Control Of Helicopter Research Articles

ANALISIS KINEMATIK MANUVER TERBANG VERTIKAL PADA KOMPONEN SWASH PLATE, ROTOR HEAD DAN ROTOR BLADES HELIKOPTER SEJENIS NBO - 105 MENGGUNAKAN CATIA V5R16

Helicopters have a unique advantage over airplanes in that they can adjust the direction of their blades to generate lift in any direction, allowing them to perform vertical takeoffs and landings and hover in one spot. This capability makes them highly valuable for a variety of operations, including transportation. A crucial component in the helicopter control system is the swash plate, which allows for adjustments to the angle of the rotor blades to achieve specific maneuvers.To manufacture and model components such as the swash plate, rotor head, and rotor blades, CATIA V5R16 software can be used. This involves modeling the individual parts in the workbench part design, assembling them in the workbench assembly design, or conducting kinematic analysis using the DMU Kinematics workbench to obtain values for linear velocity, angular velocity, linear acceleration, and angular acceleration. When compared to manual calculations, the differences between the results produced by the CATIA V5R16 software and theoretical calculations are negligible. Therefore, it can be concluded that CATIA V5R16 software is highly capable and suitable for conducting kinematic analysis of three-dimensional components.

Finite-time prescribed performance trajectory tracking control for the autonomous underwater helicopter

To address the complex trajectory tracking problem of AUH near the seabed when performing high-precision operations such as comprehensive underwater inspections for offshore engineering structures, a prescribed performance control strategy with a finite-time performance function (FTPF) and the fast terminal sliding surface is proposed. The influence of ocean current is fully considered by the combination of ocean current velocity estimated by a current observer and ocean current disturbance in the dynamic model. An arctan-type disturbance observer and neural network are designed to compensate for environmental disturbances, model uncertainty, and thruster failure effects on the system. The system stability is proven by the Lyapunov method, and the numerical simulation shows that the proposed scheme is effective, robust, and efficient, even under disturbances and thruster failure.

Heading rate controller for unmanned helicopters based on modified ADRC

Heading rate controller for unmanned helicopters based on modified ADRC

Observer‐based robust optimal control for helicopter with uncertainties and disturbances

AbstractUnknown model uncertainties and external disturbances widely exist in helicopter dynamics and bring adverse effects on control performance. Optimal control techniques have been extensively studied for helicopters, but these methods cannot effectively handle flight control problems since they are sensitive to uncertainties and disturbances. This paper proposes an observer‐based robust optimal control scheme that enables a helicopter to fly optimally and reduce the influence of unknown model uncertainties and external disturbances. A control Lyapunov function (CLF) is firstly constructed using the backstepping method, then Sontag's formula is utilized to design an inverse optimal controller to stabilize the nominal system. Furthermore, it is stressed that the radial basis function (RBF) neural network is introduced to establish an observer with adaptive laws, approximating and compensating for the unknown model uncertainties and external disturbances to enhance the robustness of the closed‐loop system. The uniform ultimate boundedness of the closed‐loop system is ensured using the presented control approach via Lyapunov stability analysis. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control strategy.

Fault‐tolerant attitude tracking control of tandem rotor helicopter considering internal actuator saturation and external wind gust

SummaryTandem rotor helicopter is configured with two main rotors distributed along the longitudinal direction and without anti‐torque tail rotor. Therefore, the control strategy of tandem rotor helicopter can be quite different from that of traditional helicopter systems. In this article, a fault‐tolerant attitude tracking controller is presented for tandem rotor helicopter, with considerations of external wind disturbance and internal actuator problem. First, attitude control oriented dynamic model of the tandem rotor helicopter is constructed, in which both actuator fault and saturation are involved. Base on statistical characteristics of practical wind condition as well as aerodynamic properties of the helicopter rotors, a detailed wind load model is further established. Then, a fault‐tolerant attitude tracking controller is proposed for the tandem rotor helicopter system by incorporating nonsingular terminal sliding mode control with an adaptive super twisting algorithm, which allows a simultaneous regulation of the three angular motions via two propeller rotors. Finally, based on Quanser's 3‐dof helicopter system, comparative simulation tests are performed to demonstrate the effectiveness as well as advantages of the proposed fault‐tolerant controller design.

Dynamics analysis and control of coaxial high-speed helicopter in transition flight

Coaxial high-speed helicopters (CHHs) provide an interesting combination of the vertical takeoff and landing capabilities of helicopters and the efficient forward flight of airplanes. During the transition mode, the employed control laws must be able to handle the changing control authorities, which result from the special aerodynamic layout of coaxial rotors, propeller and aero-surfaces. In this paper, the dynamic characteristics of the CHH in transition mode are analyzed, and a unified Decoupled Allocation Transition Control (DATC) method is proposed to achieve a stable flight and improve the handling quality. The presented control architecture is designed by the explicit model following (EMF) and classical control techniques with a T-S fuzzy model-based parameter scheduling mechanism, in which the actuator saturation is considered. Furthermore, the developed multi-stage control allocations are capable of handling the changing control authorities of actuators, and efficiently distribute the required control actions between coaxial rotors, propeller and aero-surfaces. Thus, the required control authority transition is achieved smoothly. The numerical simulations demonstrate the feasibility and performance of the proposed transition flight control laws, and this method will be eligible for a potential practical implementation to CHH vehicles.

Motion Control of Autonomous Underwater Helicopter Based on Linear Active Disturbance Rejection Control with Tracking Differentiator

As a new disk-shaped autonomous underwater vehicle (AUV), the autonomous underwater helicopter (AUH) is devoted to subsea operations, usually diving into the seabed and docking with a subsea docking system. Due to the motion control’s performance, the AUH’s stability and steady-state accuracy are affected remarkably while docking. Moreover, considering the difficulties of hydrodynamic modeling of AUHs, the classical model-based control method is unsuitable for AUHs. Moreover, there is a large gap between the hydrodynamic simulation results and real situations. Hence, based on the data-driven principle, the linear active disturbance rejection control with a tracking differentiator (LADRC-TD) algorithm is employed for AUH depths and heading control. As the simulation experiments prove, LADRC and LADRC-TD have better anti-interference performance when compared with PID. According to the pool experiments, overshoots of the LADRC-TD are 20 cm and 3° for the depth control and heading control, respectively, which are superior to PID and LADRC. Meanwhile, the steady-state accuracy of the LADRC-TD is ±21 cm and ±2.5° for the depth and heading control, respectively, which is inferior to PID and the same as LADRC.

Integral Backstepping Sliding Mode Control for Unmanned Autonomous Helicopters Based on Neural Networks

In this paper, we propose an adaptive control approach to deal with the problems of input saturation, external disturbances, and uncertainty in the unmanned autonomous helicopter system. The dynamics of the system take into account the presence of input saturation, uncertainty, and external disturbances. Auxiliary systems are built to handle the input saturation. The neural networks are applied to approximate the uncertain terms. The control scheme combining integral backstepping and sliding mode control is developed in position and attitude subsystems, respectively. In the closed-loop system, the boundedness of the signals is proved by means of the Lyapunov theory. The simulation demonstrates that the approach has good robustness and tracking performance.

Trajectory tracking anti-disturbance control for unmanned aerial helicopter based on disturbance characterization index

Trajectory tracking anti-disturbance control for unmanned aerial helicopter based on disturbance characterization index

Prescribed-time adaptive constraint control of an uncertain nonlinear 2-DOF helicopter

This paper addresses the problem of attitude tracking for a 2-Degree of Freedom (DOF) helicopter system with uncertainties. Euler-Lagrange equations are utilized to develop a nonlinear model for the helicopter, considering the control input constant coefficients and system parameters as unknown. The prescribed-time control approach is proposed using adaptive backstepping to track the desired pitch and yaw positions separately. In Addition, a constrained function is also used to avoid the risk of a larger signal when time gets closer to the appointed settling time. Through the application of the theory of Lyapunov stability, it is shown that the proposed strategy ensures that all closed-loop signals are bounded, and all the states converge within the prescribed time. A significant advantage of this approach is the ability to pre-specify the upper bound of the settling time. Finally, the efficacy and control capabilities of the proposed scheme are verified by obtaining the simulation results on the Quanser 2-DOF helicopter.

Cascaded Model Predictive Control of a Tandem-Rotor Helicopter

This letter considers cascaded model predictive control (MPC) as a computationally lightweight method for controlling a tandem-rotor helicopter. A traditional single MPC structure is split into separate outer and inner-loops. The outer-loop MPC uses an SE2(3) error to linearize the translational dynamics about a reference trajectory. The inner-loop MPC uses the optimal angular velocity sequence of the outer-loop MPC to linearize the rotational dynamics. The outer-loop MPC is run at a slower rate than the inner-loop allowing for longer prediction time and improved performance. Monte-Carlo simulations demonstrate robustness to model uncertainty and environmental disturbances. The proposed control structure is benchmarked against a single MPC algorithm where it shows significant improvements in position and velocity tracking while using significantly less computational resources.

Disturbance-Observer-Based Adaptive Fuzzy Tracking Control for Unmanned Autonomous Helicopter With Flight Boundary Constraints

In this article, a disturbance-observer-based adaptive fuzzy tracking control scheme is proposed for a medium-scale unmanned helicopter of six degrees of freedom in the presence of system uncertainties, flight boundary constraints, and external disturbances. A flight boundary protection algorithm is proposed to ensure its flight trajectory within the given safety range. A fuzzy logic system is utilized to estimate the system uncertainties and a nonlinear disturbance observer is adopted to handle the unknown compound terms of the external disturbances and the estimation errors resulting from the fuzzy logic system. An inverse optimal control approach is then used to avoid solving the Hamilton–Jacobi–Bellman equation in minimizing a cost function in the attitude loop. It is shown via the Lyapunov method that the desired safe tracking performance of the position loop and attitude loop of the controlled unmanned helicopter can be achieved. Simulations are provided to illustrate the effectiveness of the proposed control scheme.

Robust Attitude Control of Helicopters with Three-Degree Freedom Based on Intermittent Event-Triggered Mechanism

In the field of the widely used helicopter, this paper studies whether the helicopters with three-degree freedom (3DOF helicopters) have a new control method of stable attitude. Therefore, two research methods are adopted. One is to use intermittent control, so as to achieve control stability in a short time without its inputting. The other is to find and update the time needed to meet the next control through the event-triggered mechanism. A theorem is given to prove the feasibility of these methods, and Lyapunov’s second law is also applied in this paper to analyze the stability of the model designed for robust attitude control. Besides, we use the linear matrix inequality solver to solve the feedback gain of the controller in the theorem. Finally, through MATLAB simulation, the system error state of helicopters tends to zero under intermittent control, which highlights the advantages of short communication time and few times of simulation, thus achieving the simulation goal.

Robust optimal attitude control for hexarotors with disturbances, uncertainties, and delays

AbstractA robust optimal attitude controller for hexarotor helicopters is proposed. Compared to the previous research studies on hexarotors, the current study takes account of the influences of non‐linear and coupling dynamics, structured and unstructured uncertainties, external time‐varying disturbances, and input time delays. A linear time‐invariant system is derived for each Euler angle by considering the actual rotational dynamic model as a nominal non‐linear system plus an equivalent perturbation, including non‐linear and coupling dynamics, uncertainties, disturbances, and time delays. Using this approach, a Linear Quadratic Regulation controller is first designed for the nominal linear system of each angle to accomplish the desired tracking performances. Then, a robust compensator based on the robust compensation method is proposed to counteract the effects of the equivalent perturbation on the system. Moreover, the robust attitude tracking property and uniform asymptotical stability of the closed‐loop hexarotor system are proved using Lyapunov stability theory. Several simulations have been performed to demonstrate the effectiveness and robustness of the proposed controller. Finally, experimental results are provided to confirm the robust performance of the proposed controller.

Robust Adaptive Control for a Small Unmanned Helicopter Using Reinforcement Learning.

This article presents a novel adaptive controller for a small-size unmanned helicopter using the reinforcement learning (RL) control methodology. The helicopter is subject to system uncertainties and unknown external disturbances. The dynamic unmodeling uncertainties of the system are estimated online by the actor network, and the tracking performance function is optimized via the critic network. The estimation error of the actor-critic network and the external unknown disturbances are compensated via the nonlinear robust component based on the sliding mode control method. The stability of the closed-loop system and the asymptotic convergence of the attitude tracking error are proved via the Lyapunov-based stability analysis. Finally, real-time experiments are performed on a helicopter control testbed. The experimental results show that the proposed controller achieves good control performance.

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.

Adaptive Neural Control of a 2DOF Helicopter with Input Saturation and Time-Varying Output Constraint

An adaptive neural control for uncertain 2DOF helicopter systems with input saturation and time-varying output constraints is provided. A radial basis function neural network is used to estimate the uncertainty terms present in the system. The saturation error and the external disturbance are considered as a composite disturbance, and an adaptive auxiliary parameter is introduced to compensate it. An asymmetric barrier Lyapunov function is employed to address the constraint violation of the system output. The closed-loop stability of the system is then demonstrated by Lyapunov theory analysis. Simulation results demonstrate the effectiveness of the control strategy.

Hybrid event-triggered tracking control for unmanned autonomous helicopter under disturbance and deception attacks

This paper studies the hybrid event-triggered tracking control based on an unmanned autonomous helicopter (UAH) and an unmanned ground vehicle (UGV) under unmeasurable states, transmission delay, external disturbance, and deception attacks. By designing a switching condition, a hybrid event-triggered scheme (ETS) is proposed to realize an elegant trade-off between less data transmissions and control performance. Then, based on the designs of the observer and tracking controller, an augmented closed-loop system is established, and a sufficient condition on uniform ultimate boundedness is presented. Moreover, a co-design method of the hybrid ETS, observer, and controller is obtained via linear matrix inequalities (LMIs), which is further extended by utilizing an improved adaptive hybrid ETS. Finally, some simulation and comparisons are exploited to illustrate the proposed method.

Modeling and Robust Tracking Decoupling Control of a Coaxial Unmanned Helicopter Based on the Improved Alternating Direction Method of Multipliers.

In this paper, a robust tracking control strategy based on the dynamic feedback linearization method is proposed for the nonlinear and highly coupled dynamic characteristics of coaxial unmanned helicopter. The mathematical model of the coaxial unmanned helicopter is determined by fault analysis. Then the high-order state system is dynamically feedback linearized by extending the state variables, and the dynamic characteristics of the zeros are analyzed according to the expected tracking characteristics of the inner loop. The pole placement of the subsystem realizes robust monitoring of height and position commands by designing robust compensators. On this basis, an outer loop proportional derivative controller is designed for the horizontal positioning subsystem to realize position tracking. Loop tracking simulation ensures the good separation characteristics of feedback linearization method, and trajectory tracking simulation under fault conditions ensures the control ability and durability of the designed controller.

Adaptive neural networks trajectory tracking control for autonomous underwater helicopters with prescribed performance

An autonomous underwater helicopter (AUH) is a type of autonomous underwater vehicle (AUV) that is capable of fixed-point hovering, precise and free take-off, and landing. It is effective for underwater ultra-mobile tasks, including mobile observation networks, resource exploration, and data connection. This paper aims to investigate an AUH trajectory tracking controller based on the prescribed performance method, considering the influence factors such as current disturbance, modeling uncertainty and thruster faults. A novel preset time performance function is designed in which the stable terminal time of the system can be specified explicitly, and the convergence rate of the system's dynamic process may be altered by adjusting the parameters, making it more intuitive for the designer. A speed observer was introduced to address this problem of measuring the required state information from the AUH's sensors in practice, which was enhanced using a radial basis function neural network (RBFNN) to approximate external perturbations and uncertainties. The stability of the closed-loop AUH system is proved by using Lyapunov theory. The feasibility and effectiveness of the proposed algorithm proposed approach were eventually verified by two sets of simulations for different thruster fault forms.