Search Results (203)

To address the challenge of controlling the hydraulic excavator’s precise motion, a nonlinear backstepping control algorithm is designed, combining a funnel function and a neural network (NN), which effectively compensates for the influence of unmodeled dynamics and external disturbances on the hydraulic excavator’s control system. Specifically, an improved funnel function is introduced to characterize both the steady-state and transient performance of the system simultaneously, thereby limiting the joint tracking error within predetermined performance constraints and enhancing the trajectory tracking accuracy. Two RBFNN estimators are employed to address the uncertain coupled mechanical dynamics and nonlinear hydraulic dynamics, respectively. The weight updating law is generated based on the gradient descent method, which can prevent high-gain feedback and enhance the system’s robustness. Finally, the stability of the closed-loop system is rigorously proven using the Lyapunov function analysis method. To verify the effectiveness of the proposed algorithm, simulations and experimental research are conducted under various external disturbances, using the excavator’s flat working condition as a case study. The results demonstrate that the controller maintains good control performance and robustness even in the presence of uncertainties and external disturbances within the system. Full article

This paper investigates bearing-based formation control of multiple unmanned aerial vehicles (UAVs) flying in low-altitude wind fields. In such environments, time-varying wind disturbances can distort the formation geometry, enlarge bearing errors, and even induce potential collisions among neighboring UAVs, yet they also contain components that can be beneficial for the formation motion. Conventional disturbance compensation methods treat wind as a purely harmful factor and aim to reject it completely, which may sacrifice responsiveness and energy efficiency. To address this issue, we propose a pure bearing-based formation control framework with Conditional Disturbance Utilization (CDU). First, a real-time disturbance observer is designed to estimate the wind-induced disturbances in both translational and rotational channels. Then, based on the estimated disturbances and the bearing-dependent potential function, CDU indicators are constructed to judge whether the current disturbance component is beneficial or detrimental with respect to the formation control objective. These indicators are embedded into the bearing-based formation controller so that favorable wind components are exploited to accelerate formation convergence, whereas adverse components are compensated. Using an angle-rigid formation topology and a Lyapunov-based analysis, we prove that the proposed CDU-based controller guarantees global asymptotic stability of the desired formation. Simulation results on triangular and hexagonal formations under complex wind disturbances show that the proposed method achieves faster convergence and improved responsiveness compared with traditional disturbance observer-based control, while preserving formation stability and safety. Full article

In harsh marine environments, during the operation of the Ship–Cable–Body coupled system, the towed cable may become slack or taut, and tension oscillations may occur, leading to cable breakage or launch and recovery system (LARS) damage, underscoring the need for effective compensation control. Traditional offline and static simulation methods fail to capture the system’s dynamics, leading to inaccurate validation of control strategies. To address this, we propose a real-time dynamic modeling framework using the OrcFxAPI, enabling millisecond-level bidirectional interaction between the towed body’s motion and LARS commands. By integrating a Python 3.10-based PID controller with OrcFxAPI, the framework achieves real-time active heave compensation (AHC) in deep-sea towing, dynamically adjusting cable length and payout speed based on feedback to suppress vibrations. Unlike prior studies focused on launch and recovery, this work systematically evaluates AHC performance during typical operations (hovering, linear and turning motion), and compares system responses with and without compensation. Results show the AHC framework significantly improves towed body stability, reduces tension fluctuations, and keeps tension within safe working limits (SWLs), while identifying critical cable payout speed thresholds for practical operation. The approach validates the use of OrcFxAPI for high-fidelity real-time coupling analysis and provides a reliable tool for optimizing control and design of deep-sea towing systems. Full article

The acquisition of images of road surfaces not only establishes a theoretical foundation for road maintenance by relevant departments but also is instrumental in ensuring the safe operation of highway transportation systems. To address the limitations of traditional road surface image acquisition systems, such as low collection speed, poor image clarity, insufficient information richness, and prohibitive costs, this study has developed a high-speed binocular-vision-based system. Through theoretical analysis, we developed a complete system that integrates hybrid anti-shake technology. Specifically, a hardware device was designed for stable installation at the rear of high-speed vehicles, and a software algorithm was implemented to develop an electronic anti-shake module that compensates for horizontal, vertical, and rotational motion vectors with sub-pixel-level accuracy. Furthermore, a road surface image fusion algorithm that combines the stationary wavelet transform (SWT) and nonsubsampled contourlet transform (NSCT) was proposed to preserve multi-scale edge and textural details by leveraging their complementary multidirectional characteristics. Experimental results demonstrate that the fusion algorithm based on SWT and NSCT outperforms those using either SWT or NSCT alone across quality evaluation metrics such as QAB/F, SF, MI, and RMSE: at 80 km/h, the SF value reaches 4.5, representing an improvement of 0.088 over the SWT algorithm and 4.412 over the NSCT algorithm, indicating that the fused images are clearer. The increases in QAB/F and MI values confirm that the fused road surface images retain rich edge and detailed information, achieving excellent fusion results. Consequently, the system can economically and efficiently capture stable, clear, and information-rich road surface images in real-time under high-speed conditions with low energy consumption and outstanding fidelity. Full article

The dynamic performance of parallel robots directly determines the machining accuracy in large optical mirror processing (LOMP). However, limitations in traditional dynamic modeling methods hinder their application in real-time control, constraining further improvements in robotic precision. This paper aims to establish a high-precision and practical dynamic model that considers joint friction for parallel robots used in LOMP, and to design an efficient real-time friction compensation control strategy to effectively enhance trajectory tracking and repetitive positioning accuracy. The novelty of this work lies in proposing a dynamic modeling approach that integrates the static mechanics-based “Disassembly Method” with a “Coulomb + Viscous” friction model. First, static analysis of the mechanism is conducted using the “Disassembly Method” to accurately compute the joint constraint reactions in any pose, providing critical input for friction calculation. Subsequently, a complete dynamic model incorporating friction in joints such as Hooke joints, composite spherical hinges, and ball screws is developed based on the Newton–Euler formulation. This method overcomes the shortcomings of traditional approaches in solving joint reactions and managing model complexity. Numerical simulations demonstrate that, compared to conventional friction-neglected models, the proposed model reveals a maximum increase of approximately 350 N in driving chain joint reaction forces and significant peaks in driving forces at motion reversal instants (e.g., 0.28 s, 0.45 s), quantitatively proving that neglecting friction severely underestimates the actual system loads. Experimental validation shows that the feedforward PD friction compensator designed based on this model reduces the rotational tracking errors of the moving platform around the X- and Y-axis from 0.295° and 0.286° to 0.134° and 0.128°, respectively, achieving an error reduction of about 55% and effectively improving motion control accuracy. This study provides a reliable dynamic modeling foundation and an effective real-time control compensation solution to address force output errors and trajectory deviations caused by joint friction in high-precision LOMP. Full article

Enhancing the positioning stability and accuracy of autonomous following systems poses a significant challenge, particularly in dynamic indoor environments susceptible to occlusion and interference. This paper proposes an innovative approach that integrates Ultra-Wideband (UWB) technology with computer vision-based gait analysis to overcome these limitations. First, a low-power, high-update-rate UWB positioning network is established based on an optimized Double-Sided Two-Way Ranging (DS-TWR) protocol. To compensate for UWB’s deficiencies under Non-Line-of-Sight (NLOS) conditions, a visual gait recognition process utilizing the GaitPart framework is introduced for target identification and relative motion estimation. Subsequently, an Extended Kalman Filter (EKF) is developed to seamlessly fuse absolute UWB measurements with gait-based relative kinematic information, thereby generating precise and robust estimates of the leader’s trajectory. This estimated path is tracked by a differentially driven mobile platform via a Model Predictive Controller (MPC). Experimental results demonstrate that the tracking deviation for most trajectory points remains within 50 mm, with a maximum observed deviation of 115 mm during turns, confirming its strong robustness and practical utility in real-world intelligent vehicle applications. Full article

The severe vertical motion of high-speed multihull vessels significantly impairs their seakeeping performance, making the design of effective anti-motion controllers crucial. However, existing controllers, predominantly designed based on deterministic dynamic models, suffer from limitations such as insufficient robustness, reliance on empirical knowledge, structural complexity, and suboptimal performance, which hinder their practical applicability. To address this, this paper proposes a robust decoupled vertical motion controller based on the step response inversion method and incorporating an Extended State Observer (ESO) uncertainty compensation term. The control algorithm is designed leveraging the equivalent noise bandwidth theory to account for the stochastic characteristics of pitch/heave motion, with ESO compensation introduced to enhance robustness. The stability of the closed loop system is rigorously proven through theoretical analysis. Simulation results demonstrate that the proposed algorithm significantly suppresses the amplitudes of both pitch and heave motions. Full article

Vibrations of the print head and structural components during 3D printing with FFF technology can significantly impact the quality of printed parts, resulting in defects such as ghosting, ringing, and geometric inaccuracies. These undesired effects are primarily caused by mechanical oscillations of the print head, build platform, and frame, induced by dynamic changes in movement speed and inertial forces within the printing mechanism. This study investigates the effectiveness of vibration compensation using an ADXL345 accelerometer to regulate the motion of the print head and build platform on the Ender 3 V2 Neo printer. The experiment consisted of three test series performed under two distinct conditions, without vibration compensation and with active compensation enabled. All tests were carried out using identical baseline printing parameters. The differences in output were evaluated through visual inspection and dimensional analysis of the printed samples. Efficient vibration monitoring and its active control, aimed at suppressing oscillatory phenomena, can enhance both geometric accuracy and surface uniformity. In FFF 3D printing, especially when utilizing increased layer heights such as 0.3 mm, surface roughness (Ra) values in the range of 18 to 25 µm are typically expected, even when optimal process parameters are applied. This study emphasizes the role of active vibration control strategies in additive manufacturing, particularly in enhancing surface quality and dimensional accuracy. The objective is not only to mitigate the adverse effects of dynamic mechanical vibrations but also to determine the extent to which surface roughness can be systematically reduced under defined conditions, such as layer height, print speed, and movement trajectory. The aim is to improve the final product quality without introducing significant compromises in process efficiency. Full article

Traditional ISAR imaging algorithms are based on the “stop-and-go” assumption and lack theoretical analysis, accurate simulation, and effective compensation regarding the high-speed motion of the target or the platform. In response to this issue, a theoretical analysis of the high-speed motion of the target or the platform in ISAR imaging is first conducted, indicating that when a chirp is transmitted, the echo from a scatterer can be approximated as a chirp with its central frequency and chirp rate changed, and this will lead to the shift and the blurring of the scatterer in range. A method is then proposed to estimate the central frequency and the chirp rate, which are used to adjust the central frequency and the chirp rate of the matched filter. The central frequency is estimated to maximize the normalized correlation of the amplitude spectrum and its nominal form, and the chirp rate is derived from the central frequency. Moreover, in order to show the rationality of our theoretical analysis and the effectiveness of our compensation method, a scheme is presented to simulate the received signal under the high-speed motion of the target or the platform. This scheme assumes that the target and the platform move continuously with time and reflects the effects of the high-speed motion on the received signal accurately. Full article

This paper introduces a new quadruped spider robot platform specializing in environmental reconnaissance and mapping. The robot measures 180 mm × 180 mm × 95 mm and weighs 385 g, including the battery, providing a compact yet capable platform for reconnaissance missions. The robot consists of an ESP32 microcontroller and eight servos that are disposed in a biomimetic layout to achieve the biological gait of an arachnid. One of the major design revolutions is in the power distribution network (PDN) of the robot, in which two DC-DC buck converters (LM2596M) are used to isolate the power domains of the computation and the mechanical subsystems, thereby enhancing reliability and the lifespan of the robot. The theoretical analysis demonstrates that this dual-domain architecture reduces computational-domain voltage fluctuations by 85.9% compared to single-converter designs, with a measured voltage stability improving from 0.87 V to 0.12 V under servo load spikes. Its proprietary Bluetooth protocol allows for both the sending and receiving of controls and environmental data with fewer than 120 ms of latency at up to 12 m of distance. The robot’s mapping system employs a novel motion-compensated probabilistic algorithm that integrates ultrasonic sensor data with IMU-based motion estimation using recursive Bayesian updates. The occupancy grid uses 5 cm × 5 cm cells with confidence tracking, where each cell’s probability is updated using recursive Bayesian inference with confidence weighting to guide data fusion. Experimental verification in different environments indicates that the mapping accuracy (92.7% to ground-truth measurements) and stable pattern of the sensor reading remain, even when measuring the complex gait transition. Long-range field tests conducted over 100 m traversals in challenging outdoor environments with slopes of up to 15° and obstacle densities of 0.3 objects/m² demonstrate sustained performance, with 89.2% mapping accuracy. The energy saving of the robot was an 86.4% operating-time improvement over the single-regulator designs. This work contributes to the championing of low-cost, high-performance robotic platforms for reconnaissance tasks, especially in search and rescue, the exploration of hazardous environments, and educational robotics. Full article

This paper presents the design, implementation, and experimental results of a six-degree-of-freedom Delta-type parallel manipulator, in which all actuators were realized using proprietary pneumatic muscles. The objective of the study was to evaluate the suitability of this type of actuator for applications in parallel robotics, with particular attention to their dynamic properties, nonlinearities, and potential limitations. In the first part of the article, the details of the manipulator’s construction and the kinematic model, covering both the forward and inverse kinematics, are presented. The control system was based on antagonistic pairs of pneumatic muscles forming servo drives responsible for the motion of individual arms. The experimental investigations were focused on analyzing trajectory-tracking accuracy and positioning repeatability, both in unloaded conditions and under additional payload applied to the end-effector. The results indicate that positioning errors for simple trajectories were generally below 1 mm, whereas for complex trajectories and under load, they increased, particularly during changes in motion direction, which can be attributed to friction and hysteresis phenomena in the muscles. Repeatability tests confirmed the ability of the manipulator to repeatedly reach the desired positions with small deviations. The analysis carried out confirms that pneumatic muscles can be effectively applied to drive parallel manipulators, offering advantageous features such as high power density and low mass. At the same time, the need for further research on nonlinearity compensation and durability enhancement was demonstrated. Full article

This paper presents an analysis of the convergence of a numerical procedure used to evaluate the dynamic accuracy of measurement transducers, with particular emphasis on their application in energy and electromechanical systems. The main objective of the study is to assess the effectiveness of a fixed-point algorithm designed to determine test signals that satisfy time and amplitude constraints while maximizing an integral quality criterion of the “energy-optimal” type. The analysis employs numerical modeling of two types of temperature transducers: an NTC-type resistance temperature transducer and a K-type thermocouple. These models are based on a polynomial approximation method, enabling the estimation of the upper bound of the dynamic error—a key parameter in applications involving rapid changes in physical conditions, typical of energy and electromechanical systems operating under variable loads, such as industrial drives, clutches, bearings, and cooling systems, as well as in automation systems, control loops, and diagnostic frameworks. From the perspective of theoretical mechanics, temperature transducers can be modeled as a dynamic system characterized by thermal inertia, whose behavior is governed by first-order differential equations analogous to the equations of motion of a mass in a mechanically damped system. The results are presented graphically, illustrating the algorithm’s convergence behavior and computational stability. The practical application of the proposed approach can contribute to improving the accuracy of temperature transducers, enhancing error compensation algorithms, and optimizing the design of measurement systems in the energy sector and electromechanical industry, as well as in mechanical and electrical systems, especially where fast and reliable measurements under variable thermal loads on machine components are crucial. Full article

This study addresses the limitations of buoyancy factor and compensation capacity in pressure hulls for full-ocean-depth underwater gliders operating in extreme deep-sea conditions. A novel lightweight multifunctional composite structure pressure hull (CSPH) is proposed, utilizing a carbon fiber cylindrical shell as the primary load-bearing structure and silicone oil as the buoyancy compensation medium. A mechanical model of the carbon fiber cylindrical shell under hydrostatic pressure was developed based on three-dimensional elastic mechanics theory. Furthermore, a comprehensive performance evaluation model for the CSPH was created, incorporating both the buoyancy factor (B_f) and buoyancy fluctuation coefficient (f_B). The NSGA-II optimization algorithm was employed to simultaneously minimize B_f and f_B by co-optimizing the carbon fiber ply parameters and the silicone oil volume (V_C). This optimization resulted in a Pareto optimal solution balancing buoyancy and compensation performance. The accuracy of the mechanical model and optimization results was validated through finite element analysis and pressure testing. The results show that, compared to traditional metallic pressure hull designs, the CSPH reduces the buoyancy factor by 48% and enhances buoyancy compensation performance by 2.5 times. The developed CSPH has been successfully deployed on the “Sea-Wing 11000” full-ocean-depth underwater glider, significantly improving its endurance and motion stability for long-term deep-sea observation missions. Full article

A mill relining manipulator is key maintenance equipment for liners exchanged and operated by workers inside a grinding mill. To improve the operation efficiency and safety, real-time path planning and end deformation compensation should be performed prior to actual execution. This paper proposes a five-dimensional digital twin framework to realize virtual–real interaction between a physical manipulator and virtual model. First, a real-time digital twin scene is established based on OpenGL. The involved technologies include scene rendering, a camera system, the light design, model importation, joint control, and data transmission. Next, different solving methods are introduced into the service space for relining tasks, including a kinematics model, collision detection, path planning, and end deformation compensation. Finally, a user application is developed to realize real-time condition monitoring and simulation analysis visualization. Through comparison experiments, the superiority of the proposed path planning algorithm is demonstrated. In the case of a long-distance relining task, the planning time and path length of the proposed algorithm are 1.7 s and 15,299 mm, respectively. For motion smoothness, the joint change curve exhibits no abrupt variation. In addition, the experimental results between original and modified end trajectories further verified the effectiveness and feasibility of the proposed end effector compensation method. This study can also be extended to other heavy-duty manipulators to realize intelligent automation. Full article

Wilderness Search and Rescue (WSAR) missions are time-critical emergency response operations that require locating a lost person within a short timeframe. Large forested terrains must be explored in challenging environments and adverse conditions. Unmanned Aerial Vehicles (UAVs) equipped with thermal cameras enable the efficient exploration of vast areas. However, manual analysis of the huge amount of collected data is difficult, time-consuming, and prone to errors, increasing the risk of missing a person. This work proposes an object detection and tracking pipeline that automatically analyzes UAV thermal videos in real-time to identify lost people in forest environments. The tracking module combines information from multiple viewpoints to suppress false alarms and focus responders’ efforts. In this moving camera scenario, tracking performance is enhanced by introducing a motion compensation module based on known camera poses. Experimental results on the collected thermal video dataset demonstrate the effectiveness of the proposed tracking-based approach by achieving a Precision of 90.3% and a Recall of 73.4%. On a dataset of UAV thermal images, the introduced camera alignment technique increases the Recall by 6.1%, with negligible computational overhead, reaching 35.2 FPS. The proposed approach, optimized for real-time video processing, has direct application in real-world WSAR missions to improve operational efficiency. Full article