在线自适应误差模型船速调节器的研究

提高船舶航速和主机负荷的稳定性是船舶运动控制的主要目标之一.以船速为被控量,主机负荷为操作变量,应用活化函数为改进双曲正切函数的自适应神经网络和最陡下降法的非线性优化技术控制策略,建立了船速误差和主机负荷误差的串级自适应控制模型.设计了由计算机、PLC、变频调速电机、伺服电机和离心水泵组成的船速综合控制半实物仿真系统,实现了在不同调速状况下的稳定性控制.结果表明:在系统模型不确定,控制对象大惯性大滞后情况下,自适应误差模型抑制扰动和参数摄动有明显的优势,整个船速控制过程平滑稳定.     

发动机的动态模型及其调速仿真应用

建立柴油机动态模型及对调速过程进行仿真，是柴油机实现电控的基础性工作。针对柴油机电子调速器参数整定实验量大且参数影响规律性不强的特点，本文建立了发动机运行过程的动态物理模型。利用该模型可分析各参数对发动机控制的影响进行仿真，并利用仿真的结果指导6105Q柴油机数字式电子调速器的参数整定实验。实验结果表明，该模型能够满足电子调速器参数仿真的要求。     

柴油机电液复合式调速系统建模与仿真分析

建立了柴油机电液复合式调速系统的数学模型,并应用Simulink进行仿真;给出了调速器在负荷突加和突减变化过程中的动态调速特性曲线.重点分析了调速器可调参数对调速系统动态过程的影响,为在调速系统改进设计和运行管理中,采取必要措施以改善系统的性能提供了依据.本文仿真结果与要求精度吻合良好.     

风翼—柴油机混合动力船舶定航速调节系统的设计

风翼—柴油机混合动力船舶具有巨大的节能减排潜力,为了满足新型动力船舶主机调速需求,文章结合风翼—柴油机混合动力船舶的航行特点,提出了定航速调节系统的概念,设计了定航速调节系统框图和控制策略方案,为风翼—柴油机混合动力船舶定航速调节系统的研发提供了理论参考。     

小型柴油机控制系统与控制策略研究

基于小型柴油机的特性参数,通过对非增压柴油机模型进行合理修正,得到了一个合适的数学模型;采用PID参数模糊自整定控制算法进行了怠速控制器的设计,并仿真得到了较常规PID更优的控制效果,结果误差在理论允许的范围内.能够为小型柴油机的技术升级提供有效依据和技术参考.     

柴油机精小型液压调速器仿真设计及分析

调速器作为柴油机的控制大脑,其性能直接决定了柴油机的性能表现。本文以某精小型液压调速器为研究对象,介绍了其结构和工作原理。针对柴油机液压调速器结构复杂、维护难度高等特点,采用AMESim平台对系统各个环节进行了建模,并将各个环节进行组合,形成了系统的仿真分析模型。在此基础上,对滑阀开度压力变化、转速波动率以及动态特性等关键环节进行了分析,并将仿真结果与装机试验结果进行了对比。结果显示:调速器的转速波动率和动态特性的仿真结果与装机试验结果一致。     

论域自调整模糊PID控制算法设计与仿真

通过建立基于论域调整的自适应模糊PID控制算法对电控直列泵柴油机转速控制的位置环PID参数进行自整定.根据执行器的工作特性建立了执行器模型,与控制算法模型组成闭环进行仿真验证.通过与普通增量式PID控制算法的仿真结果进行比较,结果表明该控制算法在柴油机全工况范围内油量调节齿杆的控制效果优于普通增量式PID控制的效果.     

基于Matlab/xPC Target的BPH调速器实时仿真试验台研究

利用M atlab提供的Sim ulink、R A W和xPC Target工具箱建立了柴油机的实时仿真模型,并通过输入输出接口电路将仿真柴油机与实际调速器相连接构成闭环控制系统。采用这种半实物实时仿真方式在试验台上可实现反映柴油机调速特性的反馈调试功能,从而能够在调速器装机前实现其性能与状态的检查与调整。     

分体式涡轮增压对船舶柴油机工作特性影响的数值模拟

为提升传统废气涡轮增压柴油机低负荷工况性能及瞬态响应特性,以某船舶推进柴油机为研究对象,建立并试验校准其一维数值仿真模型.提出了以系统综合油耗量最优为目标的分体式涡轮增压器运行策略确定方法,对比分析了采用分体式涡轮增压后柴油机各主要性能及排放参数的变化.结果表明:以柴油机各限值参数为约束,采用离散网格法可有效确定柴油机...     

柴油机电子调速器PID参数模糊自校正研究

提出了对柴油机数字式电子调速器PID参数按调速系统过渡过程进行模糊自校正的原理,并对此进行了仿真研究。结果表明,该方法对提高电子调速器的调速性能有明显效果,对电子调速器适应柴油机过程参数的变化也有一定的改善。     

A novel NN based rotor flux MRAS to overcome low speed problems for rotor resistance estimation in vector controlled IM drives

This paper presents a new neural network based model reference adaptive system (MRAS) to solve low speed problems for estimating rotor resistance in vector control of induction motor (IM). The MRAS using rotor flux as the state variable with a two layer online trained neural network rotor flux estimator as the adaptive model (FLUX-MRAS) for rotor resistance estimation is popularly used in vector control. In this scheme, the reference model used is the flux estimator using voltage model equations. The voltage model encounters major drawbacks at low speeds, namely, integrator drift and stator resistance variation problems. These lead to a significant error in the estimation of rotor resistance at low speed. To address these problems, an offline trained NN with data incorporating stator resistance variation is proposed to estimate flux, and used instead of the voltage model. The offline trained NN, modeled using the cascade neural network, is used as a reference model instead of the voltage model to form a new scheme named as “NN-FLUXMRAS.” The NN-FLUX-MRAS uses two neural networks, namely, offline trained NN as the reference model and online trained NN as the adaptive model. The performance of the novel NN-FLUX-MRAS is compared with the FLUX-MRAS for low speed problems in terms of integral square error (ISE), integral time square error (ITSE), integral absolute error (IAE) and integral time absolute error (ITAE). The proposed NN-FLUX-MRAS is shown to overcome the low speed problems in Matlab simulation.     

Assessment of a fuzzy logic based MRAS observer used in a photovoltaic array supplied AC drive

In this paper a fuzzy logic (FL) based model reference adaptive system (MRAS) speed observer for high performance AC drives is proposed. The error vector computation is made based on the rotor-flux derived from the reference and the adaptive model of the induction motor. The error signal is processed in the proposed fuzzy logic controller (FLC) for speed adaptation. The drive employs an indirect vector control scheme for achieving a good closed loop speed control. For powering the drive system, a standalone photovoltaic (PV) energy source is used. To extract the maximum power from the PV source, a constant voltage controller (CVC) is also proposed. The complete drive system is modeled in MATLAB/Simulink and the performance is analyzed for different operating conditions.     

智能化——未来舰船监控系统的灵魂

舰船动力正趋向于全电力系统发展,动力系统和电力系统结合构成综合电力系统(IPS)则是近年来形成和发展起来的新的技术思想。随着综合平台智能管理平台技术的发展和实船运用,智能化监控技术得到同步发展,作为未来舰船监控系统发展的趋势,智能化将开拓舰船监控的新疆域。     

Direct adaptive torque control for maximizing the power captured by wind turbine in partial loading condition

In this paper, a direct adaptive control approach is used to track the tip speed ratio (TSR) of wind turbine to maximize the power captured during the below rated wind speed operation. Assuming a known optimum value of TSR, the deviation of actual TSR from the optimum one is mathematically expressed as TSR tracking error. Since the actual TSR is not a measurable quantity, this expression for TSR tracking error is linearized and simplified to express it in terms of wind speed and rotor speed, where rotor speed can easily be measured. Although it is possible to measure the wind speed with high accuracy using LiDAR, using it raises the overall cost of wind turbine installation; hence, a method to estimate the wind speed is also proposed. The adaptive controller operates on this simplified TSR tracking error to drive it to zero and to keep the TSR constant at desired optimum value. The performance of the proposed control scheme is illustrated by implementing and simulating it in the National Renewable Energy Laboratory 5MW wind turbine model and comparing the results with the existing baseline fixed gain controller. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive Self-Tuning Speed Control for Permanent-Magnet Synchronous Motor Drive With Dead Time

In this paper, an adaptive self-tuning speed control for a permanent-magnet synchronous motor (PMSM) drive with dead time is proposed. Firstly, to equivalently place the dead time element outside the closed-loop speed control, a dead time compensator (DTC), based on the Smith predictor and a self-tuning proportional-integral model-following controller (ST-PI-MFC) is proposed. The model-following error is used to adaptively update the gains of the ST-PI-MFC via the affine projection algorithm (APA). Secondly, a disturbance observer, based on the time delay control (TDC) approach is used for torque feed forward control. The system's model is greatly simplified when the disturbance observer is combined with the motor. Relying on the simplified model, a natural adaptive observer is used to estimate the motor speed. Unknown motor parameters are estimated by minimizing the state estimation error using an iterative gradient algorithm offered by the affine projection. The estimated parameters are used to update the gains of the integral-proportional (IP) servo loop controller, the disturbance observer and the Smith model. The validity and usefulness of the proposed control scheme are verified through simulation and experimental results     

风速时间序列非线性短期预测

针对风速时间序列复杂的非线性特征,根据C-C算法确定重构参数(嵌入维数及延迟时间)并对风速重构相空间,建立径向基函数神经网络(RBF网络)及Volterra自适应预测模型对风速时间序列进行预测,以Lorenz方程数值解为例验证了两种预测方法的可行性。结果表明:RBF神经网络模型和Volterra自适应预测模型都能对实测风速时间序列进行较为准确的预测,预测误差分别在0.3和0.1 m/s内;Volterra自适应预测模型预测结果总体较RBF神经网络模型预测精度更高,且随着预测时间的增大,预测误差呈增大趋势,这与混沌存在初值敏感性的特征相符。     

汽油机数字式电子调速器自适应控制动态特性的研究

汽油机采用电子调速器，减小瞬时调速率值成为全面提高汽油机调速性能的关键。PID自适应控制按汽油机过渡过程各阶级转速变化的情况，确定PID各项的系数，调节节气门开度的变化量。试验结果表明，瞬时调速率达到5．4％，稳定时间1．54s，该方法对改善电子调速器的动态特性有明显效果。     

大型水电机组调节系统无模型自适应PID控制器设计

水电机组调节系统在水电发电系统中承担着能量转换的重要作用。针对水电机组运行工况复杂多变、控制困难的问题,研究无模型自适应控制（MFAC）理论,设计了一种基于紧格式动态线性化方法（CFDL）的无模型自适应PID控制器（MFAC-PID）。在此基础上,以某电站机组为对象建立其调节系统非线性仿真模型,在550、540、526 m三种水头下,进行了机组开机过渡过程仿真试验。结果表明,与PID控制相比,所设计的MFAC-PID控制器可使开机过程中机组转速超调量、转速上升时间和稳态误差值分别减小56.0%、0.6%、60.0%。此外,当机组工作水头发生变化时,MFAC和PID控制效果变差,而MFAC-PID控制器能保证良好的动态响应品质,表现出更好的自适应能力。     

柴油机模型参考自适应调速系统的研究

首先根据自动控制理论建立了柴油机模型参考自适应调速系统的数学模型，并以李亚普诺夫方法设计自适应控制器。此后，在计算机仿真的基础上，分析了调速系统的动态性能。结果表明，在发动机调速系统中引入模型参考自适应控制原理，使系统性能得到明显提高。