Search Results (493)

This paper presents a nonlinear vertical dynamic model of an electromagnetic suspension (EMS) system in maglev trains regulated by a dual nonlinear saturation controller (DNSC) under simultaneous resonance ($\Omega \cong {\omega }_s,{\omega }_s\cong 2{\omega }_c$). The governing nonlinear differential equations of the system are addressed analytically utilizing the multiple time-scale technique (MTST), concentrating on resonance situations obtained from first-order approximations. The suggested controller incorporates two nonlinear saturation functions in the feedback and feedforward paths to improve system stability, decrease vibration levels, and enhance passenger comfort amidst external disturbances and parameter changes. The dynamic bifurcations caused by DNSC parameters are examined through phase portraits and time history diagrams. The goal of control is to minimize vibration amplitude through the implementation of a dual nonlinear saturation control law based on displacement and velocity feedback signals. A comparative analysis is performed on different controllers such as integral resonance control (IRC), positive position feedback (PPF), nonlinear integrated PPF (NIPPF), proportional integral derivative (PID), and DNSC to determine the best approach for vibration reduction in maglev trains. DNSC serves as an effective control approach designed to minimize vibrations and enhance the stability of suspension systems in maglev trains. Stability evaluation under concurrent resonance is conducted utilizing the Routh–Hurwitz criterion. MATLAB 18.2 numerical simulations (fourth-order Runge–Kutta) are employed to analyze time-history responses, the effects of system parameters, and the performance of controllers. The evaluation of all the derived solutions was conducted to verify the findings. Additionally, quadratic velocity feedback leads to intricate bifurcation dynamics. In the time domain, higher displacement and quadratic velocity feedback may destabilize the system, leading to shifts between periodic and chaotic movements. These results emphasize the substantial impact of DNSC on the dynamic performance of electromagnetic suspension systems. Frequency response, bifurcation, and time-domain evaluations demonstrate that the DNSC successfully reduces nonlinear oscillations and chaotic dynamics in the EMS system while attaining enhanced transient performance and resilience. Full article

This paper proposes a Gudermannian function-based proportional–integral–derivative (G-PID) controller to enhance the transient performance of automatic voltage regulator (AVR) systems operating under highly dynamic conditions. By embedding the smooth and bounded nonlinear mapping of the Gudermannian function into the classical PID structure, the proposed controller improves adaptability to large signal variations while effectively suppressing overshoot. The controller parameters are optimally tuned using the starfish optimization algorithm (SFOA), which provides a robust balance between exploration and exploitation in nonlinear search spaces. Simulation results demonstrate that the SFOA-optimized G-PID controller achieves superior transient performance, with a rise time of 0.0551 s, zero overshoot, and a settling time of 0.0830 s. Comparative evaluations confirm that the proposed approach outperforms widely used optimization algorithms (particle swarm optimization, grey wolf optimizer, success history-based adaptive differential evolution with linear population size, and Kirchhoff’s law algorithm) and advanced AVR control schemes, including fractional-order and higher-order PID-based designs. These results indicate that the proposed SFOA optimized G-PID controller offers a computationally efficient and structurally simple solution for high-performance voltage regulation in modern power systems. Full article

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

In the case of small disturbances in the power grid, virtual synchronous generators (VSGs) often exhibit active power steady-state errors and significant frequency overshoot, and it is difficult to balance the reduction of active power steady-state errors and the mitigation of frequency overshoot. This paper proposes an improved control method based on active power differential compensation (APDC). First, an active power differential compensation loop is introduced, effectively addressing the issues of active power steady-state deviation and frequency overshoot caused by fixed parameters in the traditional VSG. Secondly, by incorporating a fuzzy logic control (FLC) algorithm, an adaptive PID tuning strategy is proposed as a replacement for the traditional fixed virtual inertia; the PID parameters are dynamically adjusted in real time according to the power–angle deviation and its rate of change, thereby enhancing the small-disturbance dynamic performance of the VSG. Finally, MATLAB R2020b/Simulink simulations and StarSim hardware-in-the-loop simulations validate the effectiveness and accuracy of the proposed control strategy. Simulation results indicate that, compared to traditional control strategies, under peak regulation conditions, the frequency overshoot is reduced by approximately 4.4%, and the active power overshoot is reduced by approximately 5%; under frequency regulation conditions, the frequency overshoot is reduced by approximately 0.26%, and the power overshoot is reduced by approximately 12%. Full article

Open-channel irrigation systems often face constraints due to water supply uncertainty and insufficient gate control precision. This study proposes an integrated framework for canal water allocation and gate control that combines interval-based uncertainty analysis with intelligent optimization to address these challenges. First, we predict the inflow process using an Auto-Regressive Integrated Moving Average (ARIMA) model and quantify the range of water supply uncertainty through Maximum Likelihood Estimation (MLE). Based on these results, we formulate a bi-objective optimization model to minimize both main canal flow fluctuations and canal network seepage losses. We solve the model using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to obtain Pareto-optimal water allocation schemes under uncertain inflow conditions. This study also designs a Fuzzy Proportional–Integral–Derivative (Fuzzy PID) controller. We adaptively tune its parameters using the Particle Swarm Optimization (PSO) algorithm, which enhances the dynamic response and operational stability of open-channel gate control. We apply this framework to the Chahayang irrigation district. The results show that total canal seepage decreases by 1.21 × 10⁷ m³, accounting for 3.9% of the district’s annual water supply, and the irrigation cycle is shortened from 45 days to 40.54 days, improving efficiency by 9.91%. Compared with conventional PID control, the PSO-optimized Fuzzy PID controller reduces overshoot by 4.84%, and shortens regulation time by 39.51%. These findings indicate that the proposed method can significantly improve irrigation water allocation efficiency and gate control performance under uncertain and variable water supply conditions. Full article

With the rapid development of precision seeding technology, which plays a vital role in promoting large-scale cultivation, reducing seed loss, increasing crop yield, and improving land use efficiency, a maize precision seed metering control system based on KF-RTS fusion speed measurement has been developed to address the issues of ground wheel slippage and chain bounce in Chinese precision planters during high-speed operation, as well as the problems of speed measurement delay, motor control lag, and susceptibility to interference in existing electric drive seeders. The system comprises an STM32 master controller, a speed acquisition unit, a seed metering drive unit, and a human–machine interaction interface. By employing a multi-rate KF-RTS (Kalman Filter-Rauch-Tung-Striebel Smoother) fusion algorithm that integrates RTK-GNSS and accelerometer data, it significantly enhances the accuracy and real-time performance of forward speed measurement. A control strategy combining Kalman filtering with a fuzzy PID controller, optimized by a particle swarm algorithm, enables the control system to converge rapidly within 0.10 s with a steady-state error below 0.55%, achieving precise and stable regulation of the seed metering shaft speed. Field test results demonstrate that the qualified index of seed spacing reaches no less than 94.11% under the fusion speed measurement method. Compared to the RTK-GNSS speed measurement alone, the coefficient of variation in seed spacing is reduced by 3.85% to 6.93%, effectively resolving seed spacing deviations caused by speed measurement delays and improving seeding uniformity. Full article

This study presents the design and implementation of a real-time flight-path tracking control system for a quadrotor unmanned aerial vehicle (UAV) capable of accurately following a mobile ground target under dynamic and uncertain environmental conditions. The proposed framework integrates classical fixed-gain PID regulation executed on Pixhawk with its built-in adaptive mechanisms, namely autotuning, hover-throttle learning, and dynamic harmonic notch filtering, to enhance robustness under communication latency and disturbances. No machine learning PID tuning is used on Pixhawk; adaptive features are estimator based rather than ML based. The proposed system addresses critical challenges in trajectory tracking, including real-time delay compensation between the UAV and rover, external perturbations, and the requirement to maintain stable six-degree-of-freedom (DOF) control of altitude, yaw, pitch, and roll. A dynamic mathematical model, formulated using ordinary differential equations with embedded delay elements, is developed to emulate real-world flight behavior and validate control performance. Experimental evaluation demonstrates robust path-tracking accuracy, attitude stability, and responsiveness across diverse terrains and weather conditions, achieving a mean positional error below one meter and effective resilience against an 8.2 ms communication delay. Overall, this work establishes a scalable, computationally efficient, and high-precision control framework for UAV guidance and cooperative ground-target tracking, with potential applications in autonomous navigation, search-and-rescue operations, infrastructure inspection, and intelligent surveillance. The term “delay-aware” in this work refers to the explicit modeling of the measured 8.2 ms end-to-end delay and the use of Pixhawk’s estimator-based adaptive mechanisms, without any machine learning-based PID tuning. Full article

A modified Enzyme Action Optimizer (mEAO) is proposed to tune a Fractional-Order Proportional–Integral–Derivative (FOPID) controller for precise temperature regulation of a nonlinear continuous stirred tank reactor (CSTR). The nonlinear reactor model, adopted from a standard benchmark formulation widely used in CSTR control studies, is employed as the simulation reference. The tuning framework operates in a simulation-based manner, as the optimizer relies solely on the time-domain responses to evaluate a composite cost function combining overshoot, settling time, rise time, and steady-state error. Comparative simulations involving EAO, Starfish Optimization Algorithm (SFOA), Success History-based Adaptive Differential Evolution with Linear population size reduction (L-SHADE), and Particle Swarm Optimization (PSO) demonstrate that the proposed mEAO achieves the lowest cost value, the fastest convergence, and superior transient performance. Further comparisons with classical tuning methods, Rovira 2DOF-PID, Ziegler–Nichols PID, and Cohen–Coon PI, confirm improved tracking accuracy and smoother actuator behavior. Robustness analyses under varying set-points, feed-temperature disturbances, and measurement noise confirm stable temperature regulation without retuning. These findings demonstrate that the mEAO-based FOPID controller provides an efficient and reliable optimization framework for a nonlinear thermal-process control, with strong potential for future real-time and multi-reactor applications. Full article

Flowers are key reproductive structures for many plant species. They are essential for seed and fruit production, and their development is tightly regulated by hormonal and genetic networks. The homeodomain transcription factors HAT3 and ATHB4 are known regulators of adaxial identity and hormone response. We demonstrate that flowers of the hat3 athb4 double mutant emerge at wider divergence angles relative to the wild type, a phenotype reflecting modified phyllotaxy and regulated by low auxin conditions. In addition, hat3 athb4 flowers exhibit aberrant trichome patterning on their sepals associated with enhanced sensitivity to cytokinin (CK). Through RNA-seq analysis of hat3 athb4 inflorescences, we identify the misregulation of genes involved in auxin biosynthesis (YUCCAs), auxin transport (PID), and CK metabolism (CKXs) and transport (PUPs). These findings suggest that HAT3 and ATHB4 fine-tune the auxin/CK balance and coordinate critical pattern events during reproductive development, offering new insight into hormone-mediated regulation of floral patterning. Full article

The essence of microfluidics lies in its ability to manipulate fluids within compact and portable systems. However, existing pressure pumps rely on bulky external compressors and are costly. Open-source solutions are generally suited for passive microfluidic applications due to their slow settling times (1500–2500 s). The innovative pressure regulator developed uses two proportional solenoid valves and a built-in compression unit. The pressure regulation is ensured by a Proportional–Integral–Derivative (PID) controller. A comparative analysis is conducted between the developed regulator and a commercial regulator (Marsh Bellofram). Both regulators provide a comparable accuracy of about ±0.01 psi (±0.7 mbar) from the desired pressure. However, our regulator demonstrates a faster settling time (∼100 ms vs. ∼200 ms), which is particularly desirable for implementation in an active system, while offering a lower price (∼USD 250 vs. ∼USD 1000). We present a cost-effective, compact pressure pump that does not rely on bulky compressors. It delivers fast and precise pressure, even at low pressure, making it suitable for both active and passive microfluidic applications. This design improves access to pressure regulation in microfluidics for low-budget laboratories and limited infrastructure environments. Full article

This paper presents an analysis of the impact of the control architecture in a mobile robot on the quality of regulation in real systems. Comparative studies were conducted for successive stages of the implementation of architectural improvements, such as optimization of RTOS resource utilization, the use of hardware mechanisms (DMP, DMA) for sensor data acquisition, and the optimization of subordinate controllers. The results showed that the final control quality depends not only on the controller tuning but also on the efficient management of the hardware and software resources of the control system. Retuning the PID controller after architectural modifications enabled the achievement of a better control quality index (IAE). The novelty of this work lies in demonstrating, through experimental evaluation, that embedded control architecture has a measurable and systematic impact on regulation quality in real systems. The obtained results indicate a significant relationship between control architecture and control performance, representing an important step toward bridging the gap between simulation studies and real-world implementations in mobile robotics. Full article

The growing integration of renewable energy sources (RES) has fundamentally altered power system dynamics, reduced system inertia and challenged conventional Load Frequency Control (LFC) mechanisms. This study presents a comprehensive review of analytical and optimisation-based approaches for frequency regulation in low-inertia, renewable-rich power systems. It highlights the evolution from classical proportional–integral (PI/PID) controllers to advanced model-based, robust, adaptive, and intelligent control schemes, emphasising their relative strengths in handling uncertainty, variability, and multi-area coordination. Additionally, the paper examines Frequency-Constrained Unit Commitment (FCUC) frameworks that explicitly incorporate frequency stability metrics, such as Rate of Change of Frequency (RoCoF), frequency nadir, and inertia adequacy, into scheduling and dispatch. Through comparative analysis, the study identifies key performance trends, computational challenges, and practical trade-offs between analytical and optimisation paradigms. The paper concludes by outlining open research directions, including decentralised FCUC, multi-agent coordination, and AI-assisted control, aimed at achieving scalable and resilient frequency regulation. Overall, this review bridges the gap between control theory and operational optimisation, offering a unified perspective to guide the development of next-generation frequency control frameworks in modern power grids. Full article

Deploying deep reinforcement learning (DRL) in safety-critical nuclear control is limited less by raw performance than by the absence of licensable, audit-ready evidence. We introduce a Deterministic Assurance Framework (DTAF) that converts controller behavior into licensing-grade proof by combining the following: (i) deterministic licensing gates tied to formal safety and performance limits (e.g., Total Time Unsafe (TTU) = 0; bounded Transient Severity Score (TSS); and minimum Grid Load-Following Index (GLFI)); (ii) a portfolio of adversarial stress tests representative of off-nominal operation; and (iii) a traceability and explainability package that renders every evaluated action auditable. The DTAF is demonstrated on a high-fidelity pressurized-water-reactor (PWR) simulation model used as a software-in-the-loop testbed. Three governor architectures are evaluated under identical, fixed scenarios: a curriculum-trained Soft Actor–Critic (SAC) agent, and Differential-Evolution-optimized Proportional–Integral–Derivative (PID-DE) and Fuzzy-Logic (FLC-DE) Controllers. Performance is assessed deterministically via gate-aligned metrics—TTU, TSS, GLFI, cumulative control effort (CE_sum), valve-reversal count (V_rev), and speed overshoot (OS_ω). Across the adversarial portfolio, the SAC controller meets the predeclared licensing gates in single-run evaluations, whereas the strong conventional baselines violate gates in specific high-severity cases; where all methods remain within the safe envelope, the SAC delivers a higher GLFI and lower CE_sum, with fewer reversals and reduced overshoot. All licensing conclusions derive from deterministic single-run tests; a small, fixed-seed check (three seeds with descriptive intervals) is reported separately as non-licensing supplementary analysis. By producing transparent, reproducible artifacts, the DTAF offers a regulator-oriented pathway for qualifying DRL controllers in grid-interactive nuclear operations. Full article

In order to solve the problems of thermal management efficiency and temperature control accuracy in the passenger compartment of electric vehicles, the phase change thermal storage design concept and the model-free adaptive control method are applied to the thermal management temperature control system of the passenger compartment. Aiming at the characteristics of waste heat utilization of the whole vehicle and the preheating demand of the passenger compartment, an integrated vehicle thermal management model with a heat exchanger and storage function and an intelligent temperature control system scheme for the passenger compartment is designed. Aiming at the demand for adaptive control of the thermal management system of the passenger compartment of the whole vehicle, a composite strategy of PID control of compressor speed and model-free adaptive control of water pump speed are proposed, and the effect of the application of different control strategies under the demand for temperature control of the passenger compartment is compared and analyzed in simulation. The study shows that the phase change heat storage system and its model-free adaptive control in this paper are more stable, with smaller overshoot and high temperature regulation accuracy; the overshoot of PID control and fuzzy PID control is 14.17% and 8.58%, respectively, while the overshoot of model-free adaptive control is only 0.42%, which verifies the superiority of the designed thermal management system and the effectiveness of the control algorithm, and will effectively enhance the thermal comfort of the passenger compartment of electric vehicles. Full article

This study examines dual-area load–frequency control (LFC) in the context of significant renewable energy integration, energy storage systems (ESSs), and collective electric vehicle (EV) involvement. We propose a RBBMO-FO-FuzzyPID+PI(1+DD) hybrid controller in which fractional-order fuzzy regulation shapes the ACE, while an auxiliary PI(1+DD) path adds damping without steady-state penalty. Across ideal linear plants, 3% governor-rate constraints (GRC), and stressed conditions that include contract violations in Area-2, renewable power variations, and partial EV State of Charge (SoC 50–70%), EV participation yields systematic gains for all controller families, and the magnitude depends on the control architecture. Baseline methods improve by 15–25% with EVs, whereas advanced designs—especially the proposed controller—benefit by 25–45%, revealing a clear synergy between controller intelligence and EV flexibility. With EV support, the proposed controller limits frequency overshoot to 0.055 Hz (a 20–55% reduction versus peers), caps the nadir at −0.065 Hz (15–41% better undershoot), and attains 3.5–4.5 s settling (25–61% faster than competitors), while holding tie-line deviations within ±0.02 Hz. Optimization studies confirm the algorithmic advantage: RBBMO achieves 30% lower cost than BBOA and converges 25% faster; EV integration further reduces cost by 15% and speeds convergence by 12%. A strong correlation between optimization cost and closed-loop performance (r² ≈ 0.95) validates the tuning strategy. Collectively, the results establish the proposed hybrid controller with EV participation as a new benchmark for robust, system-wide frequency regulation in renewable-rich multi-area grids. Full article