Search Results (214)

Suspension dome structures are widely utilized due to their superior performance compared to conventional structures. The condition of the cables, particularly the forces they experience, is critical for ensuring the safety of the overall structures. However, friction between cables and joints significantly disrupts cable force distribution, particularly during pre-stressing construction. This paper integrates a tension-compensation method with a numerical approach that accurately accounts for friction effects. A computational flowchart was introduced and subsequently applied to analyze a practical suspension dome structure. We assessed the impact of friction on cable forces, structural deformations, and the mechanical state of the cable–strut system. Furthermore, we quantified the consequences of excessive tensioning. The findings demonstrate that the method presented in this paper can efficiently be employed for the analysis of large-scale complex structures and is readily accessible to structural designers. Full article

This study resolves a critical challenge in electromechanical brake system validation: conventional ABS/RBS integrated platforms’ inability to dynamically simulate tire-road adhesion characteristics during braking. We propose a fuzzy adaptive PID-controlled magnetic powder clutch (MPC) system that achieves ground braking force simulation synchronized with slip ratio variations. The innovation encompasses: (1) Dynamic torque calculation model incorporating the curve characteristics of longitudinal friction coefficient ($\phi$) versus slip ratio ($s$), (2) Nonlinear compensation through fuzzy self-tuning PID control, and (3) Multi-scenario validation platform. Experimental validation confirms superior tracking performance across multiple scenarios: (1) Determination coefficients R² of 0.942 (asphalt), 0.926 (sand), and 0.918 (snow) for uniform surfaces, (2) R² = 0.912/0.908 for asphalt-snow/snow-asphalt transitions, demonstrating effective adhesion characteristic simulation. The proposed control strategy achieves remarkable precision improvements, reducing integral time absolute error (ITAE) by 8.3–52.8% compared to conventional methods. Particularly noteworthy is the substantial ITAE reduction in snow conditions (236.47 vs. 500.969), validating enhanced simulation fidelity under extreme road surfaces. The system demonstrates consistently rapid response times. These improvements allow for highly accurate replication of dynamic slip ratio variations, establishing a refined laboratory-grade solution for EV regenerative braking coordination validation that greatly enhances strategy optimization efficiency. Full article

This study introduces a rigid–flexible coupled constant force actuator integrated with Active Disturbance Rejection Control (ADRC) to tackle the rigidity–compliance trade-off in precision force-sensitive applications. The actuator utilizes compliant hinges to decrease contact stiffness by three orders of magnitude (${10}^6\to {10}^3 \mathrm{N}/\mathrm{m}$), facilitating effective force management through millimeter-scale placement (0.1∼1 mm) and inherently mitigating high-frequency disturbances. The ADRC framework, augmented by an Extended State Observer (ESO), dynamically assesses and compensates for internal nonlinearities (such as friction hysteresis) and external disturbances without necessitating accurate system models. Experimental results indicate enhanced performance compared to PID control: under dynamic disturbances, force deviations are limited to $\pm 0.2 \mathrm{N}$ with a 98.5% reduction in mean absolute error, a 96.3% increase in settling speed, and 99% suppression of oscillations. The co-design of mechanical compliance with model-free control addresses the constraints of traditional high-stiffness systems, providing a scalable solution for industrial robots, compliant material processing, and medical device operations. Validation of the prototype under sinusoidal perturbations demonstrates reliable force regulation (settling time $<0.56 \mathrm{s}$, errors $<0.5 \mathrm{N}$), underscoring its relevance in dynamic situations. This study integrates theoretical innovation with experimental precision, enhancing intelligent manufacturing systems via adaptive control and structural synergy. Full article

Resistive angle sensors are widely used due to their simple signal conditioning circuits and high cost-effectiveness. This paper presents a resistive angle sensor based on a rotary potentiometer, designed to offer a measurement range of 180° for low-cost angle measurement in industrial automation and electromagnetic interference (EMI)-sensitive applications. The sensor features a specially designed signal conditioning circuit and mechanical housing. Experimental results show that it exhibits excellent linearity and temperature stability over a wide temperature range of −20 °C to 60 °C, with a zero-temperature drift of approximately 0.004°/°C. For the nonlinearity and hysteresis caused by unavoidable friction and manufacturing tolerances between the transmission mechanism and rotary potentiometer, an adaptive linear neuron (ADALINE) technique based on the α-least mean square (α-LMS) algorithm was implemented for software compensation. The results show that the percentage nonlinearity error was reduced from the original 4.413% to 0.182%, and the percentage hysteresis error was decreased from the original 4.061% to 0.404%. The research results of this paper offer valuable insight for high-precision resistive angle sensors. Full article

To enhance riding comfort for drivers of heavy-duty vehicles, this paper introduces a novel adaptive prescribed performance control (APPC) for active seat suspension systems. The model incorporates dynamic friction and hysteresis damping effects to capture the complex behavior of the seat suspension. The accuracy of the proposed model is validated through experimental data. The controller utilizes a prescribed performance function (PPF) to regulate the dynamic response of the system, combined with an adaptive backstepping control (ABC) method to account for system uncertainties, such as variations in driver weight, friction, suspension stiffness, and damping coefficients. A set of parameter estimators, governed by innovative adaptive laws, compensates for estimation errors. Furthermore, the stability of the controlled system is rigorously demonstrated. Both simulation and experimental tests, including bump and random excitation tests, are conducted to assess the controller performance in both time and frequency domains. The results confirm that the proposed controller effectively mitigates vibrations in the driver–seat system and demonstrates robustness against system uncertainties. Full article

In integrated permanent magnet synchronous motors (IPMSMs) coupled with mechanical devices such as ball screws and reducers, complex nonlinear friction characteristics often arise, leading to asymmetrical distortions such as position “flat-top” and speed “ramp-up”. These phenomena significantly degrade the system’s positioning accuracy. To address this issue, this paper introduces a symmetry-inspired nonlinear predictive speed control approach based on the Stribeck piecewise linearized friction compensation and a generalized proportional integral (GPI) observer. The proposed method leverages the inherent symmetry in the Stribeck friction model to describe the nonlinear behavior, employing online piecewise linearization via the least squares method. A GPI observer was designed to estimate the lumped disturbance, including time-varying components in the speed dynamics, friction model deviations, and external loads. By incorporating these estimates, a nonlinear predictive controller was developed, employing a quadratic cost function to derive the optimal control law. The experimental results demonstrate that, compared to traditional integral NPC and PI controllers, the proposed method effectively restores system symmetry by eliminating the “flat-top” and “ramp-up” distortions while maintaining computational efficiency. Full article

This paper proposes a disturbance observer (DOB)-based robust force control framework for tendon-sheath mechanisms (TSMs) that transmit tension forces from the proximal to the distal end. A detailed physical model of the TSM system, where a motor actuates the tendon and the output corresponds to the contact force at the robot end-effector, is developed. However, the resulting nominal model adopts a simplified representation of friction and involves significant parametric uncertainties due to the inherently complex dynamics of the tendon-sheath structure. By rigorously verifying the well-established robust stability conditions associated with DOB-based control frameworks, it is confirmed that the tendon-sheath transmission system satisfies all required assumptions and stability criteria. Furthermore, the necessary additional conditions can be readily met by appropriately designing the Q-filter, which is comparatively straightforward in practice. This validation supports the theoretical soundness and practical suitability of employing a DOB to effectively estimate and compensate for the system’s inherent parametric uncertainties and external disturbances. Numerical simulations incorporating a discrete-segment tendon model with an advanced friction dynamics formulation demonstrate significant improvements in force tracking accuracy at the tendon’s distal end compared to conventional control schemes without DOB compensation. The results highlight the robustness and effectiveness of the proposed control scheme for tendon-driven robotic systems. Full article

In this work, we aimed to determine the nonlinear disturbance caused by cascaded coupling rigid–flexible deformation and friction in a direct-driven servo electric cylinder terminal positioning system (DDSEC-TPS) during feed motion of an intermittent, reciprocating, and time-varying load. For this purpose, a cascaded coupling dynamic error model of DDSEC-TPS was established based on the position–pose error model of the parallel motion platform and the rotor field-oriented vector transform. Then, a model to observe the dynamic error of the DDSEC-TPS was established using the improved beetle antennae search algorithm backpropagation neural network (IBAS-BPNN) prediction model according to the rigid–flexible deformation error theory of feed motion, and the observed dynamic error was compensated for in the vector control strategy of the DDSEC-TPS. The length and error prediction models were trained and validated using opposite and mixed datasets tested on the experimental platform, to observe dynamic errors and evaluate and optimize the prediction models. The experimental results show that dynamic error compensation can improve the position tracking accuracy of the DDSEC-TPS and the position–pose performance of the parallel motion platform. This study is of great significance for improving the consistency of following multiple DDSEC-TPSs and the position–pose accuracy of parallel motion platforms. Full article

Iterative feedforward tuning (IFFT) compensates for the dynamic tracking error in linear servo systems caused by reference trajectory and nonlinear friction. The feedback controller with infinite DC gain makes the steady-state tracking error zero. This paper analyzes the effect of the DC gain of the feedback controller on IFFT and proposes an IFFT strategy with a variable-gain feedback controller. This strategy makes the dynamic tracking error due to Coulomb friction behave as a continuous and easy-to-construct window function, which makes the feedforward basis function vector consistent with the dimensionality of the dynamic tracking error. This strategy improves both the efficiency and accuracy of IFFT compared to IFFT using a fixed-gain feedback controller. The dynamic tracking error is compensated to the maximum extent possible, and the steady-state tracking error is zero. Theoretical verification and experimental results indicate the excellent iterative efficiency and accuracy of IFFT with a variable-gain feedback controller. Full article

This study addresses the question: “Does the towing tank water temperature affect the result of model-ship extrapolation?” While it is well-established that temperature variations affect Reynolds numbers and consequently frictional and viscous resistance, this study examines whether the ITTC 1978 extrapolation method properly compensates for these effects. Although current procedures consider temperature indirectly through the Reynolds number, they assume that the form factor depends solely on the Froude number and is insensitive to viscosity changes. Our analysis reveals that the form factor is also temperature-sensitive, indicating a fundamental limitation in the conventional approach. This sensitivity arises from the limitations of the ITTC 1957 friction curve and the method’s neglect of temperature-induced variations in the form factor. To quantify the effect of temperature, model-scale CFD simulations were conducted for two ship models (KCS and KVLCC2) at different water temperatures using the ITTC 1978 procedure with Prohaska’s method. The results show that the ship-scale total resistance coefficient ($C_T$) can vary by up to 2.8% depending on the water temperature and friction line selection. This demonstrates that the ITTC 1978 performance prediction method fails to adequately compensate for the temperature-induced changes in resistance, which leads to systematic errors in the extrapolated results. Full article

This research article tackles the control problem of an inverted pendulum, also known as the Furuta pendulum, mounted on a velocity-controlled robot manipulator in two configurations: the rotary pendulum and the translational pendulum. Differently from most of the existing control architectures where the motor actuating the pendulum motion is torque-controlled, the proposed control architecture exploits the inner velocity loop usually available on industrial robots, thus easing the implementation of an inverted pendulum. Another aspect investigated in this paper and mostly overlooked in the literature is the digital implementation of the control and, specifically, the latency introduced by the digital controller. The proposed control solution explicitly models such effects in the control design phase, improving the closed-loop performance. The additional novelty introduced by this paper is the friction compensation that is essential in the swing-up phase of the inverted pendulum, whereas classical control strategies for the nonlinear swing-up usually neglect this effect, and their solutions lead to control failures in practical systems. This paper presents detailed modeling and experimental identification phases followed by the control design of both the nonlinear swing-up algorithm and the linear stabilization controller, both experimentally validated on a Meca500 robotic arm controlled via an EtherCAT communication protocol by a mini PC featuring a Xenomai real-time operating system. The overall system showcases the potential of high-performance digital control systems in industrial robotic applications. Full article

The dynamic error is the dominant factor affecting multi-axis CNC machining accuracy. Predicting and compensating for dynamic errors is vital in high-speed machining. This paper proposes a novel prediction-model-based approach to predict and compensate for the ball screw feed system’s dynamic error. Based on the lumped and distributed mass methods, this method constructs a parameterized dynamic model relying on the moving component’s position for electromechanical coupling modeling. Using Latin Hypercube Sampling and numerical simulation, a sample set containing the input and output of one control cycle is obtained, which is used to train a Cascade-Forward Neural Network to predict dynamic errors. Finally, a feedforward compensation strategy based on the prediction model is proposed to improve tracking performance. The proposed method is applied to a ball screw feed system. Tracking error simulations and experiments are conducted and compared with the transfer function feedforward compensation. Typical trajectories are designed to validate the effectiveness of the electromechanical coupling model, the dynamic error prediction model, and the feedforward compensation strategy. The results show that the prediction model exhibits a maximum prediction deviation of 1.8% for the maximum tracking error and 13% for the average tracking error. The proposed compensation method with friction compensation achieves a maximum reduction rate of 76.7% for the maximum tracking error and 63.7% for the average tracking error. Full article

In the control of robot manipulators, input torque constraints and system nonlinearities present significant challenges for precise trajectory tracking. However, fuzzy adaptive logic control (FALC) often fails to generate the optimal membership functions or function intervals. This paper proposes a modified greater cane rat algorithm (MGCRA) to optimize a fuzzy adaptive logic controller (FALC) for minimizing input torques during trajectory tracking tasks. The main innovation lies in integrating the improved MGCRA with FALC, which enhances the controller’s adaptability and performance. For benchmarking, several state-of-the-art swarm intelligence algorithms—including particle swarm optimization (PSO), artificial bee colony (ABC), ant colony optimization (ACO), gray wolf optimization (GWO), covariance matrix adaptation evolution strategy (CMA-ES), adaptive guided differential evolution (AGDE), the basic greater cane rat algorithm (GCRA), and a trial-and-error method—are compared under identical conditions. Experimental results show that the MGCRA-tuned FALC achieves lower input torques and improved trajectory tracking accuracy compared to other methods. The findings demonstrate the effectiveness and potential of the proposed MGCRA-FALC framework for advanced robotic manipulator control. Full article

Recovering from upper limb injuries is very important because having limited functionality affects everyday tasks. Rehabilitation supporting systems significantly impact the results; however, it is important to ensure that they are safe and accurate. This study addressed friction forces and gravity on the movement quality of a mechatronic rehabilitation device (MWR) for the upper limb. At first, an experimental analysis was conducted to quantify the active torque required to maintain specific angular positions. The results revealed the significant impact of the mass of mechanical components and friction between moving parts on the device’s movement quality. To address these issues, friction and gravity compensation functions were derived empirically and integrated into the control system’s algorithm. Implementing these compensation functions resulted in a substantial improvement in movement quality, as demonstrated by a reduction of over 50% in the integral of the absolute position error. These results underscore the importance of physical constraints in the control design of rehabilitation devices and provide a foundation for developing adaptive rehabilitation technologies that enhance therapeutic outcomes. Full article

In this paper, an adaptive control scheme composed of an estimated feed-forward compensation and a PD control law with three mutually independent estimators is proposed for the tracking of desired trajectories in joint space for a robotic arm. One of the estimators is used to identify inertial and geometrical parameters, while the others determine the two principal components of the friction phenomenon: the part whose magnitude is position-dependent but velocity-independent and the part whose magnitude is proportional to velocity. Next, the persistently exciting condition is satisfied for each regression matrix of the estimators in a way that is easier to prove than the classical structure. Then, uniform global asymptotic stability can be concluded for the tracking error, regardless of parametric convergence, by applying the direct Lyapunov theorem. This scheme has been applied experimentally for a robotic arm to verify the theoretical results. The experimental results yielded a better performance in both estimating the parameters and tracking, with a much simpler overall analysis than the alternatives consulted. Full article