Search Results (499)

This paper presents the results of real-time experiments conducted to evaluate the performance of a developed adaptive control scheme applied to control the motion of a real closed-kinematic chain mechanism (CKCM) robot manipulator with two degrees of freedom (DOFs). The developed control scheme, referred to as the decentralized adaptive synchronized control scheme (DASCS), was the result of the combination of model reference adaptive control (MRAC) based on the Lyapunov direct method and the synchronization technique. CKCM manipulators were considered in the experimental study due to their advantages over their open-kinematic chain mechanism (OKCM) manipulator counterparts, such as higher stiffness, better stability, and greater payload. The conducted computer simulation study showed that the DASCS was able to asymptotically converge tracking errors to zero, with all the active joints moving synchronously in a prescribed way. One of the important properties of the DASCS is the independence of robot manipulator dynamics, making it computationally efficient and therefore suitable for real-time applications. The present paper reports findings from experiments in which the DASCS was applied to control the above manipulator and carry out various paths. The DASCS’s performance was compared with that of a traditional adaptive control scheme, namely the SMRACS, when both schemes were applied to track the same paths. Full article

The challenge of achieving high-precision direction-of-arrival (DOA) estimation with enhanced degrees of freedom (DOFs) under a limited number of physical array elements remains a critical issue in array signal processing. To address this limitation, this paper makes the following three key contributions: (1) a novel moving sparse array synthesis model incorporating time-frequency-spatial joint processing for coprime frequencies signal sources; (2) an optimized coprime frequencies-based unmanned aerial vehicle array (CF-UAVA) configuration with derived closed-form expressions for the distribution of synthesized array; and (3) two DOA estimation methods: a group sparsity-based approach universally applicable to the proposed aperture synthesis model and a joint group sparsity and virtual array interpolation tailored for the proposed CF-UAVA configuration. Comprehensive simulation results demonstrate the superior DOA estimation accuracy and increased DOFs achieved by our proposed aperture synthesis model and DOA estimation algorithms compared to conventional approaches. Full article

In this paper, a viscoelastic (VE) tuned inerter damper (TID) that replaces conventional stiffness and damping elements with a cost-effective VE element is proposed to achieve a target-based improvement of seismically protected buildings. The semi-analytical solution of the optimal tuning frequency ratio of the VE TID is presented based on a two-degree-of-freedom (2-DOF) system, accounting for inherent structural damping disturbances, and then is extended to a MDOF system via an effective mass ratio. The accuracy of the semi-analytical solution is validated by comparing the numerical solution. Finally, numerical analyses on a viscoelastically damped building and a base-isolated building with optimally designed VE TIDs under historical earthquakes are performed. The numerical results validate the target-based improvement capability of the VE TID with a modest mass ratio in avoiding large strokes or deformation of existing dampers and isolators, and further reducing the specific mode vibration. Full article

This paper presents a comprehensive study of torsional stick–slip vibrations in rotary drilling systems through a comparison between two lumped parameter models with differing complexity: a simple two-degree-of-freedom (2-DOF) model and a complex high-degree-of-freedom (high-DOF) model. The two models are developed under identical boundary conditions and consider an identical nonlinear friction torque dynamic involving the Stribeck effect and dry friction phenomena. The high-DOF model is calculated with the Finite Element Method (FEM) to enable accurate simulation of the dynamic behavior of the drill string and accurate representation of wave propagation, energy build-up, and torque response. Field data obtained from an Algerian oil well with Measurement While Drilling (MWD) equipment are used to guide modeling and determine simulations. According to the findings, the FEM-based high-DOF model demonstrates better performance in simulating basic stick–slip dynamics, such as drill bit velocity oscillation, nonlinear friction torque formation, and transient bit-to-surface contacts. On the other hand, the 2-DOF model is not able to represent these effects accurately and can lead to inappropriate control actions and mitigation of vibration severity. This study highlights the importance of robust model fidelity in building reliable real-time rotary drilling control systems. From the performance difference measurement between low-resolution and high-resolution models, the findings offer valuable insights to optimize drilling efficiency further, minimize non-productive time (NPT), and improve the rate of penetration (ROP). This contribution points to the need for using high-fidelity models, such as FEM-based models, in facilitating smart and adaptive well control strategies in modern petroleum drilling engineering. Full article

Soft continuum robots are constructed from soft and compliant materials and can provide high flexibility and adaptability to various applications. They have theoretically infinite degrees of freedom (DOFs) and can generate highly nonlinear behaviors, which leads to challenges in accurately modeling and controlling their deformation, compliance, and behaviors. Inspired by animals, embodied intelligence utilizes physical bodies as an intelligent resource for information processing and task completion and offloads the computational cost of central control, which provides a unique approach to understanding and modeling soft robotics. In this study, we propose a theoretical framework to explain and guide distributed sensing enabled embodied intelligence for soft finger manipulation from a physics-based perspective. Specifically, we aim to provide a theoretical foundation to guide future sensor design and placement by addressing two key questions: (1) whether and why the state of a specific material point such as the tip trajectory of a soft finger can be predicted using distributed sensing, and, (2) how many sensors are sufficient for accurate prediction. These questions are critical for the design of soft and compliant robotic systems with embedded sensing for embodied intelligence. In addition to theoretical analysis, the study presents a feasible approach for real-time trajectory prediction through optimized sensor placement, with results validated through both simulation and experiment. The results showed that the tip trajectory of a soft finger can be predicted with a finite number of sensors with proper placement. While the proposed method is demonstrated in the context of soft finger manipulation, the framework is theoretically generalizable to other compliant soft robotic systems. Full article

In this paper, a robust tracking control problem for underactuated underwater vehicles in horizontal motion is investigated. The presented control scheme that performs the trajectory tracking task is a combination of the backstepping technique and the integral sliding mode control method using the inertial quasi velocities (IQVs) resulting from the inertia matrix decomposition. Unlike many known solutions, the proposed approach allows not only trajectory tracking, but also, due to the fact that IQV includes dynamic and geometric model parameters, allows us to obtain additional information about changes in vehicle behavior during movement. In this way, some insight into its dynamics is obtained. Moreover, the control strategy takes into account model inaccuracies and external disturbances, which makes it more useful from a technical point of view. Another advantage of this work is to indicate problems occurring during the implementation of trajectory tracking in algorithms with a dynamics model containing a diagonal inertia matrix, i.e., without inertial couplings. The theoretical results are illustrated by simulation tests conducted on two models of underwater vehicles with three degrees of freedom (DOF). Full article

Based on the research of the directional self-adaptive piezoelectric energy harvester (DSPEH), a structural design scheme of a multi-directional hybrid energy harvester (MHEH) is put forward. The working principle of the MHEH is experimentally studied. A prototype is designed and manufactured, and the output characteristics of the MHEH in vibrational degree of freedom (DOF) and rotational DOF are experimentally studied. Compared with the DSPEH, after adding the electromagnetic energy harvesting module, the MHEH effectively uses the rotational energy in the rotational DOF, achieves simultaneous energy harvesting from one excitation through two mechanisms, and the output power of the electromagnetic module reaches 61 μW. The total power of the system is increased by 10 times, the power density is increased by 500%, and the MHEH has high voltage output characteristics in multiple directions. Compared with traditional multi-directional and self-adaptive energy harvesters, the MHEH utilizes a reverse-thinking method to generate continuous rotational motion of the cantilever beam, thus eliminating the influence of external excitation direction on the normal vibration of the cantilever beam. In addition, the MHEH has achieved hybrid energy harvesting with a single cantilever beam and multiple mechanisms, providing new ideas for multi-directional energy harvesting. Full article

This study presents the design and experimental testing of a two-degrees-of-freedom (2DOF) elbow prosthesis prototype designed to replicate the movement patterns of a native or normal human elbow. Two methods of the control of the prosthesis, namely, the proportional–integral–derivative method (PID; a well-established method) and a combination of sliding mode control with a time base generator strategy (SMC + TBG; an advanced method), were compared on the basis of various performance metrics of the prosthesis, as obtained in laboratory tests. Among these metrics were the angular displacement and velocity as a function of time. The mechanical design combined 3D-printed components with custom-designed joints, featuring a worm gear transmission with a crown gear for flexion–extension, enhanced by torsional springs, and a pinion gear with a crown gear for pronation–supination and control. Sensors for voltage and current data acquisition enabled real-time monitoring and control. The prosthesis was tested in the laboratory with a range of motion of 100–120° for flexion–extension, 50° for supination, and 75° for pronation, demonstrating the adaptability of the actuators and validating their autonomy through battery-powered operation. The results showed that control using SMC + TBG resulted in biomimetic patterns for angular displacement and angular velocity of the prosthesis, whereas control using PID did not. Thus, the prosthesis with control provided using an SMC + TBG strategy may have been promised for use by people who have undergone transhumeral amputation. Full article

This paper presents a secure control framework enhanced with an event-triggered mechanism to ensure resilient and resource-efficient operation under false data injection (FDI) attacks on sensor measurements. The proposed method integrates a Kalman filter and a neural network (NN) to construct a hybrid observer capable of detecting and compensating for malicious anomalies in sensor measurements in real time. Lyapunov-based update laws are developed for the neural network weights to ensure closed-loop system stability. To efficiently manage system resources and minimize unnecessary control actions, an event-triggered control (ETC) strategy is incorporated, updating the control input only when a predefined triggering condition is violated. A Lyapunov-based stability analysis is conducted, and linear matrix inequality (LMI) conditions are formulated to guarantee the boundedness of estimation and system errors, as well as to determine the triggering threshold used in the event-triggered mechanism. Simulation studies on a two-degree-of-freedom (2-DOF) robot manipulator validate the effectiveness of the proposed scheme in mitigating various FDI attack scenarios while reducing control redundancy and computational overhead. The results demonstrate the framework’s suitability for secure and resource-aware control in safety-critical applications. Full article

Positioning servo systems utilizing permanent magnet synchronous linear motors (PMSLMs) are conventionally governed by cascaded P-PI controllers, which, despite their simplicity and robustness, suffer from limited tracking and anti-disturbance performance due to their single-degree-of-freedom (1-DOF) structure. This paper introduces a novel two-degree-of-freedom (2-DOF) control algorithm that integrates explicit model predictive control (EMPC) with a differential-compensated extended state observer (DCESO). The EMPC framework leverages position and velocity as state variables, eliminating the need for integral terms and thereby enhancing dynamic response. By employing an offline optimization approach, a control law is explicitly formulated to handle system constraints while minimizing online computational overhead. Additionally, a velocity feedforward term derived from the MPC framework is incorporated to further reduce tracking errors. To bolster disturbance rejection, the proposed DCESO introduces a differential compensator that mitigates the low-pass effects inherent in traditional ESOs, thereby improving estimation dynamics. Experimental results demonstrate that the proposed method significantly outperforms the conventional P-PI controller, increasing the position loop bandwidth from 147 Hz to 208 Hz and markedly enhancing anti-disturbance performance. The algorithm’s low online computational demand makes it highly suitable for industrial applications. Full article

Task scheduling for multiple humanoid robot manipulators in industrial and collaborative settings remains a significant challenge due to the complexity of coordination, resource sharing, and real-time decision-making. In this study, we propose a framework for modeling task scheduling for multiple humanoid robot manipulators by using the symbolic discrete controller synthesis technique. We encode the task scheduling problem as discrete events using parallel synchronous dataflow equations and apply our synthesis algorithms to manage the task scheduling of multiple humanoid robots via the resulting controller. The control objectives encompass the fundamental behaviors of the system, strict rules, and mutual exclusions over shared resources, categorized as the safety property, whereas the optimization objectives are directed toward maximizing the throughput of robot-processed products with optimal efficiency. The humanoid robots considered in this study consist of two pairs of six-degree-of-freedom (6-DOF) robot manipulators, and the inverse kinematics problem of the 6-DOF arms is addressed using metaheuristic approaches inspired by biomimetic principles. Our approach is experimentally validated, and the results demonstrate high accuracy and performance compared to other approaches reported in the literature. Our approach achieved an average efficiency improvement of 40% in 70-robot systems, 20% in 30-robot systems, and 10% in 10-robot systems in terms of production throughput compared to systems without a controller. Full article

Cable-driven redundant manipulators (CDRMs) are widely applied in various fields due to their notable advantages. Stiffness regulation capability is essential for CDRMs, as it enhances their adaptability and stability in diverse task scenarios. However, their stiffness regulation still faces two main challenges. First, stiffness regulation methods that involve physical structural modifications increase system complexity and reduce flexibility. Second, methods that rely solely on cable tension are constrained by the inherent stiffness of the cables, limiting the achievable regulation range. To address these challenges, this paper proposes a novel stiffness regulation method for CDRMs through the combined optimization of configuration and cable tension. A stiffness model is established to analyze the influence of the configuration and cable tension on stiffness. Due to the redundancy in degrees of freedom (DOFs) and actuation cables, there exist infinitely many configuration solutions for a specific pose and infinitely many cable tension solutions for a specific configuration. This paper proposes a dual-level stiffness regulation strategy that combines configuration and cable tension optimization. Motion-level and tension-level factors are introduced as control variables into the respective optimization models, enabling effective manipulation of configuration and tension solutions for stiffness regulation. An improved differential evolution algorithm is employed to generate adjustable configuration solutions based on motion-level factors, while a modified gradient projection method is adopted to derive adjustable cable tension solutions based on tension-level factors. Finally, a planar CDRM is used to validate the feasibility and effectiveness of the proposed method. Simulation results demonstrate that stiffness can be flexibly regulated by modifying motion-level and tension-level factors. The combined optimization method achieves a maximum RSR of 17.78 and an average RSR of 12.60 compared to configuration optimization, and a maximum RSR of 1.37 and an average RSR of 1.10 compared to tension optimization, demonstrating a broader stiffness regulation range. Full article

This paper presents an adaptive sliding mode controller (ASMC) with the implication of a forgetting factor for a two-degree-of-freedom (2-DOF) arm robot manipulator trajectory tracking. The proposed approach builds upon conventional sliding mode control (SMC), which is well known for its robustness and low tracking error. The controller dynamically adjusts this parameter by introducing an adaptive mechanism to enhance trajectory tracking, guarantee high robustness, and reduce chattering effects. In order to mitigate gain drift, a forgetting factor is incorporated into the adaptation law, ensuring stable and reliable control performance. Stability is validated using Lyapunov theory, and the effectiveness of the proposed ASMC is evaluated through numerical simulations. The simulations are conducted in MATLAB R2023b using a dynamic model of the 2-DOF robotic manipulator. Comparative results with conventional SMC confirm that the adaptive approach significantly improves tracking accuracy, noise robustness, and chattering suppression. Full article

To investigate the suppression method for vortex-induced vibrations (VIV) of two-degree-of-freedom (2-DOF) rotating cylinders with dual splitter plates, numerical simulations are conducted at a Reynolds number of 200, a mass ratio of 2.6, and rotation ratio of 2. The effects of the gap distance and the width of splitter plates on the vibration response, hydrodynamic coefficients, and flow wakes of rotating cylinders are examined. The numerical results show the existence of distinct suppression mechanisms between low gap distances (G/D = 0.25–0.5) and high gap distances (G/D = 0.75–2.0). Furthermore, the width (W/D) is considered as a critical factor in suppression effectiveness. The distributions of wake patterns under different gap distance and width are analyzed, and six wake patterns are observed. Finally, lift and drag coefficients are examined, revealing their distinct sensitivities to G/D and W/D. The optimal gap distance and width parameters of dual splitter plates for rotating cylinders suppression are determined. Marine drilling is persistently subjected to VIV, which critically compromise structural stability. The findings of this study deliver engineering value for marine riser VIV suppression. Full article

This paper focuses on the design analysis of a novel 5-degrees of freedom (DOF) double-driven parallel mechanism (PM). By arranging two independent actuators on one branch chain, the mechanism can realize the five degrees of freedom of the moving platform only by relying on three branch chains, which have the characteristics of a compact structure and large workspace. Subsequently, the kinematic model of the mechanism is established, and the workspace, dexterity, and singularity characteristics are analyzed based on the derived model. Additionally, an explicit dynamic model of the mechanism is established based on the principle of virtual work. Finally, based on the dynamic model, the manipulability ellipsoid index and the inertial coupling strength index are proposed, and the distribution of these two kinds of dynamic performance indexes in the workspace is studied. Full article