Overshoot Problem Research Articles

Percolating cosmic string networks from kination

We describe a new mechanism, whose ingredients are realized in string compactifications, for the formation of cosmic (super)string networks. Oscillating string loops grow when their tension μ decreases with time. If 2H+μ˙/μ<0, where H is the Hubble parameter, loops grow faster than the scale factor and an initial population of isolated small loops (for example, produced by nucleation) can grow, percolate, and form a network. This condition is satisfied for fundamental strings in the background of a kinating volume modulus rolling toward the asymptotic large volume region of moduli space. Such long kination epochs are motivated in string cosmology by both the electroweak hierarchy problem and the need to solve the overshoot problem. The tension of such a network today is set by the final vacuum; for phenomenologically appealing large volume scenario vacua, this would lead to a fundamental string network with Gμ∼10−10. Published by the American Physical Society 2024

A Transient Damping Improvement Strategy for Enhancing Grid-Connected Active Power Response Performance of VSG

The given power and grid frequency disturbances can cause transient oscillations and steady-state deviations in the output power of a virtual synchronous generator (VSG), which can be effectively addressed by adding transient damping. However, this approach may result in significant power overshoot. This article proposes an improved VSG control strategy based on transient electromagnetic power feedback compensation and a small-signal model reduction scheme. Firstly, the grid-connected active closed-loop small-signal models of typical VSG control and transient damping VSG control are established, respectively. The transient oscillation suppression mechanism of active power is revealed through root locus and frequency response analyses, and the power overshoot characteristics of the two control strategies are analysed by combining them with the system of zero points. Secondly, the active transient feedback compensation method and the small-signal model reduction design method are introduced in detail. Finally, comparative analysis experiments are conducted using the Matlab/Simulink and hardware-in-the-loop experimental platform. It is verified that the proposed control strategy can suppress transient oscillations in active power, prevent steady-state deviations, and effectively mitigate the power overshoot problem of the system.

Wave refrigeration control via deep reinforcement learning

Abstract Wave refrigerating technology is a new type of refrigerating technology that performs more efficiently and is more environmentally friendly. Nowadays, the commonly used control method is the PID control method. However, although the above control methods are simple in structure, they have the problems of difficult parameter tuning, large overshoot, and unstable and inaccurate output response. Therefore, to improve the above problems, we propose a framework of deep reinforcement learning-based wave refrigerating control system. An improved SAC algorithm is used to learn the control system. The evaluation method is established according to the working condition requirements as well as the safety requirements in the operation process. Experiments show that this method can effectively improve the control efficiency as well as the control quality, which can make the control system operate stably.

Double-Closed-Loop Model Predictive Control Based on a Linear Induction Motor

The conventional PI control, which has been extensively employed in the high-performance control of linear induction motors, has the benefit of a straightforward concept, quick dynamic response, and simple control. Nevertheless, the linear induction motor is more susceptible to outside disturbances and mismatched parameters since it is a highly linked, high-order, nonlinear, time-varying, complex system. Because of this, this paper proposes a double-closed-loop control of the linear induction motor, whose speed and current loops are the model-predictive speed controller and the model-predictive current controller, respectively, to solve the problems of speed overshoot and oscillation when the linear induction motor is operated under PI control. The findings demonstrate the benefits of the suggested control strategy, which significantly enhances the linear induction motor’s speed control performance. These benefits include improved dynamic performance, limited overshooting, and robust resistance to load disturbance.

Control system optimisation of biodiesel-based gas turbine for ship propulsion

<p>Reducing a gas emission of shipping transportations become a main goal of international maritime organization to achieve a clean energy. One of best scenarios to achieve this goal is to shift a fossil fuel to a renewable energy-based fuel of a ship propulsion. This paper studies an optimization of a control system of the renewable-based small gas turbine engine for the ship propulsion. Proposed control system consists of a proportional-integral with engine performance limiters to avoid an engine damage. Proportional-integral gains are tuned by a whale optimization algorithm. A gain scheduling analysis of a step response is performed to obtain a searching area of tuning parameters and values of constant gains. In this step, the gains are modeled as function of plant variables. After the searching area is obtained, the proportional-integral gains are optimized using the whale optimization algorithm while the additional gains are set as constant values. Using this scenario, stable and optimal gains have been successfully achieved. Results show that the proposed method has better performance than that of the previous methods, i.e. gain scheduling and gain scheduling optimized by the whale optimization algorithm. The proposed method has lowest fitness value and does not have an overshoot problem.</p>

Research on the cabin pressure control system based on the gray wolf fuzzy PID algorithm

The cabin pressure control system is typically nonaffine-nonlinear time-varying system. In this paper, the fuzzy PID control method optimized by gray wolf algorithm is proposed to solve the problems of large overshoot and long adjustment times in traditional control methods. Simulation results show that the fuzzy PID control method optimized by gray wolf algorithm proposed in this paper improves the dynamic characteristics of the system, reduces cabin pressure error and adjustment time, stabilizes the control process, and improves the comfortableness of passengers.

Magnetic levitation system control research based on improved linear active disturbance rejection

In this study, we propose an improved linear active disturbance rejection control (I-LADRC) method to achieve stable suspension of magnetic levitation balls. This method can not only solve the overshoot problem but also enhance the anti-interference capability. The control algorithm is designed, and the convergence of the control system is verified by derivation. To verify the effectiveness of the proposed control algorithm, we conduct simulation experiments and analyze the dynamic performance, tracking effect, and anti-interference ability of four controllers: sliding mode control (SMC), LADRC, longitudinal error-LADRC (LE-LADRC), and I-LADRC. Simulation results show that I-LADRC outperforms SMC, LADRC, and LE-LADRC regarding tracking effect and anti-interference ability. We also experimentally verify the control performance of I-LADRC. The experimental results show that I-LADRC has strong anti-interference ability and robust performance, which is 100% and 50% higher than LADRC and LE-LADRC, and has good dynamic performance, which verifies the effectiveness of the simulation experiment, which exhibits better robustness and dynamic performance.

Research and Simulation of Improved Smith Prediction Algorithm Based on PLC

Aiming at the problem of excessive overshoot caused by large delay in temperature control process, based on the research of Smith predictive control algorithm, an improved gain adaptive Smith predictive control scheme is proposed, which can track the change of gain in real time. The simulation program is written based on TIA Botu and configuration software, and the operation results show that the improved scheme improves the lag effect and the adaptability to the model, and it still has good control quality after the parameter changes.

Designing an optimal PID controller for a PV-connected Zeta converter using genetic algorithm

This paper suggests a way of fixing problems of voltage fluctuations and peak overshoot in a PV-connected Zeta converter system. The Zeta converter in the proposed approach is controlled using proportional integral derivative (PID) while a genetic algorithm (GA) calculates the PID coefficients based on the control mechanism. The performance of the designed system was analyzed in a MATLAB/Simulink environment. The analysis showed that the proposed system reduced the output voltage ripple and peak overshoot during transient conditions by providing feedback to the converter through the PID controller, this is a significant improvement when compared to the results found without a PID controller.

Research on Temperature Control of Plastic Laser Welding Based on Improved Snake Optimization Algorithm

Aiming at the nonlinear and time-varying characteristics of plastic laser welding temperature control system, and the problems of low accuracy and large overshoot when using the traditional proportional-integral-derivative (PID) controller, an improved snake optimization (ISO) is proposed to optimize the PID parameters. Firstly, the elite reverse learning strategy is introduced into the snake optimization (SO) to generate the reverse solution, and new individuals are generated through comparison to improve the convergence speed of the algorithm; Simultaneously introducing the water wave dynamic adaptive factor to enhance the algorithm’s iterative optimization ability. By iterating the algorithm, a set of suitable PID parameters are obtained to control the temperature control system. The simulation results show that compared to traditional PID controllers, ISO-PID reduces the adjustment time by approximately 0.42 seconds and does not cause overshoot.

Modeling and Simulation of the Stepping Motor Operation Curve

To improve the open-loop control performance of stepper motors, research was conducted on their operating curves. The acceleration-velocity characteristic equations of three common operating curves were established and compared with the torque frequency characteristic curves of stepper motors. Based on this, an improved segmented correction fitting S-shaped (SCFS) curve design method based on a high torque utilization sine curve was proposed to solve the problem of rotor blockage and overshoot caused by uneven acceleration during the operation of stepper motors. In the simulation of the stepper motor load motion system, the SCFS curve was compared with common curves. The simulation results showed that the position tracking error was reduced by approximately 82% compared to the trapezoidal curve and approximately 70% compared to the exponential curve. Research has found that this method is suitable for the design of high-precision motor operating curves and has a high application value in the field of precision motion control.

Research on control strategy of flywheel energy storage system based on active disturbance rejection control

The flywheel energy storage system (FESS) has been attracting the attention of national and international academicians gradually with its benefits such as high energy power density, high conversion productivity, and inexpensive pollution. For the mutual limitation problem of reaction speed and overshoot of the conventional PI controller, it is hard to satisfy the demand of high efficiency control. In this study, the Active Disturbance Rejection Controller (ADRC) is adopted to substitute the classical PI controller in the flywheel energy storage control system. The control system of an external loop of speed and an internal loop of current is adopted at the motor side. The standard ADRC is adopted by increasing the new nonlinear control function. The control system adopted the control strategy of the DC bus voltage external loop and the current internal loop on the grid side, as well as the second-order Linear Active Disturbance Rejection Controller (LADRC), to enhance the control ability of the DC bus voltage. In the charge/discharge control of the FESS, both the velocity external loop and current internal loop control strategies are utilized to simplify the system structure. The performance shows that the improved control system could effectively enhance the charging and discharging speed of the FESS and effectively suppress the DC bus voltage rise caused by flywheel state switching so that the system has better robustness.

Robotic abrasive belt grinding of complex curved blades based on a novel force control architecture integrating smooth trajectories

Constant force control and smooth trajectory planning are regarded as key strategies to improve the surface quality of blades in robotic abrasive belt grinding. However, some technical challenges still remain: (1) external normal grinding force with time-consuming sensing, large fluctuations, and force overshoot, and (2) lack of global C2 continuous grinding trajectories. In this paper, a unified architecture is proposed to concurrently address the above issues. The main contribution of this paper is to provide a complete solution for robots to automatically accomplish the grinding of complex curved blades. The grinding process is arranged as follows: Firstly, cubic B-spline and C2 continuous quaternion spline curves are used to generate the global C2 continuous trajectory, thereby avoiding vibrations and unexpected slowdowns during grinding. Secondly, the actual grinding force is sensed based on a low-speed Fourier series trajectory and the least square algorithm. Finally, a novel force control scheme consisting of an adaptive hybrid impedance (AHI) control scheme and two nonlinear tracking differentiator (NTD) modules is proposed to overcome the problems of large force fluctuations and force overshoot. Experimental results demonstrate that the proposed solution delivers better performance. Furthermore, the surface roughness Ra of the machined blade is controlled within 0.8 μm, which meets the requirements of real-world industrial applications.

Deadbeat Predictive Current Control for Surface-Mounted Permanent-Magnet Synchronous Motor Based on Weakened Integral Sliding Mode Compensation

Deadbeat predictive current control (DPCC) has excellent dynamics and can achieve current control with less computational effort. However, its control performance relies on the precision of the parameters of the motor. Current static error will be generated and control performance will be decreased when the predictive model parameters do not correspond to the practical parameters of the motor. In this article, a weakened integral sliding mode compensation method is proposed which converts the current error into a voltage compensation term and adds it to the prediction control output to effectively compensate for the steady-state error. In addition, a boundary layer is introduced to weaken the integral so as to solve the problems of integral saturation and overshoot caused by the introduction of the integral term when the error is large. Moreover, weight factors are introduced to optimize the feedback current, which enhances the robustness of the system. In the end, the effectiveness of this method is verified via simulation and experimental results.

An Improved Integral Sliding Mode Control for PMSM Drives Based on New Variable Rate Reaching Law With Adaptive Reduced-Order PI Observer

This paper focuses on speed control in a permanent-magnet synchronous motor (PMSM). To promote the speed tracking performance and anti-disturbance property of PMSM speed regulation system against various unknown disturbances, such as parameter mismatch, load torque variation, friction force, and so on, an improved integral sliding mode control (IISMC) method based on a new variable rate reaching law (NVRRL) and an adaptive reduced-order proportional integral observer (AROPIO) is proposed. The NVRRL method can reduce chattering, and convergence time of the system state at the same time compared to the existing sliding mode reaching law. An anti-windup sliding mode surface is proposed to overcome the overshoot problem of the integral sliding mode surface when the reference speed is large and rises in steps or large ramps. To further improve the system tracking accuracy and anti-disturbance ability, an AROPIO is used to estimate lumped disturbances and provides feedforward compensation for the IISMC. The simulation and experimental results show that the proposed IISMC+AROPIO method not only achieves high speed tracking accuracy and fast convergence speed but also achieves strong anti-interference ability.

Global fast terminal sliding mode control for path following of ultra large underactuated ship based on predictive LOS guidance

This study proposes a new line-of-sight guidance method based on position prediction that constructs the total path deviation by predicting the future time position of ships. This method can solve the problem of overshoot, which is prone to occur in the path following process of ultra large underactuated ships. A global fast terminal sliding mode method is used to design controllers that allow path deviations to converge in a finite time. To solve the problems of unknown velocity, disturbances, and sideslip angle during navigation, a high-order nonlinear observer is designed to estimate the system states and obtain the velocity values and external disturbances. The sideslip angle of the ship during navigation is obtained by estimating its velocity. Therefore, the problem of an unknown sideslip angle is solved, and the effectiveness of the proposed algorithm is verified through simulation experiments.

A Secondary-Side Phase-Shifted Bidirectional Soft-Switching DC–DC Converter Employing Step Voltage Switching for Eliminating Device Voltage Overshoot

This paper presents a modulation strategy for bidirectional power flow for the step voltage switched (SVS) secondary side phase-shifted (SPS) DC-DC converter that eliminates the device voltage overshoot problem. The voltage overshoot problem arises due to the resonance between transformer leakage inductance and the output capacitance of the current-fed side MOSFETs of the converter. Many snubber/clamp circuits were discussed in the literature to suppress this voltage overshoot. But the power loss in these clamp circuits will affect the converter efficiency. The bidirectional SVS SPS DC-DC converter presented in this paper eliminates the voltage overshoot problem instead of suppressing it and therefore nullifies the need for a voltage clamp circuit. And most of all switching devices undergo soft-switching (either ZVS or ZCS). These factors result in achieving a peak efficiency of 96%. The proposed topology is tested for 1.7KW at 100KHz switching frequency with voltage-fed side voltage being 72V and current-fed side voltage of 400V. The results obtained prove the feasibility of the proposed work.

Adaptive Controller for Bridgeless New SEPIC Integrated Landsman Converter for PFC in Induction Motor

The Induction Motor (IM)when powered by an AC supply, results in low power factor because of excessive harmonic contents, which is effectively minimized by adopting proper Power Factor Correction (PFC) technique. This paper proposes an AC-DC bridgeless SEPIC-Landsman converter for a 3ϕVoltage Source Inverter (VSI) fed IM to perform effective PFC and power quality enhancement at AC supply mains. Here, the bridgeless SEPIC-Landsman converter’s switching operation is controlled by the adaptive Proportional Integral (PI) controller for getting a controlled DC output voltage with minimum ripples. A Cascaded Type 2 Fuzzy Logic Controller (CT2FLC) effectively controls speed of the IM and also reduces the peak overshoot problem. Here, the speed control is achieved by adjusting voltage and frequency of 3 IMwith a reduced settling time of 0.2s. The proposed system is modeled with MATLAB Simulink and empirically validated, generating a THD value of 1.69% and an efficiency of 93%. The simulation and hardware results thus obtained confirm an effectiveness and reliable performance of the proposed system.

Speed Regulation and Optimization of Sensorless System of Permanent Magnet Synchronous Motor

Aiming at the problems of speed overshoot, slow convergence and poor anti-interference in the control of permanent-magnet synchronous motors (PMSMs) without a position sensor, a pulse vibration high-frequency signal injection method for a permanent-magnet synchronous motor with an improved sliding mode control was designed. Firstly, the improved approach rate function is combined with the improved non-singular fast terminal sliding mode surface to design the non-singular fast terminal sliding mode controller (NFTSMC), which is used in the speed loop to improve the speed convergence ability and reduce its overshoot. Secondly, in order to eliminate the influence of the band-pass filter on the system bandwidth in the traditional high-frequency injection method, a pulse vibration high-frequency signal injection method that injects high-frequency voltage signals and synchronous current signals into the d^ axis of the estimated two-phase rotation coordinate system d^q^ and the αβ axis of the two-phase stationary coordinate system αβ was designed to estimate the motor position and speed to achieve sensorless control. Finally, the above control strategy was compared with the speed loop PI and the traditional sliding mode controller (SMC) of the speed loop, respectively. The simulation and experimental results show that whether it is a no-load variable speed or fixed speed loading, the above control strategy can effectively reduce the speed overshoot, accelerate the speed convergence and improve the load capacity of the system.

Design and Analysis of EAST Predictive Control System for Hot Nitrogen Baking Process

To realize the automatic temperature closed-loop control of EAST (Experimental advanced super-conducting tokamak) baking system, the transfer function of EAST baking system is obtained by the step response method after being familiar with the mechanism structure of the baking system. According to the transfer function of the system, two control methods, conventional PI control and PI control based on Smith prediction are novelty proposed. MATLAB simulation analysis shows that PI control based on Smith prediction does not produce an overshoot compared with conventional PI control, and the final error given by tracking slope can be reduced by selecting appropriate PI parameters. Generally, PI control based on Smith prediction has better stability and dynamic performance. The novelty here lies in the introduction of PI control based on Smith prediction to solve the problem of large overshoot in conventional PI control.