Search Results (69)

In this paper, a composite control framework integrating feedback linearization, an extended state observer, and an adaptive fractional-order sliding-mode controller is presented for autonomous underwater vehicles operating under uncertain hydrodynamics and external disturbances. The proposed algorithm, named adaptive fractional-order sliding-mode control with extended state observer, aims to enhance trajectory-tracking accuracy, disturbance rejection, and robustness against model uncertainties beyond what is offered by conventional active disturbance rejection control and integer-order sliding-mode control. First, a fractional-order sliding surface with an extended state observer is introduced to estimate and compensate lumped disturbances, where the fractional operator provides intrinsic filtering and memory effects to reduce chattering. Second, an adaptive exponential reaching law with smooth switching is formulated to overcome the trade-off between convergence speed and chattering, and a Levant differentiator is employed for sensorless velocity estimation. Finally, the uniform ultimate boundedness of the closed-loop system is proved via Lyapunov stability theory. Comparative simulation studies on step, sinusoidal, and circular trajectories under external disturbances, measurement noise, and 50% parametric uncertainties demonstrate that the proposed controller achieves zero overshoot, suppresses position fluctuations by 97%, and reduces root mean square tracking errors by 38–70% relative to conventional methods, confirming its superior performance. Full article

This paper establishes a theoretical framework for treating communication quality as a navigable resource in long-endurance unmanned aerial vehicle (UAV) control under stochastic degradation. We prove that a hierarchical architecture integrating communication-aware model predictive control (MPC) achieves $\epsilon$-optimality with respect to the intractable stochastic dynamic programming formulation while maintaining exponential stability guarantees under switched system dynamics governed by continuous-time Markov chains. Three primary theoretical contributions were made: (1) A stochastic optimality theorem is given showing that sigmoid penalty function approximation yields bounded suboptimality of $\eta \le 0.12$ under mild ergodicity conditions; (2) a formal stability result for mode switching based on hysteresis was established using multiple Lyapunov functions, and it showed exponentially fast convergence with a decay rate of $\lambda \ge 0.23$; and (3) bifurcation analysis showed that there is a critical time threshold of 72 h at which thermal-induced gyro-drift in the GPS sensor causes a transition in navigation error dynamics from linear to catastrophic nonlinear growth. The validation through 2430 Monte Carlo missions over 54,686 flight hours resulted in an average increase in endurance by 243% (18.2 days versus 5.3 days), while keeping CEP at approximately 8.7 m and achieving 82% mission success under extreme communication degradation ($q_{comm}<0.3$). The statistical results confirm a very strong positive relationship between the Resilience Quotient (RQ) and the length of successful missions ($R^2=0.89$, $p<0.001$), supporting the theoretical model with empirical evidence. Full article

Accurate measurement of spool displacement is essential for achieving high-performance closed-loop control and condition monitoring in hydraulic systems. However, conventional inductive displacement transducers typically rely on sinusoidal excitation and complex analog signal conditioning circuits, resulting in higher hardware cost and limited system integration. To address these issues, this paper proposes a software-based demodulation method for a differential inductive displacement transducer under symmetric complementary square-wave excitation. First, the structure and operating principle of the transducer are analyzed, and an electromagnetic model describing the nonlinear relationship between coil inductance and the position of the inductive core is established, along with its electrical characteristics. Then, a simplified signal acquisition circuit is designed to enable digital extraction of inductance variations using a microprocessor. Compared with conventional approaches, the proposed scheme significantly reduces hardware complexity and cost while being more suitable for embedded system integration. A simulation model is developed to analyze the inductance variation and to validate the proposed hardware circuit. In addition, a test platform is built to conduct static calibration and dynamic response experiments. The experimental results show that the proposed method achieves a linearity of 2.36% and a sensitivity of 155.6 mV/mm and exhibits strong robustness against switching noise. Finally, application tests in a hydraulic valve system demonstrate that the proposed transducer and demodulation method enable accurate and stable spool position measurement, providing a low-cost and easily integrated solution for embedded hydraulic control systems. Full article

Nowadays, sensorless control of permanent magnet synchronous linear motors (PMLSM) is widely utilized in industrial applications due to its inherent cost and spatial advantages. However, existing sensorless control methods for PMLMs face insufficient observation accuracy of states and disturbances and poor variable-speed trajectory tracking. To address these issues, this paper proposes a sensorless control method combining multi-observer coordinated perception and robust adaptive control. Firstly, a sliding mode observer based on an improved saturation switching function is designed, which suppresses current noise with a low-pass filter to achieve unbiased estimation of back electromotive force (EMF). Secondly, an extended state observer with back-EMF as input is constructed to synchronously observe disturbances such as the mover speed, position, and thrust ripple of linear machine. Then, a robust adaptive controller is designed to compensate for system uncertainty via an adaptive law, forming closed-loop control with SVPWM. Compared with the traditional methods, the proposed multi-observer coordinated perception scheme can significantly enhance the observation accuracy of the mover speed, position, and lumped disturbances, and the robust adaptive controller can effectively improve the variable-speed trajectory, tracking performance under system uncertainties. Finally, the simulation results have confirmed the effectiveness of the proposed method in accurately observing and tracking speed and position, providing a feasible solution for high-precision sensorless control of PMLSM. Full article

In multirotor unmanned aerial vehicle (UAV) GNSS/INS integrated navigation systems, a single filter such as the extended Kalman filter (EKF) or the error-state extended Kalman filter (ESKF) is commonly adopted. However, both methods have inherent performance limitations. The EKF suffers from significant linearization errors in highly nonlinear flight scenarios, leading to degraded estimation accuracy. Although ESKF achieves higher precision during steady flight, its model assumptions may no longer strictly hold during aggressive maneuvers, causing performance degradation in complex flight missions. To address the limitations of using a single filter, this study proposes a dynamic filter selection strategy under the interaction multi-filter (IMF) framework. The approach builds on the interactive multiple model (IMM) method and establishes a cooperative mechanism between EKF and ESKF. By computing the filter likelihoods at each time step and updating the probability switching matrix, the framework adaptively selects the optimal filter based on the current flight conditions. Simulation results demonstrate that the proposed IMF-based strategy effectively avoids the performance bottlenecks of individual filters. In highly nonlinear environments, it reduces linearization errors and suppresses divergence trends; compared with traditional ESKF, the proposed algorithm 3D RMSE is reduced by 57.2%, compared with the adaptive robust EKF (AREKF), the proposed approach reduces positioning errors by up to 21.3%. The results confirm that IMF-based adaptive switching between EKF and ESKF yields a robust, high-precision solution for UAV navigation in complex operational scenarios. Full article

Mechanical control systems structure, derived from Euler–Lagrange dynamics, is directly tied to physically meaningful coordinates such as joint angles, positions, and velocities. This work investigates when a mechanical control system can be transformed, without changing its physical coordinates, into an equivalent form whose Christoffel symbols vanish, thereby eliminating the configuration-dependent coupling terms in the inertia matrix. We establish a necessary and sufficient condition under which a mechanical control system can, via pure mechanical feedback, be transformed into an equivalent system with zero Christoffel symbols. For three representative examples of mechanical systems, we extensively discuss the global stabilization problem. These case studies demonstrate, respectively, global linearization; local linearization with singularities that can be globalized through an appropriate switching control strategy; and partial linearization, where eliminating the Christoffel symbols enables the design of a globally stabilizing nonlinear controller for a system that is not fully feedback linearizable. These findings demonstrate that achieving vanishing Christoffel symbols, while preserving physically meaningful coordinates, provides a powerful and broadly applicable tool for addressing complex control problems. Full article

This paper proposed an end-effector (EE)-driven whole-body tele-operation framework based on linear and angular motion decomposition. The proposed EE-driven tele-operation method enables intuitive control of a mobile manipulator using only EE commands, unlike conventional systems where the mobile base and manipulator are controlled by separate interfaces that directly map user inputs to each component. The proposed linear and angular motion decomposition mechanism significantly reduces the computational burden compared to conventional optimization-based whole-body control algorithms. Also, EE position is evaluated relative to the manipulator’s WS, and control authority is automatically switched between the manipulator and mobile base to ensure feasible motion. A blending-based transition strategy is introduced to prevent discontinuous switching and chattering near WS boundaries. Simulation results confirm that the method accurately reproduces tele-operation commands while maintaining stable whole-body coordination, demonstrating smooth transitions between control authorities and effective WS regulation. Simulation results confirm that the method accurately reproduces tele-operation commands while maintaining stable whole-body coordination, verifying the feasibility of the proposed approach. Future work will focus on experimental validation using a physical mobile manipulator. Full article

We present a utilization of the magnon Kerr effect to generate nonreciprocal genuine microwave entanglement in a hybrid system consisting of a yttrium iron garnet (YIG) sphere and three microwave cavities. Based on the quantum Langevin theory and linearization method under the condition of strong magnon driving, the system dynamics and covariance evolution are deduced and then applied to determinate the quantum correlations. It is found that three microwave cavities entangle with each other at the steady state. The basic root is that the Kerr nonlinearity can not only induce the enhanced parametric amplification of magnon but also cause the magnon frequency shift. Naturally, when the direction of the externally applied bias magnetic field is changed, switching of the magnon Kerr coefficient from positive to negative occurs and nonreciprocal tripartite entanglement among three microwave photons can be achieved. This may provide a fundamental resource for practical applications in quantum information processing and quantum networks. Full article

The article introduces the Guarantee-Based Bandwidth Traffic Engineering Queue (GB(Bw)-TEQ) and Guarantee-Based Utilization Traffic Engineering Queue (GB(U)-TEQ) models for queue management on router interfaces. These models implement the principles of Traffic Engineering Queues and support both DiffServ and IntServ. Their novelty lies in the ability to provide guarantees either for the bandwidth allocated to a class queue or for its utilization coefficient. Such guarantees stabilize and control the average queue length, positively affecting key Quality of Service (QoS) indicators, particularly average delay and packet loss probability. The unreserved portion of the interface bandwidth is allocated among queues in proportion to their classes. Therefore, the higher-priority queues have lower utilization, while lower-priority queues operate with higher utilization, which is consistent with DiffServ principles. The models are formulated as a mixed-integer linear programming problem with an optimality criterion and a system of constraints. Computational experiments confirmed the operability and efficiency of GB(Bw)-TEQ and GB(U)-TEQ compared to the known analogue CB-TEQ model, which does not provide service-level guarantees. The results demonstrate that the proposed models achieve the stated guarantees and enable differentiated service without blocking the lowest-class queues. These solutions can be applied to automate queue management in IP/MPLS switches and routers as well as in software-defined networks. Full article

This paper addresses the problem of optimal stabilization for stochastic dynamical systems characterized by Markov switches and concentration points of jumps, which is a scenario not adequately covered by classical stability conditions. Unlike traditional approaches requiring a strictly positive minimal interval between jumps, we allow jump moments to accumulate at a finite point. Utilizing Lyapunov function methods, we derive sufficient conditions for exponential stability in the mean square and asymptotic stability in probability. We provide explicit constructions of Lyapunov functions adapted to scenarios with jump concentration points and develop conditions under which these functions ensure system stability. For linear stochastic differential equations, the stabilization problem is further simplified to solving a system of Riccati-type matrix equations. This work provides essential theoretical foundations and practical methodologies for stabilizing complex stochastic systems that feature concentration points, expanding the applicability of optimal control theory. Full article

This paper addresses the issues of sensor failures and actuator faults in mining tracked mobile vehicles (TMVs) operating in harsh environments by proposing a global fixed-time fault-tolerant control strategy based on a hierarchical unknown input observer structure. First, a kinematic and dynamic model of the TMV is established considering side slip and track slip, and its linear parameter-varying (LPV) model is constructed through parameter-dependent linearization. Then, a distributed structure consisting of four collaborating low-dimensional observers is designed, including a state observer, a disturbance observer, a position sensor fault observer, and a wheel speed sensor fault observer, and the fixed-time convergence of the closed-loop system is proven. Additionally, by equivalently treating actuator faults as power losses, an observer capable of identifying and compensating for motor efficiency losses is designed. Finally, an adaptive fault-tolerant control law is proposed by combining nominal control, disturbance compensation, and sliding mode switching terms, achieving global fixed-time stability and fault tolerance. Experimental results demonstrate that the proposed control system maintains excellent trajectory tracking performance even in the presence of sensor faults and actuator power losses, with tracking errors less than 0.1 m. Full article

Conventional multi-object tracking approaches frequently exhibit performance degradation in marine radar (MR) imagery due to complex environmental challenges. To overcome these limitations, this paper proposes ShipMOT, an innovative multi-object tracking framework specifically engineered for robust maritime target tracking. The novel architecture features three principal innovations: (1) A dedicated CNN-based ship detector optimized for radar imaging characteristics; (2) A novel Nonlinear State Augmentation (NSA) filter that mathematically models ship motion patterns through nonlinear state space augmentation, achieving a 41.2% increase in trajectory prediction accuracy compared to conventional linear models; (3) A dual-criteria Bounding Box Similarity Index (BBSI) that integrates geometric shape correlation and centroid alignment metrics, demonstrating a 26.7% improvement in tracking stability under congested scenarios. For a comprehensive evaluation, a specialized benchmark dataset (Radar-Track) is constructed, containing 4816 annotated radar images with scenario diversity metrics, including non-uniform motion patterns (12.7% of total instances), high-density clusters (>15 objects/frame), and multi-node trajectory intersections. Experimental results demonstrate ShipMOT’s superior performance with state-of-the-art metrics of 79.01% HOTA and 88.58% MOTA, while maintaining real-time processing at 32.36 fps. Comparative analyses reveal significant advantages: 34.1% fewer ID switches than IoU-based methods and 28.9% lower positional drift compared to Kalman filter implementations. These advancements establish ShipMOT as a transformative solution for intelligent maritime surveillance systems, with demonstrated potential in ship traffic management and collision avoidance systems. Full article

Force-projecting bilateral control is an effective method for enhancing the positioning rigidity and stability of teleoperation systems equipped with compliant pneumatically driven followers. However, friction in the pneumatic actuation mechanism has caused a deterioration in force reproducibility between the leader and follower. To solve this problem, this study proposes a practical method of nonlinear friction compensation in force-projecting bilateral control to improve the force reproducibility. The proposed method generates two friction compensation forces: one based on the target admittance velocity from the leader and the other based on the actual velocity of the follower. These forces are seamlessly switched according to the dynamic state of the system to compensate for the follower’s driving force. This enables improved force reproducibility in any motion states of the system while maintaining the advantage of force-projecting bilateral control, which eliminates the need for external force measurement on the follower side. Experiments were conducted using a 1-DOF bilateral control device consisting of an electric linear motor and a pneumatic cylinder, including free motion and contact operations with two types of environments, demonstrating the effectiveness of the proposed method. Full article

This article discusses the innovative application of a Cartesian robot manipulator with acoustic feedback for calibration and precise positioning of a string-excitation element in investigating stringed instruments. It describes an experiment in which an acoustic guitar string is automatically excited with different guitar picks. The robot’s end effector positioning system utilizes limit switches, acting as a mechanical sensor, which provides feedback to the linear actuators that are equipped with stepper motors. The authors detail the research challenges they faced and propose a positioning algorithm that makes use of a microphone as an acoustic sensor, improving the calibration of the end effector’s position. Full article

Hydrogen peroxide (H₂O₂) plays a crucial role in cell signaling in response to physiological and environmental perturbations. H₂O₂ can oxidize typical 2-Cys peroxiredoxin (PRX) first into a sulfenic acid, which resolves into a disulfide that can be reduced by thioredoxin (TRX)/TRX reductase (TR). At high levels, H₂O₂ can also hyperoxidize sulfenylated PRX into a sulfinic acid that can be reduced by sulfiredoxin (SRX). Therefore, PRX, TRX, TR, and SRX (abbreviated as PTRS system here) constitute the coupled sulfenylation and sulfinylation cycle (CSSC), where certain oxidized PRX and TRX forms also function as redox signaling intermediates. Earlier studies have revealed that the PTRS system is capable of rich signaling dynamics, including linearity, ultrasensitivity/switch-like response, nonmonotonicity, circadian oscillation, and possibly, bistability. However, the origins of ultrasensitivity, which is fundamentally required for redox signal amplification, have not been adequately characterized, and their roles in enabling complex nonlinear dynamics of the PTRS system remain to be determined. Through in-depth mathematical modeling analyses, here we revealed multiple sources of ultrasensitivity that are intrinsic to the CSSC, including zero-order kinetic cycles, multistep H₂O₂ signaling, and a mechanism arising from diminished H₂O₂ removal at high PRX hyperoxidation state. The CSSC, structurally a positive feedback loop, is capable of bistability under certain parameter conditions, which requires embedding multiple sources of ultrasensitivity identified. Forming a negative feedback loop with cytosolic SRX as previously observed in energetically active cells, the mitochondrial PTRS system (where PRX3 is expressed) can produce sustained circadian oscillations through supercritical Hopf bifurcations. In conclusion, our study provided novel quantitative insights into the dynamical complexity of the PTRS system and improved appreciation of intracellular redox signaling. Full article