Search Results (151)

This study presents a comprehensive experimental investigation of a 2.2 kW brushless DC (BLDC) motor integrated with a three-shaft planetary gearbox, focusing on overall energy efficiency, battery state of charge (SOC) estimation, and real-time speed control under variable load conditions. In the first stage, the gearbox transmission ratio was experimentally verified to establish the kinematic relationship between the BLDC motor and the eddy current dynamometer shafts. In the second stage, the motor was operated in open loop mode at fixed reference speeds while variable load torques ranging from 1 to 7 N.m were applied using an AVL dynamometer. Electrical voltage, current, and rotational speed were measured in real time through precision transducers and a data acquisition interface, enabling computation of overall efficiency and SOC via the Coulomb counting method. The open loop results demonstrated that maximum efficiency occurred in the intermediate-to-high-speed region (2000 to 2800 rpm) and at higher load torques (5 to 7 N.m) while locking the third gearbox shaft produced negligible parasitic losses. In the third stage, a proportional–integral–derivative (PID) controller was implemented in closed loop configuration to regulate motor speed under the same variable load scenarios. The closed loop operation improved the overall efficiency by approximately 8–20 percentage points within the effective operating range of 1600–2500 rpm, reduced speed droop, and ensured precise tracking with minimal overshoot and steady-state error. The proposed methodology provides an integrated experimental framework for evaluating the dynamic performance, energy efficiency, and battery utilization of BLDC motor planetary gearbox systems, offering valuable insights for electric vehicle and hybrid electric vehicle (HEV) drive applications. Full article

Triboelectric nanogenerators (TENGs) offer intrinsically high open-circuit voltages in the kilovolt range; however, conventional diode rectifier interfaces clamp the voltage prematurely, restricting access to the high-energy portion of the mechanical cycle and preventing delivery-centric control. This work develops a unified physical basis for contact–separation (CS) TENGs by confirming the consistency of the canonical $V_{oc}$–$C_s$ relation with a dual-capacitor energy model and analytically establishing that both terminal voltage and storable electrostatic energy peak near maximum plate separation. Leveraging this insight, a self-powered gas-discharge-tube (GDT) rectifier bridge is devised to replace two diodes and autonomously trigger conduction exclusively in the high-voltage window without auxiliary bias. An inductive buffer regulates the current slew rate and reduces $I^{2}R$ loss, while the proposed topology realizes two decoupled power rails from a single CS-TENG, enabling simultaneous sensing/processing and actuation. A low-power microcontroller is powered from one rail through an energy-harvesting module and executes an operator-based nonlinear controller to regulate the actuator-side rail via a MOSFET–resistor path. Experimental results demonstrate earlier and higher-efficiency energy transfer compared with a diode-bridge baseline, robust dual-rail decoupling under dynamic loading, and accurate closed-loop voltage tracking with negligible computational and energy overhead. These findings confirm the practicality of the proposed self-powered architecture and highlight the feasibility of integrating operator-theoretic control into TENG-driven rectifier interfaces, advancing delivery-oriented power extraction from high-voltage TENG sources. Full article

This paper presents a comprehensive and hybrid control framework for the real-time regulation of drillstring systems that are subject to complex nonlinear dynamics, including torsional stick–slip oscillations, coupled axial vibrations, and intricate bit–rock interactions. The model also accounts for parametric uncertainties and external disturbances typically encountered during rotary drilling operations. A robust sliding mode controller (SMC) is designed for inner-loop regulation to ensure accurate state tracking and strong disturbance rejection. This is complemented by an outer-loop model predictive control (MPC) scheme, which optimizes control trajectories over a finite horizon while balancing performance objectives such as rate of penetration (ROP) and torque smoothness, and respecting actuator and operational constraints. To address the challenges of partial observability and noise-corrupted measurements, an Ensemble Kalman Filter (EnKF) is incorporated to provide real-time estimation of both internal states and external disturbances. Simulation studies conducted under realistic operating scenarios show that the hybrid MPC–SMC framework substantially enhances drilling performance. The controller effectively suppresses stick–slip oscillations, provides smoother and more stable bit-speed behavior, and improves the consistency of ROP compared with both open-loop operation and SMC alone. The integrated architecture maintains robust performance despite uncertainties in model parameters and downhole disturbances, demonstrating strong potential for deployment in intelligent and automated drilling systems operating under dynamic and uncertain conditions. Full article

The increasing demand for reliable DC fast-charging stations in electric vehicle (EV) infrastructure necessitates efficient fault detection mechanisms to ensure operational stability and user safety. This paper will present the development of a diagnostic method for identifying open-circuit faults and short-circuit faults in DC charging stations by leveraging Total Harmonic Distortion (THD) analysis combined with a Second-Order Generalized Integrator (SOGI). The proposed approach uses the THD method to detect anomalies in the current and voltage waveforms, while the Frequency Locked Loop (FLL) serves to track the frequency of the grid and keep the SOGI tuned to it, and SOGI-FLL provides the rectifier with the capability of tracking the frequency, amplitude, voltage, and phase of the grid and monitoring these parameters of the grid. The ability to measure the THD is the kernel of the detection of faults. Detailed simulation confirms the method’s high sensitivity and robustness in detecting open/short circuit faults with minimal false positives. This technique offers a cost-effective, non-invasive diagnostic solution suitable for modern DC charging systems, contributing to improved reliability and efficiency of EV charging infrastructure. Full article

Thepaper presents an efficient model predictive control framework formulated as a linear programming problem to control a servo drive with model uncertainty considerations from the viewpoint of the control performance. The model predictive framework is used to adopt $L_1$-type cost functions using absolute tracking errors, providing computational efficiency and enabling real-time implementation. A key contribution is the deployment of this approach on real hardware in a hardware-in-the-loop setting, supported by fully open-source code for Simulink Coder and C environments, verifying the solution scheme in real time. Experimental validation on a servo drive demonstrates the system’s tolerance for parameter uncertainties with slight performance degradation, resulting in an up to 18% increase in the considered control quality measure, between nominal parameters’ values and the worst configuration. The proposed linear programming approach enables constraint handling imposed on control signals and supports the arbitrary choice of prediction horizons and sampling intervals. The paper also includes a comprehensive derivation of the control law, controller implementation details, and stepwise experimental results showcasing the impact of uncertainties on control performance. This work and the attached code enable the authors to easily reproduce the proposed approach and extend it in their applications. Full article

This work presents an open-source simulation framework designed to extend the capabilities of the VRX environment for developing and validating control strategies for surface robotic vehicles. The platform features a custom monohull, kayak-type USV with four thrusters in differential configuration, represented with a complete graphical mockup consistent with its physical design and modeled with realistic dynamics and sensor integration. A thrust mapping function was calibrated using manufacturer data, and the vehicle’s behavior was characterized using a simplified Fossen model with parameters identified via Least Squares estimation. Multiple motion controllers, including velocity, position, trajectory tracking, and path guidance, were implemented and evaluated in a variety of wave and wind scenarios designed to test the full vehicle dynamics and closed-loop behavior. In addition to extending the VRX simulator, this work introduces a new USV model, a calibrated thrust response, and a set of model-based controllers validated in high-fidelity marine conditions. The resulting framework constitutes a reproducible and extensible resource for the marine robotics community, with direct applications in robotic education, perception, and advanced control systems. Full article

A fully automated, buoy-based deployment sensor system is being developed to acquire high-quality water column data, and requires a controller to accurately position an array of sensors at various depths. The sensor system will be potentially deployed under rough ocean conditions. Depth is measured by a pressure sensor and adjusted through a rotating drum powered by a stepper motor. The proposed controller uses a model predictive control algorithm, a type of optimal control that predicts system response to optimize control actions used to track a desired variable-depth, setpoint profile. The profile is calculated to ensure smooth motion of the system, preventing motor malfunction. A simplified system model was created and used to simulate an open-loop test and system response. Constraints were applied to the control actions to match the practical limitations of the stepper motor. The simulated results show successful tracking of both a shallow and deep profile. At this stage of testing, the effects of ocean currents are considered by using a simple disturbance that provides the effect of ocean currents. A practical prototype that can implement the model predictive controller was tested on the physical buoy-based system with good control performance. Full article

Dual-loop control enhances the bandwidth of piezo-actuated nanopositioning systems via inner-loop state feedback controller suppressing lightly damped resonance and outer-loop tracking controller eliminating hysteresis nonlinearity. However, the traditional framework based on the continuous-time low-order model suffers from control performance degradation. To address this issue, this paper proposes a dual-loop control framework based on the discrete-time high-order model. In this framework, the discrete-time linear quadratic regulator extends theoretical bandwidth through simultaneous parameter optimization, and direct discrete implementation of the high-order state feedback controller and an integrator improves control precision by reducing model mismatch and controller discretization errors. Experiments are conducted on a custom-designed piezo-actuated system. Experimental frequency response of the system with the developed framework agrees well with the theoretical one, and the actual bandwidth is improved to 8248 Hz, which is better than 3920 Hz (continuous-time high-order model) and 6610 Hz (discrete-time low-order model), and exceeds open-loop resonant frequency 6352 Hz. Step response and trajectory tracking tests also demonstrate the effectiveness of the developed framework. Full article

The development of efficient strategies for optimizing and controlling nonlinear bioprocesses remains a significant challenge due to their complex dynamics and sensitivity to operating conditions. This work addresses the problem by proposing a two-step methodology applied to a laboratory-scale fed-batch bioethanol process. The first step employs a dynamic optimization approach based on Fourier parameterization and orthonormal polynomials, which generates smooth and continuous substrate-feed profiles using only three parameters instead of the ten required by piecewise approaches. The second step introduces a controller formulated through basic linear algebra operations, which ensures accurate trajectory tracking of the optimized state variables. Simulation results demonstrate a $3.65\%$ increase in ethanol concentration at the end of the process, together with an accumulated tracking error of only $0.0189$ under nominal conditions. In addition, the closed-loop strategy outperforms open-loop implementation when the initial conditions deviate from their nominal values. These findings highlight that the proposed methodology reduces mathematical complexity and computational effort while producing continuous control profiles suitable for practical application. The combination of optimization and algebraic control thus provides a promising alternative for improving the efficiency of bioethanol-production processes. Full article

In order to solve the problem that it is difficult to take into account the performance constraints between the core functions of insulation, current flow and arc extinguishing of high-voltage vacuum circuit breakers at the same time, this paper proposes a flexible control strategy for the motor operating mechanism of high-voltage vacuum circuit breakers. The relationship between the rotation angle of the motor and the linear displacement of the moving contact of the circuit breaker is analyzed, and the ideal dynamic curve is planned. The motor drive control device is designed, and the phase-shifted full-bridge circuit is used as the boost converter. The voltage and current double closed-loop sliding mode control strategy is used to simulate and verify the realization of multi-stage and stable boost. The experimental platform is built and the experiment is carried out. The results show that under the voltage conditions of 180 V and 150 V, the control range of closing speed and opening speed is increased by 31.7% and 25.9% respectively, and the speed tracking error is reduced by 51.2%. It is verified that the flexible control strategy can meet the ideal action curve of the operating mechanism, realize the precise control of the opening and closing process and expand the control range. The research provides a theoretical basis for the flexible control strategy of the high-voltage vacuum circuit breaker operating mechanism, and provides new ideas for the intelligent operation technology of power transmission and transformation projects. Full article

Slope stability monitoring in open-pit mining remains a critical challenge for geological hazard prevention, where conventional qualitative methods often fail to address dynamic risks. This study proposes an integrated framework combining empirical modeling (slope classification, hazard assessment, and safety ratings) with multi-source real-time monitoring (synthetic aperture radar, machine vision, and Global Navigation Satellite System) to achieve quantitative stability analysis. The method establishes an initial stability baseline through mechanical modeling (Bishop/Morgenstern–Price methods, safety factors: 1.35–1.75 across five mine zones) and dynamically refines it via 3D terrain displacement tracking (0.02 m to 0.16 m average cumulative displacement, 1 h sampling). Key innovations include the following: (1) a convex hull-displacement dual-criterion algorithm for automated sensitive zone identification, reducing computational costs by ~40%; (2) Ku-band synthetic aperture radar subsurface imaging coupled with a Global Navigation Satellite System and vision for centimeter-scale 3D modeling; and (3) a closed-loop feedback mechanism between empirical and real-time data. Field validation at a 140 m high phosphate mine slope demonstrated robust performance under extreme conditions. The framework advances slope risk management by enabling proactive, data-driven decision-making while maintaining compliance with safety standards. Full article

Energy management for hybrid electric commercial vehicles, involving continuous power output and discrete gear shifting, constitutes a typical mixed-integer programming (MIP) problem, presenting significant challenges for real-time performance and computational efficiency. To address this, this paper proposes a physics-informed neural network-optimized model predictive control (PINN-MPC) strategy. On one hand, this strategy simultaneously optimizes continuous and discrete states within the MPC framework to achieve the integrated objectives of minimizing fuel consumption, tracking speed, and managing battery state-of-charge (SOC). On the other hand, to overcome the prohibitively long solving time of the MIP-MPC, a physics-informed neural network (PINN) optimizer is designed. This optimizer employs the soft-argmax function to handle discrete gear variables and embeds system dynamics constraints using an augmented Lagrangian approach. Validated via hardware-in-the-loop (HIL) testing under two distinct real-world driving cycles, the results demonstrate that, compared to the open-source solver BONMIN, PINN-MPC significantly reduces computation time—dramatically decreasing the average solving time from approximately 10 s to about 5 ms—without sacrificing the combined vehicle dynamic and economic performance. Full article

The properties of Hardware-in-the-Loop (HIL) for the development of controllers, together with electronic emulation of physical process by Digital Twins (DT) significantly enhance the optimization of design and implementation in nonlinear control applications. The study emphasizes the use of the Raspberry Pi (RBP), a low-cost and portable electronic board for two interrelated goals: (a) the Electronic Control Unit (ECU-RBP) implementing a Lyapunov-based Controller (LBC) for nonlinear trajectory tracking of P3DX wheeled robots, and (b) the Digital Twin (DT-RPB) emulating the real robot behavior, which is remotely connected to the control unit. ECU-RBP, DT-RBP and real robot are connected as nodes within the same wireless network, enhancing interaction between the three physical elements. The development process is supported by the Matlab/Simulink environment and the associated packages for the specified electronic board. Following testing of the real robot from the ECU-RBP in an open loop, the model is identified and integrated into the DT-RBP to replicate its functionality. The LBC solution, which has also been validated through simulation, is implemented in the ECU-RBP to examine the closed-loop control according to the HIL strategy. Finally, the study evaluates the effectiveness of the HIL approach by comparing the results obtained from the application of the LBC, as implemented in the ECU-RBP to both the real robot and its DT. Full article

This study presents a quasi-static optimization framework for the pressure-based control of a multi-segment soft continuum manipulator. The proposed method circumvents traditional curvature and length-based modeling by directly identifying the quasi-static input–output relationship between actuator pressures and the 6-DoF end-effector pose. Experimental data were collected using a high-frequency electromagnetic tracking system under monotonic pressurization to minimize hysteresis effects. Transfer functions were identified for each coordinate–actuator pair using the System Identification Toolbox in MATLAB, and optimal actuator pressures were computed analytically by solving a constrained quadratic program via a manual active-set method. The resulting control strategy achieved sub-millimeter positioning error while minimizing the number of actuators engaged. The approach is computationally efficient, sensor-minimal, and fully implementable in open-loop settings. Despite certain limitations due to sensor nonlinearity and actuator hysteresis, the method provides a robust foundation for feedforward control and the real-time deployment of soft robots in quasi-static tasks. Full article

The atmospheric boundary layer (ABL) and tropopause play critical roles in weather formation and climate change. This study initially focuses on the ABL height (ABLH), tropopause height (TPH), and temperature (TPT) retrieved from the integrated radio occultation (RO) profiles from FY-3E, FY-3F, and FY-3G satellites during September 2022 to August 2024. All three FY-3 series satellites are equipped with the RO payload of Global Navigation Satellite System Radio Occultation Sounder-II (GNOS-II), which includes open-loop tracking RO observations from the BeiDou navigation satellite system (BDS) and the Global Positioning System (GPS). The wavelet covariance transform method was used to determine the ABL top, and the temperature lapse rate was applied to judge the tropopause. Results show that the maximum ABL detection rate of FY-3/GNOS-II RO can reach up to 76% in the subtropical eastern Pacific, southern hemisphere Atlantic, and eastern Indian Ocean. The ABLH is highly consistent with the collocated radiosonde observations and presents distinct seasonal variations. The TPH retrieved from FY-3/GNOS-II RO profiles is in agreement with the radiosonde-derived TPH, and both TPH and TPT from RO profiles display well-defined spatial structures. From 45°S to 45°N and south of 55°S, the annual cycle of the TPT is negatively correlated with the TPH. This study substantiates the promising performance of FY-3/GNOS-II RO measurements in observing the ABL and tropopause, which can be incorporated into the weather and climate systems. Full article