Search Results (1,169)

The transient performance of sensorless control for interior permanent magnet synchronous motors (IPMSMs), based on back-electromotive force (back-EMF) estimation, is a critical factor in ensuring the high reliability of motor drive systems. Although rotor speed and position can be accurately estimated under steady-state conditions, estimation errors tend to increase during transient states such as acceleration, deceleration, and load torque variations. The enhancement of transient stability is closely related to the overshoot in the estimated position and speed errors. In this paper, the maximum overshoot of the estimated position and speed errors during transient operation is analyzed. Furthermore, compensation strategies are proposed to reduce the magnitude of these overshoots. The effectiveness of the proposed sensorless control method is validated through comparative analysis with existing approaches. Full article

Under complex operating conditions, the single-loop control structure of permanent magnet synchronous motors (PMSMs) suffers from various uncertain disturbances. Although extended state observers with high-gain designs have been widely adopted for disturbance rejection control due to their rapid convergence characteristics, they typically induce significant noise amplification and increased sensitivity to disturbances. To address this issue, this paper proposes a hybrid extended state observer-based control with adaptive switching strategy (AS-HyESO) for suppressing uncertain disturbances. In the AS-HyESO framework, matched disturbances from the control channel and unmatched disturbances from non-control channels are separately estimated using the HyESO, which are subsequently eliminated through the designed control law to ensure precise tracking of the speed reference input. Furthermore, the proposed observer incorporates an adaptive bandwidth switching mechanism that employs larger bandwidth during steady-state operation and reduced bandwidth during dynamic transients. This innovative approach achieves overshoot-free speed regulation while maintaining enhanced disturbance rejection capability, thereby effectively resolving the inherent conflict between dynamic response performance and anti-disturbance robustness. Experimental validation conducted on a 64 W PMSM dual-motor test platform demonstrates the superior effectiveness of the AS-HyESO, control strategy in practical applications. Full article

To enable safe cooperative flight of multi-UAV formations in urban 3-D airspace with wind-field disturbances, we develop an integrated planning-control framework.The planning layer uses an APF-guided RRT* with continuous collision prediction and explicit velocity/acceleration limits, and compensates wind online.The control layer adopts a dual-loop MA-AADRC-SMC design. An adaptive ESO estimates disturbances for feed-forward cancellation, and an SMC term improves robustness and tracking accuracy. By coupling the planned trajectory with speed-weighted repulsive fields, the framework coordinates path and attitude in closed loop, enabling collision-free and overshoot-free formation flight in wind and clutter. Simulations show higher tracking accuracy and better formation stability than ADRC, PID and SMC. A Lyapunov analysis proves uniform boundedness and asymptotic stability. The framework is scalable to applications such as disaster assessment and urban air transport. Full article

In the integrated hydro–wind–solar–storage system, the strong output fluctuations of wind and solar power, along with prominent system nonlinearity and time-varying characteristics, make it difficult for traditional PID controllers to achieve high-precision and robust dynamic control. This paper proposes a fuzzy fractional-order PID control strategy based on a multi-objective optimization algorithm, aiming to enhance the system’s frequency regulation, power balance, and disturbance rejection capabilities. The strategy combines the adaptive decision-making ability of fuzzy control with the high-degree-of-freedom tuning features of fractional-order PID. The multi-objective optimization algorithm AGE-MOEA-II is employed to jointly optimize five core parameters of the fuzzy fractional-order PID controller (K_p, K_i, K_d, λ, and μ), balancing multiple objectives such as system dynamic response speed, steady-state accuracy, suppression of wind–solar fluctuations, and hydropower regulation cost. Simulation results show that compared to traditional PID, single fractional-order PID, or fuzzy PID controllers, the proposed method significantly reduces system frequency deviation by 35.6%, decreases power overshoot by 42.1%, and improves renewable energy utilization by 17.3%. This provides an effective and adaptive solution for the stable operation of hydro–wind–solar–storage systems under uncertain and variable conditions. Full article

This paper presents an automatic oil sampling system designed for vertical cylindrical oil tanks on land, focusing primarily on the structural design and control optimization for oil level measurement and liquid sampling inside the tank. First, the key structure and control architecture of the automatic sampler are introduced, explaining the collaborative working principles of its components to ensure good stability in system structure and motion control. On this basis, an improved Sparrow Search Algorithm (CSSA) is proposed, which integrates the Coati Optimization Algorithm (COA) and the traditional Sparrow Search Algorithm (SSA). This algorithm is used to optimize the parameters of the Proportional–Integral–Derivative (PID) control system in the oil sampler, aiming to address issues such as response delay, large overshoot, and insufficient stability that commonly occur in traditional PID control under complex conditions. This method achieves consistent response behavior over time and adaptiveness in the control process by dynamically adjusting the PID parameters in real time. To verify the effectiveness of the proposed control strategy, system simulations were conducted in the MATLAB 2024B environment, and a physical experimental platform was built for testing. The simulation compares the CSSA-PID controller with traditional PID, COA-PID, and SSA-PID control methods. In addition, a load disturbance was introduced at 300 ms to perform anti-interference comparative simulations. The results show that under CSSA-PID control, the system response time was shortened by up to 112 ms, the convergence speed improved by 72.3%, the global optimization capability was significantly enhanced, and the anti-interference ability was stronger. In the actual tests, the average error was reduced by approximately 45.3%. These results indicate that CSSA-PID can significantly enhance the stability and response speed of the control system. The efficient control of the automatic oil sampler will greatly enhance the intelligence and efficiency of oil level detection in tanks and reduce labor costs, having significant implications for the development of the grain and oil storage industry. Full article

In closed Brayton cycle power generation systems, sudden load disturbances can induce a compressor surge in turbine–alternator–compressor systems, posing significant risks to dynamic stability and operational reliability. To address this challenge, this study proposes a PID control strategy optimized via a genetic algorithm. A high-fidelity dynamic model of the turbine–alternator–compressor system under closed Brayton cycle conditions is developed in Simulink, incorporating surge boundaries derived from performance maps. Control parameters are tuned using a weighted multi-objective fitness function that integrates overshoot, rise time, and the integral of absolute error. Simulation results demonstrate that the proposed control scheme markedly enhances system responsiveness—achieving approximately a 70% improvement in rotational speed regulation—and effectively maintains the operating point outside the surge region. The proposed framework provides a practical and robust approach for improving the dynamic stability and reliability of closed Brayton cycle power generation systems. Full article

Unmanned aerial manipulators (UAMs), composed of unmanned aerial vehicles (UAVs) and manipulators, have great application potential in aerial manipulation like precision inspection, disaster rescue, etc. However, strong dynamic coupling exists between UAVs and manipulators. In addition, UAMs meet external disturbances such as gusts of wind during movements. Also, the control performance metrics, such as tracking accuracy and control stability, are seriously affected. Therefore, a cooperative control method is developed for a UAM system with a UAV and a 2-degree-of-freedom manipulator. First, the Euler–Lagrange formulation is employed to study the UAM dynamics like inertial forces and coupling effects. Then, an integral sliding mode control (ISMC) method with an integral term is developed to enhance robustness and eliminate steady-state errors. Finally, the proposed ISMC method is validated through numerical simulations in Matlab R2024a, introducing comparative analyses with the Proportional–Integral–Derivative (PID) and SMC controllers. The simulation results and the comparative analyses validate the effectiveness of ISMC, showing its superiority over the PID and SMC controllers in handling dynamic coupling and external disturbances, where the overshoot of ISMC is reduced by an average of more than 90%. The ISMC method provides a high-performance control strategy to promote the practical application of UAMs in various aerial manipulation tasks and lays the foundation for further optimizing control methods for more complex UAM systems. Full article

In response to the challenges of reduced efficiency and compromised seeding accuracy in conventional soybean planters operating at high speeds, this research introduces a novel precision seeding system powered by an electric drive, aiming to enhance both operational reliability and sowing precision. The entire system is powered by the tractor’s 12 V battery and incorporates an OGWO-Fuzzy PID control strategy to regulate the seeding motor speed. To achieve faster and more accurate regulation of the seeding motor speed, this study employs a ternary phase-diagram-based strategy to optimize the weight allocation among the α, β, and δ wolves within the Grey Wolf Optimization (GWO) algorithm. Based on engineering requirements, the optimal weight ratio was determined to be 16:2:1. Simulation results indicate that the optimized OGWO-Fuzzy PID control strategy achieves a settling time of only 0.17 s with no overshoot. In bench tests, the OGWO-Fuzzy PID control strategy significantly outperformed both GWO-Fuzzy PID and Fuzzy PID in terms of seed-metering speed regulation time and accuracy. The average qualified seeding index reached 95.68%, demonstrating excellent seeding performance at medium-to-high operating speeds. This study provides a practical and technically robust approach to ensure seeding quality during medium–high-speed soybean planting Full article

This paper focuses on enhancing master cylinder pressure control in pressure-sensorless Electro-Hydraulic Brake (EHB) systems. A novel control strategy is developed, integrating a Piecewise Sliding Mode Controller (Piecewise-SMC) with an Extended Sliding Mode Observer (ESMO) based on a newly derived pressure–position–velocity model that accounts for rack position and velocity effects. To handle external disturbances and parameter uncertainties, the ESMO provides accurate pressure estimation. The nonlinear EHB model is approximated piecewise linearly to facilitate controller design. The proposed Piecewise-SMC regulates motor torque to achieve precise pressure tracking. Experimental validation under step-change braking conditions demonstrates that the Piecewise-SMC reduces response time by 31.8%, overshoot by 35.8%, and tracking root mean square error by 9.6% compared to traditional SMC, confirming its effectiveness and robustness for pressure-sensorless EHB applications. Full article

This paper presents a novel speed controller design for a brushless DC motor (BLDCM) operating under field-oriented control (FOC). The proposed speed controller is developed by integrating the zebra optimization algorithm (ZOA) with sliding mode theory (SMT). In this approach, the parameter ranges of the sliding mode dynamic trajectory control gain, exponential reaching gain, and constant speed reaching gain—three key components of the exponential reaching law-based sliding mode controller (ERLSMC)—are defined as the research space for the ZOA. The feedback speed error and its rate of change are used as features to calculate the fitness value. Subsequently, the fitness value computed by the algorithm is compared with the current best fitness value to determine the optimal position coordinates. These coordinates correspond to the optimal set of gain parameters for the sliding mode speed controller. During the operation of the BLDCM, these optimized parameters are applied to the controller in real time. This enables the system to adjust the three gain parameters dynamically under different operating conditions, thereby reducing the overshoot commonly induced by the ERLSMC. As a result, the speed response of the BLDCM drive system can more accurately and rapidly track the speed command. Therefore, the proposed control strategy is not only characterized by a small number of parameters and ease of tuning, but also does not require large datasets for training, making it highly practical and easy to implement. Finally, the proposed control strategy is simulated using Matlab/Simulink (2024b version) and applied to the BLDCM drive system for experimental testing. Its performance is compared against three types of sliding mode controllers employing different reaching laws: the constant speed reaching law, the exponential reaching law, and the exponential reaching law combined with extension theory (ET). Simulation and experimental results confirm that the proposed novel speed controller outperforms the other three sliding mode controllers based on different reaching laws, both in terms of speed command tracking and load regulation response. Full article

This study proposes a current control strategy to enhance the control stability of an interior permanent magnet synchronous motor (IPMSM) under transient conditions, such as rapid acceleration or deceleration in electric vehicle (EV) applications. Conventional current control methods provide optimal steady-state current references corresponding to torque commands using a lookup table (LUT)-based approach. However, during transitions between these reference points, particularly in the field-weakening region at high speeds, the voltage limit may be exceeded. When the voltage limit is exceeded, unstable overmodulation states may occur, degrading stability and resulting in overshoot of the inverter input current. Although ramp generators are commonly employed to interpolate between current references, a fixed ramp slope may fail to ensure a sufficient voltage margin during rapid transients. In this study, a method is proposed to dynamically adjust the rate of change of the d-axis current reference in real time based on the difference between the inverter output voltage and its voltage limit. By enabling timely field-weakening before rapid changes in speed or q-axis current, the proposed strategy maintains control stability within the voltage limit. The effectiveness of the proposed method was verified through simulations based on real vehicle driving profiles and dynamometer experiments using a 38 kW class IPMSM for a hybrid electric vehicle (HEV), demonstrating reduced input DC current overshoot, improved voltage stability, and enhanced torque tracking performance under high-speed transient conditions. Full article

Hybrid AC/DC microgrids (HADCMGs), which integrate renewable energy sources and battery storage systems, often face significant stability challenges due to their inherently low inertia and highly variable power inputs. To address these issues, this paper proposes a novel, robust composite controller based on backstepping fast terminal sliding mode control (BFTSMC). This controller is further enhanced with a virtual capacitor to emulate synthetic inertia and with a fractional power-based reaching law, which ensures smooth and finite-time convergence. Moreover, the proposed control strategy ensures the effective coordination of power sharing between AC and DC sub-grids through bidirectional converters, thereby maintaining system stability during rapid fluctuations in load or generation. To achieve optimal control performance under diverse and dynamic operating conditions, the controller gains are adaptively tuned using the marine predators algorithm (MPA), a nature-inspired metaheuristic optimization technique. Furthermore, the stability of the closed-loop system is rigorously established through control Lyapunov function analysis. Extensive simulation results conducted in the MATLAB/Simulink environment demonstrate that the proposed controller significantly outperforms conventional methods by eliminating steady-state error, reducing the settling time by up to 93.9%, and minimizing overshoot and undershoot. In addition, real-time performance is validated via processor-in-the-loop (PIL) testing, thereby confirming the controller’s practical feasibility and effectiveness in enhancing the resilience and efficiency of HADCMG operations. Full article

Discrete Silicon Carbide Metal-Oxide-Semiconductor Field-Effect Transistors (SiC MOSFETs) are characterized by their lower parasitic parameters and single-chip design, enabling them to achieve even faster switching speeds. However, the rapid rate of change in voltage (dv/dt) and current (di/dt) can lead to overshoot and oscillation in both voltage and current, ultimately limiting the performance of high-frequency operations. To address this issue, this paper presents a high-switching-frequency motor controller that utilizes discrete SiC MOSFETs. To achieve a high switching frequency for the controller while minimizing current oscillation and voltage overshoot, a novel electronic system architecture is proposed. Additionally, a passive driving circuit is designed to suppress gate oscillation without the need for additional control circuits. A new printed circuit board (PCB) laminate stack featuring low parasitic inductance, high current conduction capacity, and efficient heat dissipation is also developed using advanced wiring technology and a specialized heat dissipation structure. Compared to traditional methods, the proposed circuit and bus design features a simpler structure, a higher power density, and achieves a 13% reduction in current overshoot, along with a 15.7% decrease in switching loss. The silicon carbide (SiC) controller developed from this research has successfully undergone double-pulse and power testing. The results indicate that the designed controller can operate reliably over extended periods at a switching frequency of 50 kHz, achieving a maximum efficiency of 98.2% and a power density of 9 kW/kg (10 kW/L). The switching frequency and quality density achieved by the controller have not been observed in previous studies. This controller is suitable for use in the development of new energy electrical systems. Full article

The increasing demand for high-performance power converters for electric vehicle (EV) applications places a significant emphasis on developing effective and robust control strategies for DC-DC converter operation. This paper deals with the development, simulation, and experimental validation of an adaptive Lyapunov-type Nonlinear Sliding Mode Control (L-SMC) strategy for a DC–DC boost converter, addressing significant uncertainties caused by large variations in system parameters (R and L) and ensuring the tracking of a voltage reference. The proposed control strategy employs the Lyapunov stability theory to build an adaptive law to update the parameters of the sliding surface so the system can achieve global asymptotic stability in the presence of uncertainty in inductance, capacitance, load resistance, and input voltage. The nonlinear sliding manifold is also considered, which contributes to a more robust and faster convergence in the controller. In addition, a logic optimization technique was implemented that minimizes switching (chattering) operations significantly, and as a result of this, increases ease of implementation. The proposed L-SMC is validated through both simulation and experimental tests under various conditions, including abrupt increases in input voltage and load disturbances. Simulation results demonstrate that, whether under nominal parameters (R = 320 Ω, L = 2.7 mH) or with parameter variations, the voltage overshoot in all cases remains below 0.5%, while the steady-state error stays under 0.4 V except during the startup, which is a transitional phase lasting a very short time. The current responds smoothly to voltage reference and parameter variations, with very insignificant chattering and overshoot. The current remains stable and constant, with a noticeable presence of a peak with each change in the reference voltage, accompanied by relatively small chattering. The simulation and experimental results demonstrate that adaptive L-SMC achieves accurate voltage regulation, a rapid transient response, and reduces chattering, and the simulation and experimental testing show that the proposed controller has a significantly lower steady-state error, which ensures precise and stable voltage regulation with time. Additionally, the system converges faster for the proposed controller at conversion and is stabilized quickly to the adaptation reference state after the drastic and dynamic change in either the input voltage or load, thus minimizing the settling time. The proposed control approach also contributes to saving energy for the application at hand, all in consideration of minimizing losses. Full article

During the winding process of a coil winding machine, excessive tension can cause wire deformation, over-stretching, or breakage, while insufficient tension may lead to slackness, accumulation, and wrinkling. The magnitude of winding tension directly affects product quality and operational performance. This paper addresses the challenges of inadequate constant-tension control accuracy and excessive fluctuations in the unwind system of winding machines under disturbances. By integrating specific operational scenarios, a fuzzy PID control strategy suitable for actual production environments is designed. Based on an established coupling model relating unwind tension to roll diameter, unwind speed, and moment of inertia, conventional PID and fuzzy PID control simulation models are developed in the MATLAB/Simulink platform. These models evaluate both control strategies under noise disturbances and abrupt tension changes. A systematic comparative analysis examines the dynamic response characteristics, steady-state accuracy, and anti-interference capabilities. Results demonstrate that the fuzzy PID control, integrated with actual winding machine conditions, effectively suppresses tension fluctuations induced by nonlinear disturbances, reducing adjustment time by 3 s compared to conventional PID control. This indicates that the production-condition-integrated fuzzy PID control exhibits smaller overshoot, enhanced robustness, and superior dynamic response and better meets precision requirements for wire winding tension control. Full article