Controllability metrics based on system Gramians have been widely adopted to provide quantitative measures of the degree of controllability (DoC) and the disturbance rejection capability (DoDR) of dynamical systems. While steady-state Gramian formulations offer closed-form tractability, they are not applicable when rigid-body modes are present, as the associated poles at the origin cause the conventional Gramians to diverge. This paper presents a novel steady-state DoDR metric for linear time-invariant systems with a rigid-body mode. By block-diagonalizing the dynamics through a similarity transformation and analyzing the asymptotic behavior of the Gramian matrices, we derive an exact closed-form expression for the steady-state DoDR. The resulting formulation is numerically stable and enables systematic evaluation of disturbance-rejection capability even in the presence of a rigid-body mode. The proposed metric is validated using a mass–spring–damper chain model, where its effectiveness is demonstrated in actuator placement problems. The results show that the metric not only remains computationally well-posed but also provides physically meaningful interpretations consistent with modal characteristics. This study establishes a foundation for extending disturbance-rejection metrics to systems with multiple rigid-body modes, thereby broadening the applicability of Gramian-based controllability analysis.

This paper investigates the problem of practical prescribed-time trajectory tracking consensus for higher-order heterogeneous multi-agent systems (MASs) with unknown time-varying control gains and non-vanishing uncertainties, while also taking external disturbances into account. A directed graph is employed to characterize the communication topology. By introducing a time-varying scaling function and adopting an adaptive backstepping design, a distributed controller is developed that achieves practical prescribed-time trajectory tracking consensus of heterogeneous MASs, while avoiding unbounded control gains and preserving the continuity of control inputs. Furthermore, to optimize the use of communication resources, an event-triggered mechanism is incorporated to reduce the update frequency of controllers. Finally, numerical simulations are carried out to verify the effectiveness of the proposed method.

Continuous estimation of joint angles based on surface electromyography (sEMG) signals is a promising method for naturally controlling prosthetic limbs and assistive devices. However, conventional methods based on neural networks have limitations such as long training times and calibration burdens. This study investigates the use of an echo state network (ESN), which enables fast training, to estimate wrist joint angles from sEMG. Five participants mimicked the motion of a 1-degree-of-freedom robotic arm by flexing and extending their wrist, while sEMG signals from the wrist flexor and extensor muscles and the robotic arm’s angle were recorded. The ESN was trained to take two sEMG channels as input and the robotic joint angle as output. High-accuracy estimation with a median coefficient of determination R2 = 0.835 was achieved for representative ESN parameters. Additionally, the effects of the reservoir size, spectral radius, and time constant on estimation accuracy were evaluated using data from a single participant. Furthermore, online estimation of joint angles based on sEMG signals enabled successful control of the robotic arm. These results suggest that sEMG-based ESN estimation offers fast, accurate joint control and could be useful for prosthetics and fundamental studies on body perception.

Piezoelectric synthetic jet actuators typically struggle to generate high-speed jets at low driving frequencies due to the coupling effect between jet frequency and jet intensity. This limitation to some extent restricts their application in flow control within low-speed flow fields. To address this issue, this study presents two methods of signal modulation. The effects of driving signal modulation on dual synthetic jet actuator (DSJA) characteristics were experimentally investigated. A laser displacement meter was used to measure the central point amplitude of the piezoelectric diaphragm, while the velocity at the exit of the DSJAs was measured using a hot-wire anemometer. The effects of signal modulation on the amplitude of the piezoelectric diaphragm, the maximum jet velocity, and the frequency domain characteristics of the dual synthetic jet (DSJ) were thoroughly analyzed. Experimental results demonstrate that driving signal modulation can enhance jet velocity at relatively low driving frequencies. The modulated DSJ exhibits low-frequency characteristics, rendering it suitable for flow control applications that require low-frequency jets. Furthermore, the coupling effect between jet frequency and jet intensity in the piezoelectric DSJA is significantly alleviated. Starting from the vibration displacement of the piezoelectric transducer (PZT), this paper systematically elaborates on the corresponding relationship between PZT displacement and the peak velocity at the jet outlet, and the “low-frequency and high-momentum jet generation method based on signal modulation” proposed herein is expected to break through the momentum–frequency coupling limitation of traditional piezoelectric dual-stenosis jet actuators (DSJAs) and enhance their application potential in low-speed flow control.

The increasing trend towards electrification in transportation highlights the potential for electric ships and the demand for safe, rapid charging systems. Underwater capacitive power transfer (UCPT) is considered a suitable solution due to its high power density potential. This article presents research on and optimization of UCPT for shore-to-ship charging in freshwater environments. It proposes a design for an insulation coupler and explores the influence of parasitic capacitance in the environment. This study demonstrates how the ship and shore impact the coupler’s coupling coefficient and mutual capacitance, thereby affecting the power and efficiency. Through theoretical calculations and finite element analysis, a kW-level UCPT coupler is designed. Experimental verification under different cases confirms the efficiency and constant current output characteristics, with superior performance observed when the coupler is positioned further away from the ship or shore. This study showcases the potential of UCPT to provide reliable and efficient power supply for electric ships, while emphasizing the importance of considering environmental factors and parasitic effects in system design and operation. These findings contribute to advancing UCPT technology and offer insights for further optimization to enhance practical applicability.

The high-speed maglev train employs linear induction motors for propulsion and incorporates electromagnetic suspension for levitation. Ensuring the stability of the suspension control is imperative for the effective operation of the maglev train at high speeds, necessitating precise calculation of the suspension force. The commonly employed models, while simple in structure, lack the accuracy needed for high-precision suspension control. This paper conducts finite element analysis to simulate the static suspension conditions of high-speed maglev trains and refines the magnetic force calculation model using the obtained data to minimize computational inaccuracies arising from factors like magnetoresistance effects. The revised model is particularly well-suited for scenarios with significant air gaps and elevated currents, showcasing practical value for engineering applications.

The Magnetic Suspension Balance System (MSBS) serves as a core apparatus for interference-free aerodynamic testing in wind tunnels, where its high-precision levitation control performance directly determines the reliability of aerodynamic force measurements. This paper addresses the strong coupling issues induced by rigid-body motion in the MSBS vertical suspension system and proposes a decoupling control framework integrating classical decoupling methods with geometric feature transformation. First, a nonlinear dynamic model of the six-degree-of-freedom MSBS is established. Through linearization analysis of the vertical suspension system, the intrinsic mechanism of displacement-pitch coupling is revealed. Building upon this foundation, a state feedback decoupling controller is designed to achieve decoupling among dynamic channels. Simulation results demonstrate favorable control performance under ideal linear conditions. To further overcome its dependency on model parameters, a decoupling strategy based on geometric feature transformation is proposed, which significantly enhances system robustness in nonlinear operating conditions through state-space reconstruction. Finally, the effectiveness of the proposed method in vertical suspension control is validated through both numerical simulations and a physical MSBS experimental platform.

In the field of life sciences, delay effects are often modeled with two compartments that do not model any particular organ. In this paper the use of this double counterpart model is investigated in Fixed-Point Iteration-based (FPI) Control, which was introduced in 2009 as an adaptive extension to the Computed Torque Control method. This controller is particularly sensitive to delays and measurement noise due to its iterative nature. It was recognized that, besides modeling the delay effect, this signal tackling also provided the controller with some noise filtering ability; the formerly accumulated effects of noise filtering and formally delayed sampling were avoided. This smeared delay has a noticeable effect even slightly later in time, making the adaptive method based on it more robust. This assumption was investigated both on a simulation and experimental basis.

While networked multi-agent systems have been widely explored, the challenges introduced by underactuation still impede safety-critical cooperative control of multiple underactuated manipulators. This paper introduces a distributed framework for end-effector formation control and obstacle avoidance in planar n-link manipulators with a passive first joint and active remaining joints—termed PAn−1 manipulators. By exploiting the integrability of each PAn−1 manipulator’s second-order nonholonomic constraint, we reformulate the dynamics into a cascaded structure and derive a reduced-order model driven solely by active joint velocities. Building on this reduced-order model, we design safety-critical distributed formation control laws for the reduced-order dynamics, which serve as the manipulators’ desired active joint velocities. Then, we employ the backstepping method to obtain control inputs for the full-order dynamics. To guarantee safety, we treat backstepping tracking errors as matched disturbances and address them within a robust control barrier function framework. Numerical simulations and comparative studies confirm the effectiveness of the proposed approach.

Under no-load conditions, the wet clutch of vehicles generates drag torque across a wide speed range, which increases power loss in the transmission system and significantly impacts its efficiency and reliability. To address the clutch drag issue over a wide speed range, this study first establishes a low-speed drag torque model that simultaneously considers the viscous friction effects in both the complete oil film region and the oil film rupture zone of the friction pair clearance. Subsequently, by solving the fluid-structure interaction dynamics model of the friction plates, the collision force between high-speed friction pairs and the resulting friction torque are determined, forming a method for calculating high-speed collision-induced drag torque. Building on this, a unified drag torque model for wet clutches across a wide speed range is developed, integrating both viscous and collision-induced drag torques. The validity of the wide-speed-range drag torque model is verified through experiments. The results indicate that as oil temperature and friction pair clearance increase, the drag torque decreases and the rotational speed corresponding to the peak drag torque is reduced, while the onset of collision phenomena occurs earlier. Conversely, with an increase in oil supply flow rate, the drag torque rises and the rotational speed corresponding to the peak drag torque increases, but the onset of collision phenomena is delayed. Finally, with the optimization objectives of minimizing the peak drag torque in the low-speed range and the total drag torque at the maximum speed in the high-speed range, an optimization design model for the surface grooves of the clutch friction plates is constructed. An optimized groove pattern is obtained, and its effectiveness in suppressing drag torque across a wide speed range is experimentally validated.