-disturbance landing control schemes. A continuous terminal sliding mode control method is proposed for the feedback controller design, which not only effectively mitigates the chattering of the control action, but also simplifies the design process of the controller. Numerical simulations demonstrate the effectiveness and superiorities of the proposed control schemes.