Search Results (8,945)

This paper presents a 2D micro-conveyance device based on a 3 × 3 electromagnetic digital actuator array. This device allows the conveyed object to be moved between several discrete positions distributed in the xy-plane through a collaborative actuation of the digital actuators. Each digital actuator includes a mobile permanent magnet placed in a square cavity and can be moved between four discrete positions. An analytical model of the digital actuators was proposed and used to design the conveyance device. Then, a prototype was built using rapid prototyping techniques and was experimentally characterized. The reachable workspace of the conveyance device is 56 mm × 56 mm in the xy-plane, and the proposed architecture enables the workspace to be easily enlarged by adding elementary modules. The distance between two discrete positions is 4 mm, and the positioning repeatability was measured as 5.5 µm. The maximum conveyance velocity and transportable mass were found to be up to 16 mm.s⁻¹ and 15 g, respectively. Full article

This study proposes a permanent magnet edge topology optimization method to address the low force output efficiency in Electromagnetic Vibration Absorbers caused by magnetic field distortion at the geometric discontinuity between the permanent magnet and the magnetic yoke. A theoretical model incorporating magnetic flux enhancement and improved directional consistency is established, revealing a transition in dominant mechanisms: magnetic flux enhancement dominates at small chamfer depths, while improved directional consistency becomes predominant at larger chamfer depths. Experimental validation was conducted on the optimized structure with a standard chamfer angle and 4 mm chamfer depth under operational conditions. Test results show an average force output increase of 4.6%, reaching 6.8% at 5 A. This research provides a theoretical basis and design methodology for geometric optimization of electromagnetic actuators in space-constrained environments. Full article

With the increasingly prominent demand for building energy efficiency and occupant-centric design, accurate and reliable personal thermal comfort models (PTCMs) are playing an important role in various residential and energy applications (e.g., building energy-saving design, indoor environmental regulation, and health and well-being improvement). In recent years, data-driven and artificial intelligence (AI) technologies have attracted considerable attention in the field of personal thermal comfort modeling. This study systematically reviews recent progress in data-driven personal thermal comfort modeling, emphasizing contact-based and non-contact data collection ways, correlation analysis of feature data, modeling methods based on machine learning and deep learning. Considering the high cost and limited scale of collection experiments, as well as noise, ambiguity, and individual differences in subjective feedback, special attention is put on the data-efficient thermal comfort modeling in data scarcity scenarios using a transfer learning (TL) strategy. Characteristics and suitable occasions of four transfer methods (model-based, instance-based, feature-based, and ensemble methods) are summarized to provide a deep perspective for practical applications. Furthermore, integration of PTCM into building environment control is summarized from aspects of the integration framework, modeling method, control strategy, actuator, and control effect. Performance of the integrated systems is analyzed in terms of improving personal thermal comfort and promoting building energy efficiency. Finally, several challenges faced by PTCMs and future directions are discussed. Full article

This paper investigates the robust fault-tolerant control (FTC) problem for interval type-2 fuzzy systems (IT2FS) with simultaneous time-varying input and state delays. In order to more comprehensively capture system uncertainties, an Interval Type-2 (IT2) fuzzy model is constructed, which, compared to the conventional Interval Type-1 model, better captures the uncertainty information of the system. A premise-mismatched fault-tolerant controller is designed to ensure system stability in the presence of actuator faults, while providing greater flexibility in the selection of membership functions. In the stability analysis, a novel Lyapunov–Krasovskii functional is formulated, incorporating membership-dependent matrices and delay-product terms, leading to sufficient conditions for closed-loop stability based on linear matrix inequalities (LMIs). A numerical simulation and a practical physical model are used, respectively, to illustrate the effectiveness of the proposed method. Comparative experiments further reveal the impact of input delays and actuator faults on closed-loop performance, verifying the effectiveness and robustness of the designed controller, as well as the superiority of interval type-2 over interval type-1. Full article

Cable-driven robotic systems are widely used in applications requiring lightweight structures, large workspaces, and accurate force regulation. In such systems, the mechanical behavior of cable-driven actuators is strongly influenced by the elastic properties of the cable, transmission elements, and supporting structure, leading to an effective stiffness that varies with pretension, applied load, cable length, and operating conditions. These stiffness variations have a direct impact on force control performance but are often implicitly treated or assumed constant in control-oriented studies. This paper investigates the effects of operating-point-dependent (incremental) cable stiffness on actuator-level force control performance in cable-driven robotic systems. The analysis is conducted at the level of an individual cable-driven actuator to isolate local mechanical effects from global robot dynamics. Mechanical stiffness is characterized within a limited elastic domain through local linearization around stable operating points, avoiding the assumption of global linear behavior over the entire force range. Variations in effective stiffness induced by changes in pretension, load, and motion regime are analyzed through numerical simulations and experimental tests performed on a dedicated test bench. The results demonstrate that stiffness variations significantly affect force tracking accuracy, dynamic response, and disturbance sensitivity, even when controller structure and tuning parameters remain unchanged. Full article

Time-varying formation tracking of networked unmanned aerial vehicle (UAV) systems plays a crucial role in cooperative missions such as encirclement, cooperative surveillance, and search-and-rescue operations, where human operators are often involved and system reliability is challenged by actuator faults and external disturbances. Motivated by these practical considerations, this paper investigates a human-in-the-loop time-varying formation tracking problem for networked UAV systems subject to compound actuator faults and external disturbances. To address this problem, a novel two-layer control architecture is developed, comprising a distributed observer and a fault-tolerant controller. The distributed observer enables each UAV to estimate the states of the human-in-the-loop leader using only local information exchange, while the fault-tolerant controller is designed to preserve formation tracking performance in the presence of compound actuator faults. By incorporating dynamic iteration regulation and adaptive laws, the proposed control scheme ensures that the formation tracking errors converge to a bounded neighborhood of the origin. Rigorous Lyapunov-based analysis is conducted to establish the stability, convergence, and robustness of the resulting closed-loop system. Numerical simulations further demonstrate the effectiveness of the proposed method in achieving practical time-varying formation tracking under complex fault scenarios. Full article

Dynamic positioning (DP) systems play a critical role in maintaining vessel position and heading under environmental disturbances such as wind, waves, and currents. This study presents a model predictive control (MPC)-based DP system for a fireboat equipped with a rudder–propeller configuration, explicitly accounting for both environmental loads and the reaction force generated during water cannon operation. Unlike conventional DP architectures in which DP control and thrust allocation are treated as separate modules, the proposed framework integrates both functions within a unified MPC formulation, enabling real-time optimization under actuator constraints. Environmental loads are modeled by incorporating nonlinear second-order wave drift effects, while nonlinear rudder–propeller interaction forces are derived through computational fluid dynamics (CFD) analysis and embedded in a control-oriented dynamic model. This modeling approach allows operational constraints, including rudder angle limits and propeller thrust saturation, to be explicitly considered in the control formulation. Simulation results demonstrate that the proposed MPC-based DP system achieves improved station-keeping accuracy, enhanced stability, and increased robustness against combined environmental disturbances and water cannon reaction forces, compared to a conventional PID controller. Full article

Shape memory alloy (SMA) actuators possess unique advantages for aerospace applications, including significant deformation, a high work-to-weight ratio, and structural simplicity. However, SMA actuators exhibit inherently strongly saturated and asymmetric hysteresis characteristics, which cause significant hysteresis in the output response. These hysteresis nonlinearities, compounded by process and measurement noise, severely degrade control precision. To overcome these issues, this study proposes a Smoothed Generalized Prandtl–Ishlinskii (SGPI) model to characterize such hysteresis behavior. Based on the SGPI model, we developed a state-space representation for the SMA actuator. Furthermore, an Extended Kalman Filter (EKF) is employed to estimate unmeasurable internal hysteresis states, and these estimates are subsequently utilized as input states for Model Predictive Control (MPC). The simulation results demonstrate that the proposed EKF-MPC approach achieves both rapid dynamic response and high-precision tracking control, effectively compensating for hysteresis nonlinearity while rejecting noise disturbances. Full article

This study investigates the incorporation of a standardised flexibility protocol within a physics-based models to enable controllable demand-side flexibility in residential energy systems. A heating subsystem is developed using MATLAB/Simulink and Simscape, serving as a testbed for protocol-driven control within a Multi-Energy System (MES). A conventional thermostat controller is first established, followed by the implementation of an OpenADR event engine in Stateflow. Simulations conducted under consistent boundary conditions reveal that protocol-enabled control enhances system performance in several respects. It maintains a more stable and pronounced indoor–outdoor temperature differential, thereby improving thermal comfort. It also reduces fuel consumption by curtailing or shifting heat output during demand-response events, while remaining within acceptable comfort limits. Additionally, it improves operational stability by dampening high-frequency fluctuations in mdot_fuel. The resulting co-simulation pipeline offers a modular and reproducible framework for analysing the propagation of grid-level signals to device-level actions. The research contributes a simulation-ready architecture that couples standardised demand-response signalling with a physics-based MES model, alongside quantitative evidence that protocol-compliant actuation can deliver comfort-preserving flexibility in residential heating. The framework is readily extensible to other energy assets, such as cooling systems, electric vehicle charging, and combined heat and power (CHP), and is adaptable to additional protocols, thereby supporting future cross-vector investigations into digitally enabled energy flexibility. Full article

Achieving a balance between rapid adaptation and robustness is a critical yet challenging objective in the design of industrial control systems. Model Reference Adaptive Control (MRAC) is a standard approach for managing system uncertainties; however, it suffers from a fundamental trade-off between adaptation speed and robustness. The high adaptation gains required for fast tracking often lead to parameter bursting or instability in the presence of noise. To resolve this issue, this paper proposes a new Dual-Loop Optimal Feedback Control (OFC) architecture applied to a Brushless DC (BLDC) motor drive. Unlike conventional methods that rely solely on tuning the adaptive mechanism, the proposed architecture introduces a parallel compensation loop designed to decouple disturbance rejection from reference tracking. This structure utilizes a Genetic Algorithm (GA) as an offline optimization engine to identify the Optimal Compensator gains that balance transient recovery with steady-state stability. Experimental validation demonstrates that the proposed Dual-Loop OFC architecture significantly outperforms traditional approaches. Specifically, it achieves an 88.99% reduction in overshoot and a 13.8% reduction in settling time compared to Conventional MRAC (CMRAC). Furthermore, it exhibits an 86.7% faster rise time compared to Self-Tuning Fuzzy PID (STFPID). These results confirm that the proposed Dual-Loop structure effectively mitigates the classic adaptability–robustness trade-off, offering a stable and high-performance solution for industrial actuators under varying operating conditions. Full article

The systems to manipulate a single particle in a microfluidic channel can be adopted to pharmacological and cytological experiments of single-cell observation. The common cell position systems use syringe pumps driven by piezoelectric devices, and these have a flow quantity limit. To achieve single-cell manipulation using actuators without limiting the flow quantity and with a low risk of contamination, we propose a particle control system that uses a sidewall-driven peristaltic micropump driven by pneumatic pressure. The adopted pump was integrated into a single-layer mold with a flow path and was simple to fabricate. Unlike syringe pumps, it not only pumps water forward, but also inhales from the back simultaneously, and can pump indefinitely. We developed a responsive and precise particle position control system using this pump in combination with a high-speed camera. In this system, the pumping pressure is operated by real-time adjustment of a pneumatic pressure supply to realize PID control. This approach moves the particle rapidly when it is far from a designated target position for a quick approach and slowly near the target position to position precisely. Full article

This review addresses the pivotal challenge in distributed-drive electric vehicle (DDEV) dynamics control: how to optimally distribute braking and steering forces during combined maneuvers to simultaneously enhance lateral stability, safety, and energy efficiency. The over-actuated nature of DDEVs presents a unique opportunity for precise torque vectoring but also introduces complex coupled dynamics, making vehicles prone to instability such as rollover during aggressive steering–braking scenarios. Moving beyond a simple catalog of methods, this work provides a structured synthesis and evolutionary analysis of chassis control methodologies. The problem is first deconstructed into two core control objectives: lateral stability and longitudinal braking performance. This is followed by a critical analysis of how integrated control architectures resolve the inherent conflicts between them. The analysis reveals a clear trajectory from independent control loops to intelligent, context-aware coordination. It further identifies a paradigm shift from the conventional goal of merely maintaining stability toward proactively managing stability boundaries to enhance system resilience. Furthermore, this review highlights the growing integration with high-level motion planning in automated driving. By synthesizing the current knowledge and mapping future directions toward deeply integrated, intelligent control systems, it serves as both a reference for researchers and a design guide for engineers aiming to unlock the full potential of the distributed drive paradigm. Full article

To investigate the performance of skewed roller thrust bearings (SRTBs) in the no-back brake of horizontal stabilizer trim actuators (HSTAs), this study conducts systematic theoretical modelling, experimental validation, and numerical simulation focusing on torque and contact characteristic optimization. First, a theoretical model for resistance torque of the SRTB was established based on the kinematics and load behaviours, followed by a systematic investigation into the effects of roller centre position and skew angle on the bearing’s resistance torque. An experimental platform was built, and tests were carried out on the bearings to verify the results of the theoretical analysis. Subsequently, a tangent arc profile was applied to the rollers to mitigate stress concentration at their ends, and the influences of crown drop and straight segment length on roller contact stress were explored by finite element method. Finally, considering the actual operating conditions of no-back brake components, the effect of roller centre position on brake deformation and roller contact stress was studied. The results show that the resistance torque increases with both roller skew angle and centre position, but is insensitive to rotational speed. Roller contact stress first decreases rapidly and then increases gradually with crown drop, indicating the existence of an optimal crown drop value. This optimal value first decreases and then increases with increasing straight segment length, with the optimal parameters determined as 9 μm (crown drop) and 4 mm (straight segment length). In practical applications, asymmetric loading on the two sides of the ratchet disc causes uneven roller contact distribution and stress concentration. Adjusting the roller centre position to balance the deformation of the ratchet disc and rod shoulder can effectively reduce contact stress, with the optimal position being approximately 48 mm (slightly offset from the load centre of 49 mm). This study provides valuable insights for the optimal design of SRTBs and no-back brakes. Full article

To address the challenges inherent in the transition flight control of QTR UAVs, this paper proposes an asynchronous tilt transition control framework that integrates NDIC with an ESO. First, a heterogeneous control allocation strategy is introduced to coordinate the rotors and aerodynamic surfaces, thereby maintaining consistent matching between control demands and actuator capabilities. Furthermore, compared with the synchronous tilt strategy, the proposed asynchronous tilt strategy improves pitch moment balance and forward acceleration capability, thereby enhancing robustness against CG variations and extending the achievable forward acceleration range. Finally, based on the asynchronous tilt transition strategy, a transition flight control method combining NDIC with ESO is presented to achieve precise transition control performance under the lumped disturbances. The simulation results demonstrate that the proposed tilt method achieves a safe and smooth transition, satisfies dynamic performance requirements, and exhibits strong robustness and high control accuracy. Full article

Balancing path-following accuracy and error convergence with graceful motion in steering control is challenging due to the competing nature of these requirements, especially across a range of operating speeds and conditions. This paper demonstrates that an integrated, multi-tiered steering controller considering slip in kinematic control, dynamic control, and steering actuator rate commands achieves accurate and graceful path following. Kinematic and dynamic models are adapted to include slip. A path-following kinematic controller is then derived using a continuous, time-varying, and speed-based variable-structure controller (VSC) to balance safe and graceful motion with robust error convergence. Yaw rate commands from the kinematic controller are nested in a backstepping slip–yaw dynamic tracking controller to generate steering rate commands. A high-gain observer (HGO) estimates the sideslip and yaw rate, which are used in sensor-based output feedback control. Stability analysis of the output feedback controller is provided, and peaking is resolved. The work focuses on lateral control alone so that the steering controller can be combined with other speed controllers. Field results demonstrate gracefulness and accuracy along complex paths in variable terrain, in different weather conditions, and with perturbations. Full article