Attitude Control Research Articles

Adaptive configuration control of combined UAVs based on leader-wingman mode

Modular Unmanned Aerial Vehicles (UAVs) can adapt to rapidly changing payload requirements based on the shape and weight of the load by adding or subtracting units, reconfiguring, or changing the type of units. The existing research has addressed aerial docking and hover control post-docking but fails to achieve coordinated flight following combination, leading to delayed response and oscillations as the number of UAV units increases. Moreover, the configuration of modular UAVs is complex and variable, making it challenging to adjust the controller parameters of each unit online. Therefore, this paper presents: (A) Adaptive attitude allocation method for different combined UAV configurations: establishing a mapping relationship between constant controller parameters of the unit and the combination angular acceleration. The desired torque of the combination is allocated based on the size of the lever arm, enabling adaptive attitude control of the combination for varying configurations by controlling the attitude of the local unit; (B) A power allocation strategy based on a leader-wingman mode: employing a leader to control the entire combination, distributing the combination’s force and torque to wingman units according to the mapping relationship of the attitude allocation method. This transforms the complex control of the combination into unit control in the leader-wingman mode. Compared to current average allocation methods, the step response of attitude angle improves by about 60% on average, and spatial trajectory tracking increases by an average of 11.5%. As the number of units grows, the response of the combination becomes similar to that of a single, independently flying UAV, resolving the oscillation issue in combined flight. Additionally, this approach eliminates the need to change the controller parameters of all units, facilitating convenient reconfiguration and coordinated flight for modular UAVs post-combination.

Determinants of Millennial Interest in Investing on Sharia Securities Crowdfunding Platforms in Indonesia

This research aims to analyze the influence of attitude variables, subjective norms, and perceived behavioral control on interest upon investing in SCF sharia as well as the influence of the variables of Islamic financial literacy, religiosity, risk and return on attitudes towards investing among the millennial generation in SCF Syariah. The research employed a quantitative approach utilizing the Structural Equation Model Partial Least Square (SEM-PLS) with primary data gathered through purposive sampling. The technique was conducted by an online method on 152 individuals from the millennial generation. Not all TPB factors significantly influence the interest to invest in Sharia Securities Crowdfunding. Attitude and Behavior Control Perception have a positive impact on the interest to invest in Sharia SCF. Subjective Norm does not have an impact on the interest to invest in Sharia SCF. Sharia financial literacy does not significantly affect attitude. Religiosity significantly affects attitude. Risk and return significantly affect attitude.

Numerical modeling of wrinkling modulation in tensegrity-membrane structures

Tensegrity-membrane structures are potential to be lightweight gossamer spacecraft (e.g., solar sails, radar antennae, solar module), and the dynamics of deployment has been studied in the past studies where the membranes were usually modeled as a flat panel without wrinkles. However, the attitude control of membrane as well as the flatness are critical to the functionality of gossamer spacecraft. The paper proposes a numerical investigation on the modulation of wrinkling in tensegrity-membrane structures. The kinematic and deformation description is based on the co-rotational finite element method (FEM), while the wrinkling of membrane is modeled by Tension Field Theory (TFT). The numerical method is validated by an illustrative experiment, and then used for a surrogate model-based optimization design, in which clustered actuation is responsible for the attitude control of membrane, while classical actuation accounts for the suppression of wrinkles. An interesting tensegrity-membrane “Sunflower” is presented to show the result of optimization, where “Sunflower” can follow the sunlight angle accurately and freely control the orientation of “corolla” while maintaining its daylighting surface quality. This study provides an effective means for the numerical simulation and optimization design of tensegrity-membrane structures, especially when the attitude and wrinkling of membranes must be considered.

Rocket Thrust Vectoring Attitude Control based on Convolutional Neural Networks

Rocket Thrust Vectoring Attitude Control based on Convolutional Neural Networks

Actor-Critic Neural-Network-Based Fractional-Order Sliding Mode Control for Attitude Tracking of Spacecraft with Uncertainties and Actuator Faults

This paper investigates the attitude control of rigid spacecraft in the presence of uncertainties, disturbances, and actuator faults. In order to effectively address these challenges and improve the performance of the system, a novel actor-critic neural-network-based fractional-order sliding mode control (ACNNFOSMC) has been developed for spacecraft. The integration of actor-critic neural network, fractional-order theory, and sliding mode control enables dual functionality: the actor-critic neural network serves to approximate the aggregate of uncertain parameters, disturbances, and actuator faults, thereby facilitating their compensation, while the fractional-order sliding mode control mechanism significantly improves the system’s tracking precision and overall robustness against uncertainties. Theoretical analyses are presented to analyze the stability of the proposed control framework. Thorough examination via simulation experiments affirms the effectiveness and control precision of attitude of our proposed control strategy, even in complex operational scenarios.

Health status assessment of unmanned aerial vehicle (UAV) attitude control system based on an improved multivariate state estimation method

Health status assessment of unmanned aerial vehicle (UAV) attitude control system based on an improved multivariate state estimation method

Connectivity preservation control for multiple unmanned aerial vehicles in the presence of bounded actuation

This paper proposes a novel multi-unmanned aerial vehicle (UAV) connectivity preservation controller, suitable for scenarios with bounded actuation and limited communication range. According to the hierarchical control strategy, controllers are designed separately for the position and attitude subsystems. A distributed position controller is developed, integrating an indirect coupling control mechanism. The innovative mechanism associates each UAV with a virtual proxy, facilitating connections among adjacent UAVs through these proxies. This structuring assists in managing the actuator saturation constraints effectively. The artificial potential function is utilized to preserve network connectivity and fulfill coordination among all virtual proxies. Additionally, an attitude controller designed for finite-time convergence guarantees that the attitude subsystem adheres precisely to the attitude specified by the distributed position controller. Simulation results validate the efficacy of this distributed formation controller with connectivity preservation under bounded actuation conditions. The simulation results confirm the effectiveness of the distributed connectivity preservation controller with bounded actuation.

Motion Equations and Attitude Control in the Vertical Flight of a VTOL Bi-Rotor UAV: Part 2

This paper gathers the dynamical modeling of an unmanned aircraft and the design and simulation of the control system, allowing it to perform a Vertical Take-Off (VTOL) maneuver, a fixed-wing (FW) flight and a transition between the two configurations using two tilting rotors (Bi-Tilt). These Unmanned Aerial Vehicles (UAVs) operating in this configuration are categorized as Hybrid UAVs, for their capability of having a dual flight envelope: flying like a multi-rotor and navigating like a traditional fixed-wing aircraft, allowing the drone to perform complex missions where these two flight configurations are essential. This work exhibits the Bi-Rotor non-linear dynamics, valid for both flight configurations, the design of the control algorithm for stability and navigation, and a simulation of a complete flight mission.

Explicit design optimization of air rudders for maximizing stiffness and fundamental frequency

In aerospace engineering, there is a growing demand for lightweight design through topology optimization. This paper presents a novel design optimization method for stiffened air rudders, commonly used for aircraft attitude control, based on the Moving Morphable Component (MMC) method. The stiffeners within the irregular enclosed design domain are modeled as MMCs and discretized by shell elements, accurately capturing their geometry and evolution during optimization process using explicit parameters. In order to maximize the stiffness and fundamental frequency of the rudder structures, numerical analysis algorithms were developed with shape sensitivity analysis conducted. To comply with the manufacturing requirement, a minimum thickness is prescribed for the stiffeners, and the thickness and density penalty schemes are proposed to meet the minimum thickness constraint and prevent the occurrence of spurious modes respectively. The method’s effectiveness was demonstrated through optimization examples of a typical trapezoidal air rudder, illustrating the significance of stiffener’s distribution on design objectives. The explicit modeling characteristics allow for directly importing the optimization results into CAD systems, significantly enhancing the engineering applicability.

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.

Prescribed Performance Spacecraft Attitude Control with Multiple Convergence Rates

This paper proposes a prescribed performance control policy for spacecraft attitude tracking control. The designed controller employs a kind of performance envelope function that can configure the convergence rate arbitrarily. Moreover, the controller design is based on the barrier Lyapunov function and indirect adaptive methods, which can suppress the fluctuation of external disturbances to obtain lower steady-state errors. Compared to prior studies on spacecraft attitude tracking, the proposed policy can arbitrarily configure the system convergence performance to achieve performance trade-offs in different scenarios. Moreover, the barrier Lyapunov function design and adaptive methods can achieve low steady-state errors with low computational resource consumption. Simulations that verify its effectiveness and superiority are provided herein.

The Effects of Pointing Error Sources on Energy Delivery from Orbiting Solar Reflectors

Many proposals are being made for cleaner, more sustainable forms of energy production. Terrestrial solar photovoltaic farms (SPFs) could potentially deliver large quantities of energy to the grid, although these are limited to daytime use. The output from these SPFs could be enhanced, particularly around dawn and dusk, by the use of orbiting solar reflectors (OSRs) in near-polar orbit. These would reflect an image of the solar disk, or solar image (SI), onto the SPFs to augment their energy output. Pointing requirements are therefore to ensure that reflected sunlight is delivered to the terrestrial SPF, avoiding the losses incurred by an offset of the SI and the SPF itself. The SI would typically be of order 10 km for a reflector in a 1000 km orbit. Given the potentially large size of the reflectors, this presents a challenge for the attitude determination and control system (ADCS) to ensure that the maximum quantity of energy can be delivered to a SPF, typically requiring large control moment gyro actuators. In addition, there exist numerous sources of error in the ADCS which can cause further degradation in the quantity of energy delivered to the SPF. These errors can manifest in the resolution of the various sensors, flexible structural modes, manufacturing inaccuracies, and misalignments due to vibration during launch. This paper will investigate the effects of pointing error sources (PES) on the reflector ADCS and so on the quantity of energy delivered to the SPF. With the application of a PD controller with feedforward compensation, and the set of noise characteristics defined in this paper, numerical simulations will show the typical losses in energy delivered to SPFs of 0.015% when the model accounts for PES in onboard sensors, actuator uncertainty and flexible structural modes.

Adaptive sliding mode attitude control of two-wheeled robots for planetary auxiliary: From theory to applications

The value of two-wheeled robots in planetary auxiliary is significant, but their attitude control presents challenges due to their inherent characteristics and external environment conditions. To address this issue, this paper presents an adaptive sliding mode (SMC) control scheme of two-wheeled robots for planetary auxiliary. Firstly, a motion model specifically for two-wheeled robots that focuses on attitude control is established. Secondly, an adaptive reaching law was proposed based on the study (Wang et al. 2014). It improves upon the previous adaptive gain, and it can ensure stable operation when the improved adaptive gain converges to a small neighborhood of the origin. This effectively avoids the chattering phenomenon and guarantees that the sliding mode surface converges within a finite time. On this basis, an adaptive SMC attitude controller is developed, and its stability is proven using Lyapunov stability theory. Finally, comparative simulation experiments are conducted to verify the effectiveness, adaptability, superiority and robustness of the proposed control scheme. (A virtual simulation video generated by Simulink 3D Animation can be viewed onhttps://pan.baidu.com/s/1JxRR7vMyq9Cm-23YHFPnYA?pwd=5lf1)

Control stability analysis of dynamic model with time delay for quadrotor UAV

For the first-order unstable object with time delay, the PD control parameter tuning method based on the traditional definition lacks consideration of the lower boundary of amplitude margin, resulting in a certain deviation between the result and the reality. In this paper, through analyzing the control loop of quadrotor UAV (QUAV), the integral link is moved from the controlled object to the controller, and the QUAV becomes a first-order unstable object, realizing the conversion of PD to PI in the hovering state. The system stability margin remains unchanged, and the position and attitude control objectives can be realized synchronously. By means of parameter setting method, the upper boundary of stability margin is obtained. Pade approximation is carried out for the time delay link, and then the lower margin of the amplitude margin is deduced according to Routh stability criterion, so as to obtain a more accurate reachable stability margin region. To avoid the high gain feedback of attitude angular velocity of QUAV, a numerical analytical setting formula for PD attitude control is derived to meet the requirements of gain and phase margin. The graph shows that the reachable region obtained by the strict definition of stability margin analysis decreases significantly. The proposed method can not only give the reachable region intuitively, but also give the tuning formula of the control parameters concisely, which has important engineering application value.

Event-triggered fixed-time fault-tolerant attitude control for the flying-wing UAV using a Nussbaum-type function

This paper introduces an innovative adaptive event-triggered fault-tolerant attitude control framework designed for a flying-wing unmanned aerial vehicle (UAV) operating under constraints such as limited embedded resources, unknown actuator failures, system uncertainties, and external disturbances. The proposed scheme incorporates several noteworthy features: (i) Implementation of a relative threshold event-triggered mechanism to efficiently alleviate communication pressures and computational burdens inherent in the attitude control system. (ii) Utilization of a radial basis function neural network to approximate lumped disturbances, reducing dependence on prior knowledge. (iii) Adaptive compensation for sampling errors and actuator faults by employing the Nussbaum gain. (iv) Integration of a smooth function to address singularity issues and prevent Zeno behavior. Furthermore, Lyapunov analysis validates that all signals within the closed-loop system remain bounded and converge within a predetermined time frame. Comparative numerical simulations underscore the effectiveness and superiority of the proposed control approach.

Correction: Li et al. Attitude Control of UAVs with Search Optimization and Disturbance Rejection Strategies. Mathematics 2023, 11, 3794

In the original publication [...]

Incremental fully actuated system approach-based prescribed-time fault-tolerant formation control of helicopters under multiple faults

Helicopter formation is characterized by intricate dynamics, complex mechanics, and challenging scenarios, raising the necessity for agile, robust, and convenient controller design. This paper explores the prescribed-time fault-tolerant formation control of multiple helicopters through the incremental fully actuated system approach, which addresses multiple faults in sensors and swash plate struts. First, the helicopter model encompassing aerodynamic, flapping dynamic, swash plate dynamic, actuator faults, and sensor faults is established and further partitioned into attitude and position subsystems. Then, in the attitude subsystem, a prescribed-time attitude controller based on the incremental fully actuated system approach is proposed to track the desired attitude with robustness against actuator faults, aerodynamic drags, inter-axis coupling, and non-linearity. Next, in the position subsystem, the faults of velocity and position sensors are estimated and compensated through the prescribed-time fault-estimation observer, and a prescribed-time formation controller through the incremental fully actuated system approach is designed to achieve distributed leader-follower formation control. A Task-Fault dual-driven scheduling mechanism of the parameters of the prescribed-time technique is developed to promptly activate the prescribed-time function, and the control scheme is proven to be prescribed-time convergent via Lyapunov stability theory. Finally, numerical simulations are conducted to illustrate the efficiency of the algorithm.

Attitude-position obstacle avoidance of trajectory tracking control for a quadrotor UAV using barrier functions

In this article, an attitude-position obstacle avoidance trajectory tracking control scheme based on barrier functions is proposed for a quadrotor unmanned aerial vehicle (UAV). First, the barrier functions are designed based on the relationship between the position and attitude of the quadrotor UAV and obstacles. Then, by decoupling the quadrotor UAV system into a position control subsystem and an attitude control subsystem and incorporating integral barrier Lyapunov functions (IBLFs) into the backstepping process, a novel obstacle avoidance tracking control strategy for the position subsystem and the attitude subsystem is constructed. Compared with the existing obstacle avoidance results, the designed obstacle avoidance strategy can simultaneously achieve obstacle avoidance on the position and attitude of the quadrotor UAV. Finally, the efficiency of the proposed method is verified by simulation results.

Aerodynamic Feedforward-Feedback Architecture for Tailsitter Control in Hybrid Flight Regimes

This paper presents a guidance-control design methodology for the autonomous maneuvering of tailsitter transitioning unmanned aerial systems (t-UASs) in hybrid flight regimes (i.e., the dynamics between VTOL and fixed-wing regimes). The tailsitter guidance-control architecture consists of a trajectory planner, an outer-loop position controller, an inner-loop attitude controller, and a control allocator. The trajectory planner uses a simplified tailsitter model, with aerodynamic and wake effect considerations, to generate a set of transition trajectories with associated aerodynamic force estimates based on an optimization metric specified by a human operator (minimum time transition). The outer-loop controller then uses the aerodynamic force estimate computed by the trajectory planner as a feedforward signal alongside feedback linearization of the outer-loop dynamics for 6DOF position control. The inner-loop attitude controller is a standard nonlinear dynamic inversion control law that generates the desired pitch, roll, and yaw moments, which are then converted to the appropriate rotor speeds by the control allocator. Analytical conditions for robust stability are derived for the outer-loop position controller to guarantee performance in the presence of uncertainty in the feedforward aerodynamic force compensation. Finally, both tracking performance and stability of the control architecture are evaluated on a high-fidelity flight dynamics simulation of a quadrotor biplane tailsitter for flight missions that demand high maneuverability in transition between flight modes.

Coaxial Helicopter Attitude Control System Design by Advanced Model Predictive Control under Disturbance

This paper proposes an advanced model predictive control (MPC) scheme for the attitude tracking of coaxial drones under wind disturbances. Unlike most existing MPC setups, this scheme embeds steady-input, steady-output, and steady-state conditions into the optimization problem as decision variables. Consequently, the coaxial drone’s attitude can slide along the state manifold composed of a series of steady states. This allows it to move toward the optimal reachable equilibrium. To address disturbances that are difficult to accurately measure, an extended state observer is employed to estimate the disturbances in the prediction model. This design ensures that the algorithm maintains recursive stability even in the presence of disturbances. Finally, numerical simulations and flight tests are provided to confirm the effectiveness of the proposed method through comparison with other control algorithms.