Attitude Control Problem Research Articles

Planning Aggressive Drone Manoeuvres: A Geometric Backwards Integration Approach

This paper addresses the problem of performing aggressive manoeuvres by using multirotor vehicles that include passing through any specific point within the full state space of the vehicle. To this end, the design of optimal trajectories considers the dynamical model of the vehicles by numerically integrating it backwards in time, in the manifold where the dynamics evolve, and dividing the manoeuvres into three distinct phases to accommodate any combination of initial, desired, and final states. In the first phase, the vehicles fly from an initial to a launch configuration to achieve the necessary momenta to reach the desired one in the second phase. To ensure the feasibility of executing the second phase, the relation between snap and body torques is exploited by commanding the vehicles to track geodesic curves on SO(3) during the backwards integration. The vehicles are then driven to a final configuration in the third phase. Most existing solutions to execute aggressive and precise manoeuvres with these rotorcraft focus either on the attitude control problem, leaving the position in open-loop, or use different controllers for different sections of the manoeuvre. In this work, a single tracking controller is considered to validate the proposed trajectory planning strategy in a realistic simulation environment, which involves the PX4 firmware, and in a controlled experimental setup. The results demonstrate that accurate tracking of the designed trajectories enables the vehicles to perform 360-degree loops at great speed and manoeuvres that facilitate the exchange of a parcel between two multirotor vehicles during flight.

Finite-horizon approximate optimal attitude control based on adaptive dynamic programming for ultra-low-orbit satellite

This study investigates the finite-horizon approximate optimal attitude control problem for ultra-low-orbit satellites, addressing the complexities introduced by substantial disturbance, actuator faults, actuator saturation, and time constraint. Initially, a fixed-time concurrent learning fault and disturbance estimation approach is proposed that relieves persistent excitation constraints and isolates different influences individually. Subsequently, the cost function is designed with actuator fault estimation, ensuring that the control strategy consistently adheres to actuator saturation constraints and can compensate for current faults. Furthermore, based on the adaptive dynamic programming, an approximate optimal attitude control approach is proposed, which employs time-varying activation functions to approximate the optimal cost function. A fixed-time neural network weight adaptation strategy is designed to ensure the precision and reliability of the approximation. Finally, the numerical simulation confirms the validity and practical applicability of the proposed approach in satellite attitude control systems.

Predefined time attitude control of aircraft based on predefined time sliding mode control

This paper proposes a sliding mode control strategy with predefined time convergence for addressing the attitude control problem of aircraft. Firstly, a predefined time extended state observer is developed to realize the estimation of modelling error, uncertainty and external disturbance of aircraft within a predefined time. Secondly, a predefined time non-singular terminal sliding mode and a predefined time sliding mode reaching law are proposed for attitude control of aircraft. Especially, to address potential singularities arising from negative power terms, a switching strategy is employed. Finally, the numerical simulations and Monte Carlo test are used to validate the effectiveness of the proposed controller.

Reentry vehicle fixed-time terminal guidance and attitude control with impact angle constraints

The motivation of this paper is to handle the terminal guidance and attitude control problem for the unpowered reentry vehicle in the diving phase, which is crucial for interception to the target. The most important objectives of this study are to intercept the maneuvering target with the miss distance and impact angle error as small as possible. First, the second-order derivatives of the aerodynamic angles are derived with the fin deflections as control input, which is objective to avoid the tracking of reentry vehicle body angle rate command in the traditional methods. Second, a novel fixed-time time-varying parameter nonsingular terminal sliding mode guidance law is proposed to improve the convergence speed of line-of-sight angle rate, which can avoid control input singularity without switching to the polynomial form when the error approaches the origin. Thirdly, a new global time-varying sliding mode is developed to design the attitude controller, with the predefined fixed convergence time and analytical solution. The system states are proved to be fixed-time convergence based on the Lyapunov stability theory. Six-degree-of-freedom flight simulations are conducted to validate the superiority of the proposed algorithm in terms of miss distance, impact angle error, intercepting time and control input energy.

Multi-Body Dynamics Modeling and Simulation of Maglev Satellites

The Lorentz force magnetic levitation gim2bal stabilized platform (LFMP), as a new generation of high-precision turntable for maglev satellites, can meet the requirements of future spacecraft for ultra-high attitude pointing accuracy and stability. To solve the problem of three-module multi-body attitude control under maneuvering conditions, the platform subsystem is first dynamically modeled based on the second type of Lagrangian equation, and the payload subsystem is dynamically modeled based on the Newton–Euler method. Secondly, a multi-loop control system is designed, consisting of high-precision and fast attitude pointing control for the payload, position tracking control for the platform subsystem, and tracking control for the maglev module. The final simulation results verified the feasibility and effectiveness of the payload-centered control method. An evaluation of the stability with a specific model has been performed, and the attitude accuracy of the payload is within 0.00002° and the attitude stability is within 0.00005°/s.

Characterization and verification of the optimal feedback gain of a satellite magnetorquer-based attitude control system

In spacecraft mission planning and operation, the attitude determination and control subsystem (ADCS) of a satellite provides information about the orientation of the satellite in the inertial reference frame. Furthermore, this subsystem produces the control actions required to adjust the orientation of the satellite, especially in the low-Earth orbit (LEO) regime. This paper focuses on the satellite’s three-axis attitude control problem within the context of active and passive control, which includes detumbling control, pointing control, magnetic control, and attitude stabilization after solar panel wing deployment using magnetorquers as the primary actuators. The objective is to stabilize and reduce the angular rate while orienting the satellite to the desired attitude. The proposed satellite attitude control system (ACS) strategies are designed, developed, characterized, and verified. These strategies encompass the B-dot control algorithm for detumbling control along with pointing control and attitude stabilization after solar panel wing deployment. hardware-in-the-loop simulation (HiLs) tests are conducted to assess the performance of the satellite magnetorquer-based ACS in the presence of noise. These tests involve a relative Earth’s magnetic field (EMF) generator in conjunction with SGP-4-based satellite orbital propagator high-level control software. Additionally, cascade proportional-integral-derivative (PID) and state-dependent Riccati equation (SDRE) controllers are implemented to generate sufficient torque using three-axis magnetorquers on a frictionless air-bearing platform. The platform is balanced to closely simulate the dynamic motion of a spacecraft in space. The testing includes a single initial condition and three inertia conditions for stabilization after solar panel wing deployment. Finally, the effectiveness of the cosimulation as a primary experiment through an integrated HiLs process is validated. This comprehensive approach confirms the control system’s performance and its ability to meet mission requirements.

Research on Attitude Analysis of Hydraulic Support Based on Column Length

The existing hydraulic support attitude monitoring and control methods integrate multiple sensing technologies, but it is difficult to apply and promote due to unclear monitoring mechanisms, complicated types, and a large number of sensors. Aiming at the problem of attitude monitoring and control of hydraulic support, firstly, the kinematics mathematical model of hydraulic support is established by the key marker point method and the two-dimensional bar system model, and the forward and inverse solution algorithm of hydraulic support attitude based on the double-drive length of front and rear columns is proposed. Secondly, the rigid body dynamics simulation model of hydraulic support is constructed to verify the theoretical analytical model and prove the correctness of the algorithm. The rigid body simulation model can be used as the attitude monitoring system of hydraulic support. Thirdly, considering the influence of material elastic deformation, a rigid-flexible coupling dynamic simulation model of hydraulic support is established to explore the influence of elastic deformation of components on the attitude of hydraulic support and its causes. On this basis, the rigid-flexible coupling dynamic simulation model of the hydraulic support with clearance is established by replacing the revolute pair in the simulation model with the solid axis pin connection unit. The influence of the axis pin connection clearance on the attitude of the hydraulic support and its causes are explored, and the actual attitude and change characteristics of the hydraulic support under simulated real conditions are obtained. Finally, considering the force compression of the hydraulic cylinder of the column, the rigid-flexible and machine-liquid coupling dynamic simulation model of the hydraulic support with clearance is constructed.

Dynamic event‐triggered adaptive neural nonsingular fixed‐time attitude control for multi‐UAVs systems

SummaryThis article looks into the dynamic event‐triggered fixed‐time adaptive attitude control problem for nonlinear six‐rotor unmanned aerial vehicle (UAV) with external disturbances. The multiple six‐rotor UAVs considered are regarded as nonlinear multi‐agent systems (MASs), and each subsystem has multiple inputs. Under the framework of backstepping recursive design, an effective adaptive fixed‐time control method is proposed by combining neural networks (NNs) technology and fixed‐time theory. NNs are utilized to handle unknown nonlinearity and unmodeled parts in attitude systems. The hyperbolic tangent function is ushered to address the singularity problem that may occur in the derivative of the controller, thereby averting the phenomenon of chattering. For the sake of alleviating the correspondence burden of multiple UAVs attitude systems, a modified dynamic event‐triggered mechanism (DETM) is ushered. The developed controller swears for that all signals of the six‐rotor UAV attitude systems are bounded and the tracking errors converge to a small neighborhood of the origin within a fixed‐time interval. Eventually, with the help of simulation results, the effectiveness of the proposed control scheme was verified.

Composite anti-disturbance dynamic positioning for mass-switched unmanned marine vehicles with multisource disturbances and actuator saturation: A switched model method

This article focuses on the composite anti-disturbance dynamic positioning (CADDP) control problem for the unmanned marine vehicle (UMV) system subject to mass switching, multisource disturbances and actuator saturation. The multisource disturbances include the unmeasurable modeled disturbances and measurable unmodeled disturbances. First, a switched model is introduced to describe the mass-switched UMV (MSUMV) system. Then, a series of switching observers are built to capture the unmeasurable disturbances. Meanwhile, the convex hull technique is exploited to address the actuator saturation. Further, based on the disturbance observer, the CADDP control scheme is developed to alleviate the influences of the multisource disturbances and actuator saturation, and to achieve the dynamic positioning (DP) of the MSUMV model. In the end, the established CADDP control strategy is carried on a supply vessel to illustrate the feasibility of the developed theory.

Adaptive sliding mode and RBF neural network based fault tolerant attitude control for spacecraft with unknown uncertainties and disturbances

Taking the external disturbance, model uncertainty, actuator failure, and actuator saturation into consideration, this paper investigates the nonlinear fault-tolerant attitude control problem for the spacecraft. First, to deal with the disturbance and uncertainty with unknown boundaries, an adaptive sliding mode control method is proposed to stabilize the state variables of the spacecraft attitude control system. Then the actuator failure and saturation are further considered, and the second spacecraft fault-tolerant attitude controller is derived based on adaptive sliding mode control and radial basis function (RBF) neural networks. The adaptive control gains reduction technique is applied in the design process, which can weaken the chattering phenomenon of the controller to some extent, and the stability of the attitude control system is analyzed through Lyapunov theory. In the proposed controller, model information and external disturbance are not required and only the system states are needed. Furthermore, the boundaries of the model uncertainty, external disturbance, actuator fault and saturation are assumed to be existing but unknown by the proposed controllers. These features make the proposed attitude controllers need few modeling information of the spacecraft, or maintain strong robustness even if the model or external environment occurs significant changes. Finally, numerical simulations demonstrate the great performance of the proposed fault-tolerant attitude control method.

Multiple model fault diagnosis and fault tolerant control for the launch vehicle’s attitude control system

Abstract For the launch vehicle attitude control problem, traditional methods can seldom accurately identify the fault types, making the control method lack of pertinence, which largely affects the effect of attitude control. This paper proposes an active fault tolerant control strategy, which mainly includes fault diagnosis and fault tolerant control. In the fault diagnosis part, a small deviation attitude dynamics model of the launch vehicle is established, Kalman filters with different structures are designed to detect and isolate faults through residual changes, and the fault quantity of the actuator is further estimated. In the fault tolerant control part, the following control scheme is adopted according to the above diagnostic information: when the sensor fault is detected, the sensor measurement data is reconstructed; when the actuator fault is identified, the control allocation matrix is reconstructed. Simulation results show that the proposed method can effectively diagnose sensor fault and actuator faults, and significantly improve attitude tracking accuracy and control adjustment time.

Finite-time fault-tolerant control of a spacecraft using composite learning in the presence of moment of inertia uncertainty and external disturbances

In this paper, a neuro-adaptive finite-time fault-tolerant control for a class of nonlinear systems is proposed based on the backstepping method, considering model uncertainties and external disturbances. To compensate for model uncertainties, a neural network is employed, while external disturbances and the estimation error of the neural network are handled using a disturbance observer. Additionally, actuator faults are estimated and compensated for distinctly using two adaptive elements in the proposed control system. Moreover, to enhance the learning of the neural network, disturbance observer, and other adaptive elements, particularly in the lack of persistently exciting signals, a composite learning approach is utilized. To this end, a state-observer is introduced, and its estimation error along with the tracking error is used in the updating rules of all the adaptive elements in the design. Additionally, to prevent the explosion of terms in the backstepping method, a command filter with practical finite-time stable auxiliary variables is incorporated into the proposed controller. Finite-time convergence of the tracking error to zero is rigorously proved using the Lyapunov method. To demonstrate the effectiveness of the proposed control method, the problem of attitude control of a rigid spacecraft with moment of inertia uncertainty, external disturbances, and multiple actuator faults is considered since precise attitude control of a spacecraft is of great importance in different maneuvers. The results show that using the introduced control system, the spacecraft is able to track the desired trajectory under different types of uncertain dynamics.

Multi-objective integrated attitude control of large solar power satellite: A distributed incremental predictive approach

This paper addresses the multi-objective integrated attitude control problem of a large solar power satellite (SPS) in the presence of time-varying parameters, disturbances, and actuator saturation. The attitude coupling dynamic model, which could accurately describe the rotational motion of different SPS components, is firstly obtained. The gravity gradient, solar radiation pressure, microwave radiation reflection, and friction torques are investigated to evaluate their influence on attitude control accuracy. The coupling dynamic model is linearized and discretized, which provides a subsystem model for distributed controller design. A distributed incremental predictive controller is designed for each rotation channel to form a distributed system. The augmented system state is defined to solve the complex constraint problem, and the predicted value with feedback correction is introduced to deal with the disturbances. Besides, the stability of the system is analyzed by considering external disturbances and actuator failure. Comparative analysis with centralized methods under the same prediction horizon is provided, and the results demonstrate a tenfold solution performance enhancement while maintaining accuracy. Furthermore, the controller is integrated with feedback correction, which could improve control accuracy by at least one order of magnitude. The proposed controller reduces the adjusting time for attitude stabilization by 56.8 % in the presence of actuator failure. The simulation results demonstrate that the proposed controller has good robustness and fault tolerance, which provides a feasible solution for SPS multiple attitude control missions.

Optimal attitude control for landing on asteroid with a flexible lander

The recently developed flexible lander offers a potential option for future asteroid landing missions due to its advantages in suppression of rebound and overturning. The strong nonlinear dynamics and control constraints of the flexible lander hinder the online implementation of optimal attitude feedback control. To generate the optimal attitude control rapidly, a constrained inhomogeneous approximating sequence of Riccati equations (CI-ASRE) method is proposed. The saturation function is firstly constructed to incorporate control magnitude constraints into dynamics so that the constraints can be analytically handled. Subsequently, to avoid singularity, a partial factorization strategy is proposed to convert the constrained dynamics into two parts, a pseudolinear term and an inhomogeneous term. This factorization enables the nonlinear problem to be expressed as the limit of a sequence of inhomogeneous linear quadratic problems while avoiding local linearization. At last, the analytical CI-ASRE is newly derived to iteratively solve these problems to rapidly obtain optimal feedback control. The computational simplicity and effectiveness of the CI-ASRE method overcome difficulties of optimal attitude control problems of the flexible lander associated with control constraints, strong nonlinearity, and online feedback control generation. The effectiveness of the proposed method for the flexible lander is verified using a landing scenario on asteroid 433 Eros.

Estimation of shape memory alloy actuator dynamics to design reduced‐order position controller with input saturation

AbstractThis study focuses on the precise model estimation for a position control problem actuated by a shape memory alloy (SMA) wire. Because the hysteresis characteristic of SMA introduces complexities in system modelling and adds degrees of freedom, a model with reduced order is implemented for controller design. This model is online updated by calculating a complementary term from the measured data to compensate for the SMA actuator dynamics and other parametric uncertainties. The position controller, derived from the formulated reduced‐order model, adapts itself to real conditions and is cost‐effective due to the use of only displacement sensor. The saturation of the control input is modelled within the structure of a constrained optimization problem solved by Karush–Kuhn–Tucker theorem. The boundedness of mean and covariance of tracking error and its derivative is demonstrated by stochastic analysis. The experimental results conducted on a platform incorporating a SMA wire show the efficiency of the proposed system in precisely controlling the position by admissible voltage range. The comparative results with a sliding mode controller indicate higher accuracy for the proposed controller to reduce the effect of uncertainties.

The Angular Momentum Unloading of the Asymmetric GEO Satellite by Using Electric Propulsion with a Mechanical Arm

A high-precision attitude control satellite uses an angular momentum exchange device such as a flywheel or a control moment gyro as the actuator for attitude stability control. Once the accumulation of angular momentum exceeds the upper limit of the angular momentum exchange device, the satellite will lose its attitude control ability. Therefore, it is necessary to unload the angular momentum exchange device to ensure the attitude control ability of the satellite platform. The angular momentum accumulation of GEO(Geosynchronous Orbit, GEO) satellites with asymmetric structure can reach 40 Nms per day, and the accumulation speed is more than 20 times that of GEO satellites with symmetrical structure. Therefore, it is necessary to carry out angular momentum unloading for GEO satellites with asymmetric structure every day. The previous method of angular momentum unloading using electric propulsion has weak unloading capacity, which is not suitable for angular momentum unloading of asymmetric satellites. This paper presents a method of angular momentum unloading using a four-joint mechanical arm plus an electric thruster. Large angular momentum unloading with near-zero burn-up can be achieved through the thrust generated by station keeping. In addition, the problem of attitude and orbit coupling control can be solved by controlling the thrust direction of the electric thruster with a mechanical arm.

Reinforcement Learning for Dual-Control Aircraft Six-Degree-of-Freedom Attitude Control with System Uncertainty

This article proposes a near-optimal control strategy based on reinforcement learning, which is applied to the six-degree-of-freedom (6-DoF) attitude control of dual-control aircraft. In order to solve the problem that the existing reinforcement learning is difficult to apply to the high-dimensional multiple-input multiple-output (MIMO) systems, the Long Short-Term Memory (LSTM) neural network is introduced to replace the polynomial network in the adaptive dynamic programming (ADP) technique. Meanwhile, based on the Lyapunov method, a novel online adaptive updating law of LSTM neural network weights is given, and the stability of the system is verified. In the simulation process, the algorithm proposed in this article is applied to the six-degree-of-freedom attitude control problem of dual-control aircraft with system uncertainty. The simulation results show that the algorithm can achieve near-optimal control.

Anti-unwinding adaptive robust backstepping attitude maneuver control for rigid spacecraft

In this paper, an anti-unwinding adaptive robust backstepping control law is proposed to solve the attitude control problem of rigid spacecraft with external disturbances and inertia uncertainties. A new variable based on hyperbolic sine functions is designed to prevent the unwinding phenomenon, and then a novel robust backstepping controller is developed. Initially, a nonlinear tracking law is designed to obtain the desired angular velocity and to ensure that the attitude maneuvering system could have two equilibrium points. Subsequently, an adaptive robust control law is devised, which incorporates the adaptive estimation method to update the inertial parameters in real-time. Moreover, the bounded external disturbances are taken into account in the design of the control law, and thus the robustness of the attitude control system is improved. Furthermore, the global asymptotic stability of the attitude control system is verified by the Lyapunov-Krasovskii theorem. Finally, numerical simulations are carried out to demonstrate the effectiveness and robustness of the proposed control law, as well as the anti-unwinding characteristics are perfectly validated during the attitude maneuver of rigid spacecraft.

Design and real-time implementation of a robust backstepping non-singular integral terminal sliding mode attitude control for a quadrotor aircraft

This paper concerns the problem of robust attitude control of a quadrotor aircraft subjected to modeling inaccuracies and wind disturbances. First, the model dynamics and state space representation of the quadrotor system are designed by considering the impact of disturbances and uncertainties. Then, a novel robust backstepping non-singular integral terminal sliding mode control (BNITSMC) is synthesized for the quadrotor attitude with the aim of enhancing the tracking accuracy. To strengthen the system’s robustness and guarantee the reachability of the sliding surface while reducing chattering, the supertwisting algorithm (ST) is used. Closed-loop stability and state convergence are guaranteed via the Lyapunov theory. Some experimental flight tests have been executed to validate the workability of the developed flight control. The obtained results prove that the recommended technique can provide improved performance in terms of stabilization and tracking precision.

Deep Deterministic Policy Gradient (DDPG) Agent-Based Sliding Mode Control for Quadrotor Attitudes

A novel reinforcement deep learning deterministic policy gradient agent-based sliding mode control (DDPG-SMC) approach is proposed to suppress the chattering phenomenon in attitude control for quadrotors, in the presence of external disturbances. First, the attitude dynamics model of the quadrotor under study is derived, and the attitude control problem is described using formulas. Second, a sliding mode controller, including its sliding mode surface and reaching law, is chosen for the nonlinear dynamic system. The stability of the designed SMC system is validated through the Lyapunov stability theorem. Third, a reinforcement learning (RL) agent based on deep deterministic policy gradient (DDPG) is trained to adaptively adjust the switching control gain. During the training process, the input signals for the agent are the actual and desired attitude angles, while the output action is the time-varying control gain. Finally, the trained agent mentioned above is utilized in the SMC as a parameter regulator to facilitate the adaptive adjustment of the switching control gain associated with the reaching law. The simulation results validate the robustness and effectiveness of the proposed DDPG-SMC method.