Search Results (125)

The increasing incorporation of renewable energy into power grids has significantly reduced system inertia and damping, posing challenges to frequency stability and power quality. To address this issue, an adaptive virtual synchronous generator (VSG) control strategy is proposed, which dynamically adjusts virtual inertia and damping in response to real-time frequency variations. Virtual inertia is modulated by an exponential function according to the frequency variation rate, while damping is regulated via a hyperbolic tangent function, enabling minor support during small disturbances and robust compensation during severe events. Control parameters are optimized using an enhanced particle swarm optimization (PSO) algorithm based on a composite performance index that accounts for frequency deviation, overshoot, settling time, and power tracking error. Simulation results in MATLAB/Simulink under step changes, load fluctuations, and single-phase faults demonstrate that the proposed method reduces the frequency deviation by over 26.15% compared to fixed-parameter and threshold-based adaptive VSG methods, effectively suppresses power overshoot, and eliminates secondary oscillations. The proposed approach significantly enhances grid transient stability and demonstrates strong potential for application in power systems with high levels of renewable energy integration. Full article

Hydraulic excavators operate in harsh environments where direct measurement of actuator chamber pressures and boom displacement is often unreliable or infeasible. This study presents a novel control strategy that estimates actuator chamber pressures from work port pressures using differential equations, eliminating the need for direct pressure or position sensors. A fuzzy logic-based proportional–derivative (PD) controller is developed to mitigate boom oscillations, particularly under high-inertia load conditions and variable operator inputs. The controller dynamically adjusts gains through fuzzy logic-based gain scheduling, enhancing adaptability across a wide range of operating conditions. The proposed method addresses the limitations of classical PID controllers, which struggle with the nonlinearities, parameter uncertainties, and instability introduced by counterbalance valves and pressure-compensated proportional valves. Experimental data is used to design fuzzy rules and membership functions, ensuring robust performance. Simulation and full-scale experimental validation demonstrate that the fuzzy PD controller significantly reduces pressure overshoot (by 23% during extension and 32% during retraction) and decreases settling time (by 31.23% and 28%, respectively) compared to conventional systems. Frequency-domain stability analysis confirms exponential stability and improved damping characteristics. The proposed control scheme enhances system reliability and safety, making it ideal for excavators operating in remote or rugged terrains where conventional sensor-based systems may fail. This approach is generalizable and does not require modifications to the existing hydraulic circuit, offering a practical and scalable solution for modern hydraulic machinery. Full article

Aiming at the problem that the whole row of reciprocating seedling picking mechanism is prone to inertial impacts during operation due to its excessive mass, causing seedling damage and positioning errors, this study builds a motion control system with a PLC controller as the core and proposes a composite motion control strategy based on planned S-curve acceleration and deceleration and fuzzy PID to achieve rapid response, precise positioning, and smooth operation of the seedling picking mechanism. By establishing the objective function and constraint conditions and taking into account the dynamic change of the seedling picking displacement, the S-curve acceleration and deceleration control algorithm is planned in six and seven stages to meet the requirements of a smooth transition of the speed and continuous change of the acceleration curve of the seedling picking mechanism during movement. A fuzzy PID positioning control system is designed, the control system transfer function is constructed, and fuzzy rules are formulated to dynamically compensate for the error and its rate of change to meet the requirements of fast response and no overshoot oscillation of the positioning control system. The speed and acceleration of the seedling picking mechanism under the six-segment and seven-segment S-curve acceleration and deceleration motion control conditions were simulated using MATLAB2024a simulation software and compared with the trapezoidal acceleration and deceleration motion control. The planned S-curve acceleration and deceleration control algorithm has a more stable control effect on the seedling picking mechanism when it operates under the conditions of the dynamic change of the displacement, and it meets the design requirements of seedling picking efficiency. The positioning control system was modeled and simulated using the Simulink simulation platform. When KP = 15, KI = 3, and KD = 1, the whole-row seedling picking control system ran stably, responded quickly, and had no overshoot. Compared with the PID control system with fixed parameters, the fuzzy PID control system reduced the time consumption in the rising stage by 24.5% and shortened the overall stabilization process by 17.6%. The zero overshoot characteristic was ensured, and the response speed was faster. When a disturbance signal is added, the overshoot of the fuzzy PID control system is reduced by 2.4%, and the response speed is increased by 6.8% compared with the fixed-parameter PID control system. The dynamic response rate and anti-disturbance performance are better than those of the fixed-parameter PID control system. A bench comparison test was carried out. The results showed that the S-curve acceleration and deceleration motion control algorithm reduced the average mass loss rate of seedlings by 46.19% compared with the trapezoidal acceleration and deceleration motion control algorithm, and the seedling picking efficiency met the design requirements. Fuzzy PID positioning control was used, and the maximum displacement error of the end effector during seedling picking was −1.4 mm, and the average relative error rate was 0.22%, which met the positioning accuracy requirements of the end effector in the X-axis direction and verified the stability and accuracy of the designed control system. The designed control system was tested in the field, and the average comprehensive success rate of seedling picking and throwing reached 96.2%, which verified the feasibility and practicality of the control system. Full article

In this paper, a modification of the classical PID controller scheme for position control is presented. The resulting controller incorporates an exponential trajectory that smoothly guides the system towards the setpoint and a hybrid mechanism to dynamically reset the exponential signal, allowing an adaptive response to discontinuous reference signals. This combination leverages the benefits of exponential trajectories to reduce overshoot and transient oscillations, while the hybrid system ensures robust performance over a wide range of operating scenarios. Among the advantages of the proposed approach, two stand out: (1) significant improvements in energy savings can be achieved in some cases, and (2) closed-loop system performance can be improved even considering poorly tuned PIDs. Full article

Micronewton thrusters have a wide range of applications in the aerospace field, and the accuracy of micronewton thrust measurement is directly affected by environmental vibration. The cantilever beam is the core part of the microthrust measurement system, and its stability directly affects the accuracy of thrust calibration. Aiming at the problems of the cantilever beam oscillating during the change in thrust and being susceptible to the impulse vibration of the ground, the interference suppression scheme of the microthrust measurement system based on the fuzzy PID of particle swarm optimization is investigated. And an interference suppression algorithm of the microthrust system based on the adaptive Kalman displacement expectancy estimation algorithm and the fuzzy PID of particle swarm optimization is designed. An adaptive Kalman displacement expectation estimation algorithm and a particle swarm optimization fuzzy PID microthrust system interference suppression algorithm are designed. The results show that the proposed algorithm can effectively track the thrust signal and suppress the influence of external vibration interference for the mN-level thrust change, control the overshooting amount within 10%, shorten the stabilization time to within 0.2 s, reduce the impulse oscillation to 22% of the original, reduce the steady-state error, and have a strong suppression effect on the oscillation phenomenon of the system, with better control accuracy and stability, and provide a good condition for the thrust calibration. Full article

Focused on the contradiction between the steady-state error of active power and the dynamic oscillation caused by the virtual damping characteristics of the virtual synchronous generator (VSG) under disturbances during grid-connected operation, this article proposes an adaptive virtual inertia regulation and compensation method (PFFCVSG_AJ) based on an active power differential feedforward compensation strategy (PFFCVSG). Firstly, this article presents the working and control principles of VSG, analyzing its control mechanisms through a small-signal model. Models for VSG’s active power, reactive power, and virtual impedance components are established, with particular focus on the impact of the damping coefficient on active power regulation. Based on the PFFCVSG, an adaptive virtual inertia adjustment method is introduced to resolve the inherent inertia deficiency in PFFCVSG control, the influence of the moment of inertia on PFFCVSG is theoretically analyzed, and a dynamic adjustment mechanism for moment of inertia is developed based on the rate of change in frequency (RoCoF). Finally, simulation validation using MATLAB/Simulink (MathWorks, R2022b, Natick, MA, USA) demonstrates that the proposed PFFCVSG_AJ strategy effectively eliminates active power steady-state deviation, suppresses active power dynamic oscillation, and mitigates the frequency overshoot issue prevalent in traditional PFFCVSG. Experimental verification is conducted via a TMS320F28378DPTPS-based control platform, confirming the algorithm’s effectiveness under sudden load variations, and that the power quality of the power grid is not affected under the premise of efficient grid connection. Full article

With the increasing penetration of renewable energy, doubly-fed variable speed pumped storage units (DFVSPSUs) are playing an increasingly critical role in grid frequency regulation. However, traditional PI control struggles to address the control challenges posed by the strong nonlinearity of the units and abrupt operational condition changes. This paper proposes an improved β-incremental generalized predictive controller (β-GPC), which achieves precise rotor-side current control through instantaneous linearization combined with parameter identification featuring a forgetting factor. Simulation results demonstrate that under different power command step changes, the traditional PI controller requires up to approximately 0.48 s to reach a steady state while exhibiting a certain degree of oscillations. In contrast, the enhanced β-GPC controller can stabilize the unit in just 0.2 s without any overshoot or subsequent oscillations. It is evident that the proposed controller delivers a superior regulation performance, characterized by a shorter settling time, reduced overshoot, and minimized oscillations. Full article

The conventional-speed Sliding Mode Controller (SMC) for ship PM propulsion motors, which employs exponential reaching laws and linear sliding surface functions, demonstrates susceptibility to oscillatory phenomena. To solve this problem, this paper proposes a saturation adaptive nonlinear integral sliding mode controller (SANI-SMC) which combines a nonlinear integral sliding surface function with an adaptive saturation gain reaching rate. The nonlinear integral sliding surface function improves the system responsiveness, and then enhances the stability and robustness of the system. The adaptive saturation gain reaching rate not only mitigates the chattering effect induced by the sign function in traditional exponential reaching rates, but also weakens the underlying oscillations. This approach effectively solves the overshoot problem inherent in traditional PI controllers, and has better anti-interference ability under sudden load variations. Finally, the proposed controller is experimentally verified based on an electric propulsion semi-physical experimental platform consisting of Rapid Control Prototyping (RCP), and compared with a Proportional–Integral (PI) controller and an SMC. Moreover, the integral absolute error (IAE), integral time-weighted absolute error (ITAE), and integral of the square value (ISV) metrics are calculated for the PI controller, SMC, and SANI-SMC based on experimental data collection. The results demonstrate that the SANI-SMC exhibits superior stability and robustness compared to both the PI controller and SMC. Full article

Load frequency control (LFC) is essential for maintaining the stability of power systems subjected to load variations and renewable energy disturbances. This paper presents two advanced Proportional–Integral–Derivative–Acceleration (PIDA) controllers optimized using hybrid techniques: Teaching–Learning-Based Optimization combined with transit search (PIDA-TLBO-TS) and with Exponential Distribution Optimization (PIDA-TLBO-EDO). The proposed hybrid optimization approaches integrate global exploration and local exploitation capabilities to achieve near-global optimal solutions with superior convergence performance. Three test scenarios are studied to assess controller performance: a load disturbance in area 1, a disturbance in area 2, and a disturbance introduced by stochastic wave energy input. In each case, the proposed hybrid controllers are benchmarked against the conventional TLBO-based PIDA controller available in the literature. Simulation results confirm that the hybrid PIDA-TLBO-EDO controller consistently outperforms the alternatives in terms of peak-to-peak oscillation, root mean square (RMS) error, settling time, and overshoot. Specifically, it achieves a 0.49% to 15% reduction in peak-to-peak oscillations and a 2.5% to 18% improvement in RMS error, along with a 10.27% improvement in tie-line power deviation and a 15.38% reduction in frequency oscillations under wave energy disturbances. Moreover, the PIDA structure, enhanced by its acceleration term, contributes to better dynamic response compared to traditional controller designs. The results highlight the effectiveness and robustness of the proposed hybrid controllers in damping oscillations and maintaining system stability, particularly in modern power systems with high levels of renewable energy integration. This study emphasizes the potential of combining complementary optimization techniques to enhance LFC system performance under diverse and challenging conditions. Full article

Aiming to solve the difficult problem of the miniaturization of servo valves, this paper designs a subminiature two-dimensional (2D) electro-hydraulic servo valve, which realizes the integration of the pilot stage and the power stage and significantly improves the work-to-weight ratio. Meanwhile, a high-power-density brushless DC motor (BLDC) is adopted as the electro-mechanical converter to further reduce the volume and mass. Firstly, the structure and working principle of the two-dimensional (2D) servo valve are described, and the mathematical model of the electro-mechanical converter is established. Aiming at the special working condition of the electro-mechanical converter with high-frequency oscillation at a small turning angle, this paper designs a position–current double closed-loop PID control algorithm based on the framework of the vector control algorithm (FOC). At the same time, the current feedforward compensation technique is included to cope with the high-frequency nonlinear disturbance problem of the electro-mechanical converter. The stability conditions of the electro-mechanical converter and the main valve were established based on the Routh–Hurwitz criterion, and the effects of the control algorithm of the electro-mechanical converter and the main parameters of the main valve on the stability of the system were analyzed. The dynamic and static characteristics of the 2D valve were simulated and analyzed by establishing a joint simulation model in Matlab/Simulink and AMESim. The prototype was fabricated, and the experimental bench was built; the size of the experimental prototype was 31.7 mm × 29.3 mm × 31 mm, and its mass was 73 g. Under a system pressure of 7 MPa, the flow rate of this valve was 5 L/min; the hysteresis loop of the spool-displacement input–output curve was 4.8%, and the linearity was 2.54%, which indicated that it had the ability of high-precision control and that it was suitable for the precision fluid system. The step response time was 7.5 ms, with no overshoot; the frequency response amplitude bandwidth was about 90 Hz (−3 dB); the phase bandwidth was about 95 Hz (−90°); and the dynamic characterization experiment showed that it had a fast response characteristic, which can satisfy the demand of high-frequency and high-dynamic working conditions. Full article

This paper investigates the fractional-order characteristics of the stator and rotor windings of a synchronous generator. Utilizing mechanism-based modeling methodology, it pioneers the derivation of the fractional-order voltage equations for a synchronous generator across both the three-phase stationary coordinate system (A, B, C) and the synchronous rotating coordinate system (d, q, 0). Through simplifying assumptions and rigorous derivations, a 2 + α (α ∈ (0, 2)) order synchronous generator model is formulated. This paper develops a digital simulation model of a fractional-order single-machine infinite bus system and analyzes the impact of the order α on the synchronous generator system’s dynamic performance through disturbance simulation experiments. Experimental results demonstrate that under conventional disturbances, increasing α from 0.8 to 1.2 reduces the system oscillation period and frequency while enhancing mechanical oscillation suppression, whereas decreasing α to 0.8 accelerates the generator terminal voltage response, lowers electromagnetic power overshoot, and improves excitation control effectiveness. Full article

With the continuous growth of global energy demand and the increasing severity of environmental issues, photovoltaic (PV) power generation, as a clean and renewable energy source, has attracted widespread attention. However, the performance of PV systems is easily affected by factors such as irradiance and temperature in complex environments, leading to significant fluctuations in output power and making it difficult to achieve stable and efficient energy conversion. To address this issue, this paper proposes an enhanced maximum power point tracking (MPPT) algorithm based on the combination of improved gray wolf optimizer (GWO) and incremental conductance (INC) methods, aiming to improve the adaptability and stability of PV systems in complex environments. By introducing innovative measures such as a candidate point dynamic focusing mechanism, position updates with perturbation factors, a five-level dynamic step-size strategy, direction consistency detection, and momentum suppression, the algorithm improves the search efficiency of the GWO and its adaptability to environmental mutations, avoids the drawbacks of fixed step sizes, and reduces overshoot and oscillations. Simulation verification was carried out on a simulation platform. The simulation results show that under various operating conditions, the algorithm achieves a good adaptive balance between global exploration and local exploitation, with tracking efficiency consistently above 99%, significantly improving the accuracy and efficiency of maximum power point tracking. Full article

Energy storage systems based on dual active bridge (DAB) converters are a critical component of DC microgrid systems. To address power oscillations and system stability issues caused by power deficits during the off-grid operation of DC microgrids, a control strategy for DAB energy storage systems based on voltage droop control is proposed. By analyzing the internal operational mechanisms of DAB power electronic converters and integrating voltage droop equations, a small-signal model is constructed to deeply investigate the dynamic characteristics of DAB energy storage systems under off-grid conditions. Using the Nyquist stability criterion, appropriate voltage droop coefficients are selected to enhance system stability. Finally, a DC microgrid model is built on the MATLAB/Simulink simulation platform. Through the rational design of the droop coefficients, the overshoot of the power response is reduced from 28.87% to 4.27%, and settling time is effectively shortened while oscillations are suppressed. The simulation results validate the correctness and effectiveness of the theoretical framework proposed in this study. Full article

This research proposes a novel adaptive virtual synchronous generator (VSG) control strategy for a photovoltaic-energy storage (PV-storage) hybrid system. In comparison to the traditional VSG control approach, the adaptive control strategy presented in this research markedly diminishes the fluctuations in output power. This improvement is accomplished through the dynamic adjustment of virtual inertia (J) and damping coefficient (D), which enables real-time responsiveness to variations in light intensity, converter power, and load power factors that traditional VSG controls are unable to address promptly. Initially, a small signal model of VSG’s active power closed-loop system is established and analyzed for a grid-connected converter in a PV-storage hybrid system. The influence of these parameters on the response speed and stability of the PV-storage system is discussed by analyzing the step response and root locus corresponding to varying J and D conditions. Then, this study employs the power angle and frequency oscillation characteristics of synchronous generators (SGs) to formulate criteria for selecting the J and D. Based on the established criteria, a parameter-adaptive VSG control strategy is proposed. Ultimately, the efficacy of the proposed strategy is validated in MATLAB/Simulink under three distinct conditions: abrupt changes in light intensity, converter power, and load power. The results indicate that the strategy is capable of diminishing power oscillation amplitude, effectively mitigating instantaneous impulse current, and notably alleviating frequency overshoot. Full article

This paper presents a zeroing neural networks (ZNN)-based gait optimization strategy for humanoid robots. First, the algorithm converts the angular momentum linear inverted pendulum (ALIP)-based gait planning problem into a time-varying quadratic programming (TVQP) problem by adding adaptive adjustment factors and physical limits as inequality constraints to avoid system oscillations or instability caused by large fluctuations in the robot’s angular momentum. Secondly, This paper proposes a real-time and efficient solution for TVQP based on an integral strong predefined time activation function zeroing neural networks (ISPTAF-ZNN). Unlike existing ZNN approaches, the proposed ISPTAF-ZNN is enhanced to achieve convergence within a strong predefined-time while exhibiting noise tolerance. This ensures the desired rapid convergence and resilience for applications requiring strict time efficiency. The theoretical analysis is conducted using Lyapunov stability theory. Finally, the comparative experiments verify the convergence, robustness, and real-time performance of the ISPTAF-ZNN in comparison with existing ZNN approaches. Moreover, comparative gait planning experiments are conducted on the self-built humanoid robot X02. The results demonstrate that, compared to the absence of an optimization strategy, the proposed algorithm can effectively prevent overshoot and approximate energy-efficient responses caused by large variations in angular momentum. Full article