Search Results (2,320)

Long-term vibrations endanger driver health and affect ride performance. Semi-active seat suspension systems equipped with magnetorheological (MR) dampers can effectively reduce vibrations transmitted to drivers, exhibiting excellent potential for widespread applications owing to their outstanding performance characteristics. In this paper, we propose an adaptive backstepping control system with time-delay compensation (ABC-C) for an MR-damper-based semi-active seat suspension system to enhance ride comfort and stability in commercial vehicles. The control framework integrates a reference model, an adaptive backstepping controller, a time-delay compensator, and an MR damper inverse model. The reference model balances ride comfort and stability using high-pass and low-pass filters, while the adaptive controller ensures robustness against parameter uncertainties and disturbances. A time-delay compensator mitigates delays in the control loop, improving system stability and performance. Numerical simulations under harmonic, bump, and random excitations demonstrated the superior performance of the ABC-C controller. The experimental results show that under random road excitation conditions, the frequency-weighted root mean square (FW-RMS) of acceleration was reduced by 26.9%, the vibration dose value (VDV) decreased by 29.3%, and the root mean square of relative displacement (RMS_rd) was reduced by 58.46%. The results highlight the practical effectiveness of the ABC-C controller in improving ride comfort and safety for drivers of commercial vehicles, offering significant potential for real-world applications. Full article

Cooperative robotics relies on robust fault-tolerant control (FTC) to maintain resilience in dynamic environments, where actuators are pivotal to system reliability. This review synthesizes advancements in hybrid FTC, integrating mechanical redundancy with electronic adaptability and learning-based techniques like deep reinforcement learning and swarm-optimized control, drawing from interdisciplinary evidence across manufacturing, healthcare, agriculture, space exploration, and underwater robotics. It examines how these approaches enhance uptime, precision, and coordination in multi-robot systems, reporting significant improvements despite physical validation being limited to approximately one-quarter of strategies. Addressing gaps in prior work by overcoming limitations of traditional methods, it extends to Construction 5.0, supporting human–robot collaboration (HRC) through scalability and adaptability. Future efforts will prioritize broader testing, standardized benchmarks, safety considerations, and optimization under uncertainty to align theoretical gains with practical outcomes, enhancing resilient automation across domains. Full article

The current global context demands the development of new solutions that prioritize energy efficiency, time optimization, safety, and sustainability. Urban transportation is one of the sectors undergoing significant transformation. Pursuing new urban transportation solutions has become increasingly intense, involving research institutions and companies. Considering this context, this study focused on the optimization procedures for designing a new vehicle capable of vertical take-off for urban air mobility applications. This paper reports on the optimization process of a thruster deployment mechanism using statistical techniques. In particular, the authors tested the use of Design of Experiments (DOE) techniques for the optimal design of a structural component of a new vehicle for urban mobility purposes under development at the Applied Mechanics laboratory of the Department of Industrial Engineering of the University of Salerno. For this reason, it was decided that a parametric multibody model would be developed in the Simscape Multibody environment for structural optimization using designed experiment plans to “guide” the designer in the analysis phase and search for an optimal configuration using a minimum number of configurations. Finally, employing FEM analysis, the chosen configuration was validated. This study allowed us to test the use of DOE techniques to design new systems. It allowed us to evaluate different configurations, the static and dynamic behavior, the constraining reactions present in the joints, and the active forces and torques of the actuators, highlighting the correlation between factors that can guide the designer in identifying optimal solutions. Full article

To meet the mining requirements of the ’excavation–backfill–retention’ tunneling method for inter-panel coal pillars, this paper proposes an integrated ‘excavation–backfill–retention’ equipment system centered on a cutting robot. An interactive design method was employed to analyze the interaction between mining conditions and the cutting robot, constructing a ’requirements–functions–structure’ model. The robot integrates a horizontal drum cutting mechanism with a slider shoe walking mechanism, offering enhanced adaptability to various mining conditions. A parameter model was constructed to explore the relationship between the cutting arm length and the robot’s structural parameters under varying mining heights. Using a hierarchical solution method that combines local search and multi−objective genetic algorithms, the robot’s fundamental parameters were determined, enabling the development of a detailed 3D model. A kinematic model based on the modified D–H method was developed to analyze the cutting arm’s swing angle, cylinder extension, propulsion velocity, and cutting velocity in practical mining scenarios. The working range of the height adjustment and feed cylinders at different mining heights was determined through simulation. A dynamics model of the cutting drum was developed, and a coupled simulation using the discrete element method (DEM) was conducted to analyze the relationship between coal/rock hardness, drum load, and cutting depth. The simulation results indicate that as the cutting depth raises the number of cutting teeth in contact with surrounding rock, the cutting depth grows, resulting in a larger reaction force from the coal seam and greater fluctuations in drum load torque. Once the maximum cutting depth is reached, load torque stabilizes within a specific range. Considering cutting efficiency, the robot achieves a maximum cutting velocity of 1 m/min with a cutting depth of 250 mm for rock strength greater than f3. For rock strength f3, the maximum cutting velocity is 1 m/min with a 400 mm depth, and for f2, it is 2 m/min with a 400 mm depth. These findings provide a theoretical foundation for the development of adaptive cutting strategies in mining operations, contributing to improved performance and efficiency in complex mining conditions. Full article

The research object of this paper is a new type of multi-functional, air-gap-type, vehicle-mounted magnetic suspension flywheel battery. It is a new energy storage technology with a long working life, high energy conversion efficiency, multiple charging and discharging times, low carbon and environmental protection. However, when the vehicle-mounted flywheel battery is operating, it will inevitably be disturbed by road conditions, resulting in loose sensors and feedback errors, thereby reducing the control accuracy and reliability of the system. To solve these problems, a sensorless control system came into being. It samples the current of the magnetic bearing coil through the hardware circuit and converts it into displacement for real-time control, eliminating the risk of sensor failure. However, the control accuracy of the traditional sensorless system is relatively low. Therefore, this paper adopts a BP (backpropagation) neural network PID controller based on genetic algorithm optimization on the basis of the sensorless control system. Through the joint simulation of the dynamic simulation software ADAMS/VIEW2018 and MATLAB2022b, the optimal PID control parameter database for complex road conditions is established. Through sensorless technology, the current of the flywheel battery is converted into the position error for extensive training so that the genetic BP neural network PID controller can accurately identify the current complex road conditions according to the position error, so as to provide the optimal PID control parameters corresponding to the road conditions to carry out accurate real-time stability control of the flywheel rotor. The experimental results show that the method can effectively reduce feedback errors, improve the control accuracy, and output optimal control parameters in real time under complex road conditions, which significantly improves the reliability and control performance of the vehicle flywheel battery system. Full article

A high-gear-ratio anti-backlash 3K planetary gearbox with a preloaded flexure-based carrier is a suitable reducer for robot joints owning to its compact design and high transmission accuracy. However, to design such a 3K planetary gearbox with high bidirectional efficiencies for backdrivable robot joints, it is critical to develop an accurate transmission efficiency model to predict the effects of the preloaded flexure-based carrier on the efficiency of the 3K planetary gearbox. To determine the meshing forces of gear pairs in the 3K planetary gearbox, a quasi-static model is formulated according to tangential displacements of planet gears resulting from the preloaded flexure-based carrier. Considering the reverse meshing forces in the anti-backlash 3K planetary gearbox, a modified efficiency model is developed and the bidirectional transmission efficiencies are analyzed. Simulation results show that both forward and backward transmission efficiencies of the anti-backlash 3K planetary gearbox decrease as the preload increases, while they all increase with the increasing load torque. It is also revealed that the preload primarily affects the meshing efficiency of the sun–planet gear pair. Four different carrier prototypes are fabricated for experiments. The average errors between the predicted and measured results for forward and backward transmission efficiencies are 2.30% and 4.01%, respectively. Full article

This study presents the development of a real-time simulation model for electromechanical actuators tailored to a hybrid iron bird for next-generation regional turboprop aircraft. This iron bird is aimed at integrating real and virtual components, enabling advanced validation of flight control systems while balancing risk and cost. The mathematical models of actuators needed for the development and operation of the iron bird must comply with stringent requirements, especially in terms of computational cost. A novel two-step iterative methodology is proposed, combining bottom-up and top-down approaches. This process begins with simplified low-fidelity models. Then, the models are incrementally refined to capture complex dynamics while maintaining computational efficiency. Using the proposed approach, the computational time of the real-time model remained almost unvaried and consistent with the sampling frequency, while the number of state variables and the range of described phenomena grew significantly. The real-time model is validated against simulated data from a reference high-fidelity model and experimental data, achieving excellent agreement while reducing the computational time by 93%. The enhanced model incorporates selected failure modes equivalent models regarding the electric motor, power drive unit, and mechanical transmission, supporting possible future prognostics and health management (PHM) applications. These results showcase a scalable solution for integrating electromechanical actuation in modern aerospace systems, paving the way for full virtual iron birds and greener aviation technologies. Full article

Plant tendrils exhibit intriguing tropism motions like bending, twisting, and coiling. Herein, we report the application of a liquid crystal elastomer (LCE) to make a light-sensitive and biomimetic coil to replicate behaviors of plant tendrils. The LCE coil consists of diacrylate azobenzene, diacrylate mesogens, and thiol-based spacers. These components are first mixed to form a highly viscous prepolymer solution through a thiol-acrylate Michael addition reaction. Subsequently, an extrusion–rolling process is developed to draw the viscous solution into a coil, which is mechanically stretched in a single direction to align mesogens in the LCE. Finally, the coil is photopolymerized under UV light to form an LCE coil with a diameter of 375 µm. The LCE coil possesses good rigidity and flexibility and shows movement upon light exposure. For example, the LCE coil shows a reversible bending up to 120° to 365 nm UV and 30% contraction to 455 nm visible light, respectively, due to trans-cis photoisomerization of azobenzene derivatives. When the coil is irradiated with UV light with an intensity up to 10 mW cm⁻², it can twist and coil up. It can also wrap around the UV light tube in 6 s, similar to a plant tendril. This type of light-responsive coil has great potential in making biomimetic plants or soft robotics. Full article

Piezo-driven fast steering mirrors (PFSMs) are widely employed in high-precision beam steering and accurate tracking applications. However, the inherent hysteresis nonlinearity of piezoelectric actuators significantly degrades tracking accuracy. To address the challenges posed by dynamic hysteresis nonlinearity, this study proposes an improved non-singular fast terminal sliding mode control strategy. The proposed method integrates a non-singular fast terminal sliding surface and introduces an adaptive function in the reaching law to enhance response speed and improve control robustness. Additionally, the strategy incorporates an extended state observer (ESO) and an inverse model-based feedforward compensation mechanism. Specifically, the feedforward compensation based on the inverse model aims to offset hysteresis effects, while the ESO provides a real-time estimation of the total system disturbance to mitigate the impact of external disturbances and unmodeled hysteresis. Experimental results demonstrate that the proposed method effectively compensates for the hysteresis nonlinearity of PFSMs, improves disturbance rejection performance, and enhances position control accuracy. Full article

To overcome the limitations imposed by the low flexible angle of conventional robots, an active–passive variable stiffness elastic actuator (APVSA) is investigated and a nonlinear dynamic model for the APVSA is established, considering the factors of the moment of inertia, stiffness and damping of elastic elements, meshing stiffness of gear systems, nonlinear backlash, nonlinear meshing damping, and comprehensive transmission error. The established dynamic model is discretized by the forward Euler method, and the variable stiffness performance and the influence of nonlinear factors on the APVSA are analysed by Adams and Simulink simulations, respectively. A physical prototype and an experimental platform were assembled, and the dynamic and static variable stiffness experiments were conducted. The experimental results realized the expected stiffness adjustment target and provided the foundation for the next step of control. Full article

The variable valve mechanism, as a critical component for the efficient and low-carbon development of internal combustion engines, faces increasingly stringent requirements regarding its driving efficiency, output force, precision, and energy consumption. To address the limitations of existing technologies, a new composite electromagnetic valve train is proposed, characterized by a high force-to-power ratio, fast response, and high precision, along with a unique single/double drive mode, which offers greater flexibility in controlling valve timing parameters; however, it also introduces complex coupling relationships and increases the difficulty of optimization design. To this end, this paper establishes a thermodynamic model of the engine based on the composite electromagnetic valve mechanism. First, it analyzes the effects of different valve timing parameters and drive modes on engine performance; second, a multi-objective game theory optimization algorithm is employed to optimize the valve timing parameters and obtain the optimal solution set; finally, taking into account the energy consumption of the valve mechanism, engine emissions, and performance, a control strategy for valve timing parameters is developed based on an entropy-weighted method combined with a superiority and inferiority solution distance analysis. The results indicated that, under all the operating conditions of the engine, the average torque increased by 2.56%, the effective fuel consumption rate decreased by 6.23%, and nitrogen oxide emissions reduced by 9.86%. Meanwhile, an efficient and economical operational mode for the variable valve mechanism was obtained, providing new insights for the development of variable valve timing technology. Full article

A polymer-dispersed liquid crystal (PDLC) film is a device that can transition from opaque to transparent when electrically charged. These films can be used as actuators to control light levels in response to changing natural light. However, the current state of the art for controlling PDLC films is limited to on/off functionality, and few works in the current body of literature have explored continuous control. This study develops a novel nonlinear model for PDLCs in the context of the feedback control of light. This study also demonstrates the model’s utility by comparing experimental data of a PDLC in feedback with a proportional–integral (PI) controller for disturbance rejection and tracking of a desired light setpoint. This development is motivated by the need for a smart greenhouse that can provide programmable optimized light levels for plant growth. Specifically, a light sensor is composed of a circuit with photodiodes and calibrated for the photosynthetically active radiation range. The light sensor is placed under the film, separate from an exogenous light source, allowing for feedback control to be applied. A proportional–integral type control law is selected for stiffness and the ability to eliminate steady-state error, and it is implemented using a microcontroller. An equivalent analog control effort is applied to the PDLC via a PWM voltage signal and an H-bridge type driver. Details necessary for the driving of the PDLC are presented. Open-loop identification of the nonlinear quasi-static and dynamic step-response transients of the PDLC at different control levels are presented and modeled. Finally, closed-loop experimental and simulated results are presented for both light disturbance rejection and setpoint tracking. This shows that the proposed control framework allows for continuous control of light. Full article

In this work, we propose a lightweight pneumatic gripper that can grasp objects from either the outer or inner surfaces. Inspired by the Miura-ori pattern, the gripper is fabricated by laminating films with different cutting patterns to form the crease lines and air chambers. The asymmetry in the thickness of the top and bottom sides of the air chambers causes the gripper’s end to rotate in a predetermined direction upon inflation, enabling a dual-morphing grasping action. The dual morphings include an outward grasping morphing (grasping from the outer surface) and an inward grasping morphing (grasping from the inner surface). The deflection of the gripper’s end, induced by the air chamber’s inflation, is theoretically analyzed using a simplified one-dimensional model. We conducted both finite element modeling and experimental measurements to investigate the influence of the air chamber’s design parameters. Weighing only 4.5 g, the gripper can lift objects more than ten times of its own weight. This study provides a valuable design insight for developing more flexible and adaptable soft grippers capable of holding objects with a wider range of geometrical characteristics. Full article

This work investigates the implementation of the Deep Deterministic Policy Gradient (DDPG) algorithm to enhance the target-reaching capability of the seven degree-of-freedom (7-DoF) Franka Pandarobotic arm. A simulated environment is established by employing OpenAI Gym, PyBullet, and Panda Gym. After 100,000 training time steps, the DDPG algorithm attains a success rate of 100% and an average reward of −1.8. The actor loss and critic loss values are 0.0846 and 0.00486, respectively, indicating improved decision-making and accurate value function estimations. The simulation results demonstrate the efficiency of DDPG in improving robotic arm performance, highlighting its potential for application to improve robotic arm manipulation. Full article

This paper presents an alarm system and teleoperation control framework, comparing ROS 1 and ROS 2 within a local network to mitigate the risk of robots failing to reach their goals during autonomous navigation. Such failures can occur when the robot moves through irregular terrain, becomes stuck on small steps, or approaches walls and obstacles without maintaining a safe distance. These issues may arise due to a combination of technical, environmental, and operational factors, including inaccurate sensor data, sensor blind spots, localization errors, infeasible path planning, and an inability to adapt to unexpected obstacles. The system integrates a web-based graphical interface developed using frontend frameworks and a joystick for real-time monitoring and control of the robot’s localization, velocity, and proximity to obstacles. The robot is equipped with RGB-D and tracking cameras, a 2D LiDAR, and odometry sensors, providing detailed environmental data. The alarm system provides sensory feedback through visual alerts on the web interface and vibration alerts on the joystick when the robot approaches walls, faces potential collisions with objects, or loses stability. The system is evaluated in both simulation (Gazebo) and real-world experiments, where latency is measured and sensor performance is assessed for both ROS 1 and ROS 2. The results demonstrate that both systems can operate effectively in real time, ensuring the robot’s safety and enabling timely operator intervention. ROS 2 offers lower latency for LiDAR and joystick inputs, making it advantageous over ROS 1. However, camera latency is higher, suggesting the need for potential optimizations in image data processing. Additionally, the platform supports the integration of additional sensors or applications based on user requirements. Full article