Search Results (277)

This paper investigates a carrier landing controller for unmanned aerial vehicles (UAVs), and a nonlinear model predictive control (NMPC) approach is proposed considering a precise motion control required under dynamic landing platform and environment disturbances. The NMPC controller adopts constraint aware particle filtering (CAPF) to predict deck positions for disturbance compensation and to solve the nonlinear optimization problem, based on a model establishment of carrier motion and wind field. CAPF leverages Monte Carlo sampling to optimally estimate control variables for improved optimization, while utilizing constraint barrier functions to keep particles within a feasible domain. The controller considers constraints such as fuel optimization, control saturation, and flight safety to achieve trajectory control. The advanced control method enhances the solution, estimating optimal control sequences of UAV and forecasting deck positions within a moving visual field, with effective trajectory tracing and higher control accuracy than traditional methods, while significantly reducing single-step computation time. The simulation is carried out using UAV “Silver Fox”, considering several scenarios of different wind scales compared with traditional CAPF–NMPC and the nlmpc method. The results show that the proposed NMPC approach can effectively reduce control chattering, with a landing error in rough marine environments of around 0.08 m, and demonstrate improvements in trajectory tracking capability, constraint performance and computational efficiency. Full article

The engagement quality of a helicopter dry clutch has a significant impact on the service life and overall flight performance of the helicopter. The engagement oil pressure is an important factor affecting the clutch engagement quality. Firstly, a nonlinear input–output dynamic model for the dry clutch is developed to investigate the optimization and control of dry clutch engagement pressure in this paper. Secondly, to efficiently obtain the optimal pressure curve, an optimal method combining the developed dynamic model with the state feedback gain of a linear quadratic optimization regulator (LQR) solver is proposed. Thirdly, considering that hydraulic actuators may struggle with tracking certain pressure curves, a hydraulic actuator for accurately tracking pressure curves based on fuzzy PID is proposed. The simulation results indicate that the developed hydraulic actuator exhibits an excellent tracking performance. Moreover, compared with linear and segmented pressure curves, the optimal pressure curve derived from the proposed method significantly reduces jerk, friction work, and engagement duration, resulting in improved helicopter dry clutch engagement quality. Full article

Morphing wing technology is crucial for enhancing the flight performance of aircraft. To address the monitoring challenges of full-scale variable-camber leading edges under flight conditions, this study introduces a ground-based strength testing technique aimed at precisely evaluating the deformation patterns and structural strength during actual operation. Firstly, the motion characteristics of the variable-camber leading edge were analyzed using numerical simulation based on kinematic theory. Secondly, a tracking loading test rig was designed and constructed to simulate the actuated deformation and aerodynamic loads of the leading edge. Next, mechanical boundary numerical simulation was then utilized to predict the motion trajectories of loading points on the upper and lower wing surfaces, and a multi-point coordinated control system was developed to achieve accurate experimental control. Finally, a multi-sensor iterative method was employed to ensure loading precision throughout the testing process. A case study was conducted using a leading edge test piece from a specific commercial aircraft. The results indicated that in the motion test of the variable-camber leading edge, the average error of the deflection angle was 4.59%; in the strength test, the average errors in the magnitude and direction of the applied load were 0.54% and 0.24%, respectively. These findings validate the effectiveness of the proposed technique in simulating the flight conditions of deforming wings and accurately obtaining the leading edge shape change curve, deformation accuracy curve, and strain curves of the upper and lower wing surfaces under deflection angles. Furthermore, this paper compares the deformation accuracy of different testing methods under test conditions, providing scientific evidence and technical support for the testing and evaluation of variable-camber leading edges. Full article

Uncrewed Aerial Vehicles (UAVs) are increasingly deployed across various domains due to their versatility in navigating three-dimensional spaces. The utilization of UAV swarms further enhances the efficiency of mission execution through collaborative operation and shared intelligence. This paper introduces a novel decentralized swarm control strategy for multi-UAV systems engaged in intercepting multiple dynamic targets. The proposed control framework leverages the advantages of both learning-based intelligent algorithms and rule-based control methods, facilitating complex task control in unknown environments while enabling adaptive and resilient coordination among UAV swarms. Moreover, dual flight modes are introduced to enhance mission robustness and fault tolerance, allowing UAVs to autonomously return to base in case of emergencies or upon task completion. Comprehensive simulation scenarios are designed to validate the effectiveness and scalability of the proposed control system under various conditions. Additionally, a feasibility analysis is conducted to guarantee real-world UAV implementation. The results demonstrate significant improvements in tracking performance, scheduling efficiency, and overall success rates compared to traditional methods. This research contributes to the advancement of autonomous UAV swarm coordination and specific applications in complex environments. Full article

As the power unit of an aircraft, the engine’s primary task is to provide the demanded thrust, making research on direct thrust control crucial. However, being a complicated multivariable system, effective multivariable direct thrust control methods are currently lacking. The main content of this paper is threefold. First, it presents a dual-loop multivariable μ-synthesis direct thrust control scheme for mixed-exhaust low-bypass turbofan engines, which is a typical rotationally symmetric machine. The scheme adjusts fuel flow for thrust control and nozzle area to control the turbine pressure ratio, ensuring thrust tracking while maintaining the engine’s key parameters within safe limits. Second, a fast, accurate thrust estimation algorithm based on aerodynamic thermodynamics and component characteristics is introduced. At last, considering the model uncertainties between off-design and design points, a weight function frequency shaping μ-synthesis control design method is proposed to address internal loop coupling and external disturbance suppression. Nonlinear simulations within the flight envelope show that μ-synthesis direct thrust control achieves robust servo tracking and disturbance rejection, with a maximum steady-state thrust error of no more than 0.1%, and the key parameters are not over their safety boundaries. Full article

Compared with traditional control methods, moving mass control (MMC) enhances the aerodynamic efficiency and stealth performance of fixed-wing unmanned aerial vehicles (FWUAVs), thereby facilitating their broader application in military and civilian fields. Nevertheless, this approach increases system complexity, nonlinearity, and coupling characteristics. To address these challenges, a novel attitude controller is proposed using adaptive global fast terminal sliding mode (GFTSM) control. Firstly, a dynamic model is established based on aerodynamics, flight dynamics, and moving mass dynamics. Secondly, to improve transient and steady-state responses, prescribed performance control (PPC) is adopted, which enhances the controller’s adaptability for mass-actuated aircraft. Thirdly, a fixed-time extended state observer (FTESO) is utilized to solve the inertial coupling issue caused by mass block movement. Additionally, the performance of the entire control system is rigorously proven through the Lyapunov function. Finally, numerical simulations of the proposed controller are compared with those of PID and linear ADRC in three different conditions: ideal conditions, fixed aerodynamic parameters, and nonlinear aerodynamic parameter changes. The results indicate that the controller effectively compensates for the system’s uncertainty and unknown disturbances, ensuring rapid and accurate tracking of the desired commands. Full article

This study introduces an advanced dual-mode compound attitude control framework for reusable launch vehicles (RLVs), underpinned by an enhanced particle swarm optimization (PSO) algorithm. This innovative strategy is tailored to meet the stringent demands for precision and robust anti-interference capabilities across the entire flight envelope of RLVs. The research commences with the formulation of a comprehensive attitude dynamics model and diverse heterogeneous actuator representations, meticulously crafted to reflect the distinct phases of RLV flight. Building upon this foundation, a synergistic control paradigm is engineered, integrating PID and fuzzy PID controllers and dynamically adjusting the inertia weights and learning factors of the PSO algorithm to achieve the balance between global and local optimization performance, complemented by a refined fitness evaluation function. The crux of the study is the application of an upgraded PSO algorithm to fine-tune the controllers’ weighting coefficients, culminating in an optimized dual-mode compound attitude control system. A series of comparative simulation analyses are thoroughly executed to appraise the system’s responsiveness, stability, precision, and resilience to interference. The simulation outcomes demonstrate an average reduction of 42.21% in step response overshoot, an 18.52% decrease in settling time, a 53.18% decline in steady-state error, a 56.80% drop in the maximum deviation value, a 55.82% improvement in recovery speed, and a 75.61% enhancement in tracking precision for the proposed controller. The findings clearly verify the superior performance of the proposed control system, affirming its contribution to the advancement of RLV attitude control. The proposed controller holds promising potential for real application in attitude control systems and is poised to augment the reliability and mission success rate of RLVs under intricate flight scenarios. Full article

Due to constraints in launch platforms and cost, the maneuverability of gliding-guided projectiles is limited, necessitating a rational design of their trajectory schemes. To reduce the sensitivity of trajectory schemes to uncertainties while ensuring compatibility between flight schemes and guidance control systems and fully exploiting the control capability of the projectile, a closed-loop robust trajectory planning method is proposed. Models of major uncertain factors and state deviation at the control start point are established. Based on the NIPCE method, the stochastic dynamic model is transformed into a high-dimensional deterministic model with PCE coefficients as state variables, and the uncertainty propagation law is obtained. A PID algorithm is employed to design a tracking guidance law based on position error feedback, and open-loop and closed-loop robust trajectory planning models are established accordingly. The optimal control problem is solved by transforming it into a nonlinear programming problem using the direct shooting method. Our simulation results indicate that the NIPCE method can significantly improve the computational efficiency of uncertainty propagation while ensuring accuracy; compared with parallel MCS, the computation time is reduced by 96.8%. Open-loop robust planning can effectively mitigate the sensitivity of gliding trajectories to uncertainties (the standard deviations of terminal altitude and lateral deviations are reduced by 23.6% and 35.3%, respectively, compared to deterministic planning) but cannot completely eliminate terminal dispersion. Closed-loop robust planning effectively improves control effort consumption on the basis of open-loop planning. Full article

This paper proposes a new approach to enhance the realism and interactivity of shooting simulation systems by integrating a three-degree–of–freedom (3-DoF) platform with sensory and interactive elements, as well as digital content. The system employs visual effects computers and servo controls, utilizing network packet messages for communication based on different scene definitions. When the control handle sends commands, the visual effects computer transmits control parameters to the image generator. Additionally, AI-controlled aircrafts act as enemy planes, autonomously determining flight paths, tracking targets, and engaging in combat, thereby enhancing realism in interactive mechanisms. An iterative learning control (ILC) is designed to provide the platform with good dynamic response, load capacity, and tracking ability when operated by a manual control handle. The core control uses a TMS320F28377D digital signal processor from Texas Instruments, integrated with visual effects computers for three-axis control, controller computation, finite state machines, and network communication operations. Experimental results demonstrate the feasibility and effectiveness of the developed three-axis shooting platform, achieving immersion and coordination with AI enemy aircrafts. Full article

Remotely operated vehicles (ROVs) provide practical solutions for a wide range of activities in a particularly challenging domain, despite their dependence on support ships and operators. Recent advancements in AI, machine learning, predictive analytics, control theories, and sensor technologies offer opportunities to make ROVs (semi) autonomous in their operations and to remotely test and monitor their dynamics. This study moves towards that goal by formulating a complete navigation, guidance, and control (NGC) system for a six DoF BlueROV2, offering a solution to the current challenges in the field of marine robotics, particularly in the areas of power supply, communication, stability, operational autonomy, localization, and trajectory planning. The vehicle can operate (semi) autonomously, relying on a sensor acoustic USBL localization system, tethered communication with the surface vessel for power, and a line of sight (LOS) guidance system. This strategy transforms the path control problem into a heading control problem, aligning the vehicle’s movement with a dynamically calculated reference point along the desired path. The control system uses PID controllers implemented in the navigator flight controller board. Additionally, an infrastructure has been developed that synchronizes and communicates between the real ROV and its digital twin within the Unity environment. The digital twin acts as a visual representation of the ROV’s movements and considers hydrodynamic behaviors. This approach combines the physical properties of the ROV with the advanced simulation and analysis capabilities of its digital counterpart. All findings were validated at the Point Rouge port located in Marseille and at the port of Ancona. The NGC implemented has proven positive vehicle stability and trajectory tracking in time despite external interferences. Additionally, the digital part has proven to be a reliable infrastructure for a future bidirectional communication system. Full article

This paper presents the design and implementation of the hardware and control strategies of an electrohydraulic air load simulation system for testing aerospace actuators. The system is part of an Iron Bird, which is an energy management research platform developed in collaboration between Saab AB and Linköping University. The purpose of the air load system is to provide realistic forces on the test object through the integration of a flight simulator for full mission evaluation. The challenge with electrohydraulic force control is tackled by increasing the hydraulic capacitance from increased load cylinder dead volumes, together with a feed-forward link based on accurate modelling of the test object and load system by adopting an optimisation routine to find model parameters. The system is implemented for both an electromechanical and servohydraulic actuator as test objects with different performance requirements. The control design is based on nonlinear and linear modelling of the system, and experimental test data are used to tune the models. Finally, test results of the air load system prove its force-tracking performance. Full article

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. Full article

Considering the effect of icing on aircraft control performance, this paper proposes an adaptive dynamic inverse ice tolerance control method based on piecewise constant. A control allocation algorithm is introduced to compensate for the change of control surface performance caused by icing. This method can achieve satisfactory disturbance estimation accuracy under a given sampling time, and thus ensure a closed-loop system error within an acceptable range. The proposed design method is applied to the design of a flight control law for a transport aircraft, aiming to solve the problem of ice-tolerant flight control, reduce the influence of icing conditions on controllability and safe flight of the transport aircraft, and thus improve the flight quality of the transport aircraft. The simulation results are verified under the influence of both standby ice type and failure ice type, and the interference effect on aircraft aerodynamic parameters is further added. The simulation results show that adaptive dynamic inverse control based on piecewise constant can overcome the influence caused by icing and aerodynamic parameter interference, achieve accurate tracking of command, and provide excellent fault tolerance and robustness, which ensures that the transport aircraft can achieve the desired control performance and safe flight capability. Full article

In situations where photovoltaic (PV) systems are exposed to varying light intensities, the conventional maximum power point tracking (MPPT) control algorithm may become trapped in a local optimal state. In order to address this issue, a two-step MPPT control strategy is suggested utilizing an improved tuna swarm optimization (ITSO) algorithm along with an adaptive perturbation and observation (AP&O) technique. For the sake of enhancing population diversity, the ITSO algorithm is initialized by the SPM chaos mapping population. In addition, it also uses the parameters of the spiral feeding strategy of nonlinear processing and the Levy flight strategy adjustment of the weight coefficient to enhance global search ability. In the two-stage MPPT algorithm, the ITSO is applied first to track the vicinity of the global maximum power point (MPP), and then it switches to the AP&O method. The AP&O method’s exceptional local search capability enables the global MPP to be tracked with remarkable speed and precision. To confirm the effectiveness of the suggested algorithm, it is evaluated against fuzzy logic control (FLC), standard tuna swarm optimization (TSO), grey wolf optimization (GWO), particle swarm optimization (PSO), and AP&O. Finally, the proposed MPPT strategy is verified by the MATLAB R2022b and RT-LAB experimental platform. The findings indicate that the suggested method exhibits improved precision and velocity in tracking, efficiently following the global MPP under different shading conditions. Full article

Incremental control strategies such as Incremental Nonlinear Dynamics Inversion (INDI) and Incremental Backstepping (IBKS) provide undeniable advantages for controlling Uncrewed Aerial Vehicles (UAVs) due to their reduced model dependency and accurate tracking capacities, which is of particular relevance for tail-sitters as these perform complex, hard to model manoeuvres when transitioning to and from aerodynamic flight. In this research article, a quaternion-based form of IBKS is originally deduced and applied to the stabilization of a tail-sitter in vertical flight, which is then implemented in a flight controller and validated in a Hardware-in-the-Loop simulation, which is also made for the INDI controller. Experimental validation with indoor flight tests of both INDI and IBKS controllers follows, evaluating their performance in stabilizing the tail-sitter prototype in vertical flight. Lastly, the tracking results obtained from the experimental trials are analysed, allowing an objective comparison to be drawn between these controllers, evaluating their respective advantages and limitations. From the successfully conducted flight tests, it was found that both incremental solutions are suited to control a tail-sitter in vertical flight, providing accurate tracking capabilities with smooth actuation, and only requiring the actuation model. Furthermore, it was found that the IBKS is significantly more computationally demanding than the INDI, although having a global proof of stability that is of interest in aircraft control. Full article