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基于LabVIEW的温度采集和控制系统研究 被引量:3
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作者 秦永晋 郭亮 付力扬 《电子测试》 2016年第10期68-69,共2页
温度采集和控制系统在功能上表现出了较大的弊端,即系统功能性滞后,在采集控制过程中呈现非线性特征,在功能表达过程中很难建模。过去用的控制方法为PID法,其在控制输出的过程中会出现不利于系统运行的问题,如比例冲击和微变等。因此本... 温度采集和控制系统在功能上表现出了较大的弊端,即系统功能性滞后,在采集控制过程中呈现非线性特征,在功能表达过程中很难建模。过去用的控制方法为PID法,其在控制输出的过程中会出现不利于系统运行的问题,如比例冲击和微变等。因此本文主要研究的是一种基于LabVIEW的控制器,是在传统PID基础上发展形成的,其为FI-FP-FD控制器,又称为新型模糊PID控制器,其在温度采集与控制系统中发挥了较大的作用。 展开更多
关键词 温度采集和控制系统 LABVIEW fi-fp-fd控制器
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基于LabVIEW的温度采集和控制系统 被引量:6
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作者 付俐芳 晋帆 金小婷 《科学技术与工程》 2011年第34期8610-8613,共4页
温度采集和控制系统具有非线性、滞后大、建模难等问题,应用传统PID控制方法控制输出存在比例冲击和微分突变,使系统产生较大超调。为了避免这些问题,设计了一种基于LabVIEW的新型模糊PID控制器(FI-FP-FD控制器),并将其应用于基于虚拟... 温度采集和控制系统具有非线性、滞后大、建模难等问题,应用传统PID控制方法控制输出存在比例冲击和微分突变,使系统产生较大超调。为了避免这些问题,设计了一种基于LabVIEW的新型模糊PID控制器(FI-FP-FD控制器),并将其应用于基于虚拟仪器技术搭建的温度采集和控制系统中。现场试验表明,此新型模糊PID控制器有效地实现了对系统的温度采集和控制,有很高的实用价值。 展开更多
关键词 温度采集和控制 虚拟仪器LabVIEW FI-FP—FD控制器
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Parallel Fuzzy P+Fuzzy I+Fuzzy D Controller:Design and Performance Evaluation 被引量:4
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作者 Vineet Kumar A.P.Mittal 《International Journal of Automation and computing》 EI 2010年第4期463-471,共9页
In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller is proposed. It is derived from the conventional parallel proportional-integral-derivative (PID) contr... In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller is proposed. It is derived from the conventional parallel proportional-integral-derivative (PID) controller. It preserves the linear structure of a conventional parallel PID controller, with analytical formulas. The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller. Computer simulations are performed to evaluate the performance of the FP+FI+FD controller for setpoint tracking and load-disturbance rejection for some complex processes, such as first- and second-order processes with delay, inverse response process with and without delay and higher order processes. Also, the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve. The simulation and real time control is done using National InstrumentTM hardware and software (LabVIEWTM). The response of the FP+FI+FD controller is compared with the conventional parallel PID controller, tuned with the Ziegler-Nichols (Z-H) and /~strSm- H^gglund (A-H) tuning technique. It is observed that the FP+FI+FD controller performed much better than the conventional PI/PID controller. Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP+FI+FD controller. 展开更多
关键词 Proportional-integral-derivative (PID) fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller liquid-flow process inverse response process dead time.
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Some Investigations on Fuzzy P+Fuzzy I+Fuzzy D Controller for Non-stationary Process 被引量:1
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作者 Vineet Kumar B. C. Nakra A. P. Mittal 《International Journal of Automation and computing》 EI 2012年第5期449-458,共10页
The paper addresses the adaptive behaviour of parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller. The parallel FP+FI+FD controller is actually a non-linear adaptive controller ... The paper addresses the adaptive behaviour of parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller. The parallel FP+FI+FD controller is actually a non-linear adaptive controller whose gain changes continuously with output of the process under control. Two non-stationary processes, whose characteristics change with time, are considered for simulation study. Simulation is performed using software LabVIEW TM . The set-point tracking response of parallel FP+FI+FD is compared with conventional parallel proportional plus integral plus derivative (PID) controller, tuned with the Ziegler-Nichols (Z-N) tuning technique. Simulation results show that conventional PID controller fails to track the set-point and becomes unstable as the process changes its characteristic with time. But the parallel FP+FI+FD controller shows considerably much better set-point tracking response and does not deviate from steady state. Also, a huge spike is observed in the output of PID controller as the reference set-point and process parameters are changed, while the FP+FI+FD controller gives spike free control signal. 展开更多
关键词 Proportional plus integral plus derivative (PID) controller fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller non-stationary process adaptive control SELF-TUNING
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Stability Analysis of Parallel Fuzzy P + Fuzzy I + Fuzzy D Control Systems 被引量:1
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作者 Vineet Kumar A. P. Mittal R. Singh 《International Journal of Automation and computing》 EI CSCD 2013年第2期91-98,共8页
The study presented in this paper is in continuation with the paper published by the authors on parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP + FI + FD) controller. It addresses the sta... The study presented in this paper is in continuation with the paper published by the authors on parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP + FI + FD) controller. It addresses the stability analysis of parallel FP + FI + FD controller. The famous"small gain theorem" is used to study the bounded-input and bounded-output (BIBO) stability of the fuzzy controller. Sufficient BIBO-stability conditions are developed for parallel FP + FI + FD controller. FP + FI + FD controller is derived from the conventional parallel proportional plus integral plus derivative (PID) controller. The parallel FP + FI + FD controller is actually a nonlinear controller with variable gains. It shows much better set-point tracking, disturbance rejection and noise suppression for nonlinear processes as compared to conventional PID controller. 展开更多
关键词 Proportional plus integral plus derivative (PID) fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP FI FD) controller fuzzy control bounded-input and bounded-output (BIBO) stability nonlinear process.
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A Robust Fractional Order Fuzzy P + Fuzzy I + Fuzzy D Controller for Nonlinear and Uncertain System
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作者 Vineet Kumar K. P. S. Rana +2 位作者 Jitendra Kumar Puneet Mishra Sreejith S Nair 《International Journal of Automation and computing》 EI CSCD 2017年第4期474-488,共15页
In this paper, a robust fractional order fuzzy P + fuzzy I + fuzzy D (FOFP + FOFI + FOFD) controller is presented for a nonlinear and uncertain 2-1ink planar rigid manipulator. It is a nonlinear fuzzy controller... In this paper, a robust fractional order fuzzy P + fuzzy I + fuzzy D (FOFP + FOFI + FOFD) controller is presented for a nonlinear and uncertain 2-1ink planar rigid manipulator. It is a nonlinear fuzzy controller with variable gains that makes it self- adjustable or adaptive in nature. The fractional order operators further make it more robust by providing additional degrees of freedom to the design engineer. The integer order counterpart, fuzzy P + fuzzy I + fuzzy D (FP + FI + FD) controller, for a comparative study, was realized by taking the integer value for the fractional order operators in FOFP + FOFI + FOFD controller. The performances of both the fuzzy controllers are evaluated for reference trajectory tracking and disturbance rejection with and without model uncertainty and measurement noise. Genetic algorithm was used to optimize the parameters of controller under study for minimum integral of absolute error. Simulation results demonstrated that FOFP + FOFI + FOFD controller show much better performance as compared to its counterpart FP + FI + FD controller in servo as well as the regulatory problem and in model uncertainty and noisy environment FOFP + FOFI + FOFD controller demonstrated more robust behavior as compared to the FP + FI + FD controller. For the developed controller bounded-input and bounded-output stability conditions are also developed using Small Gain Theorem. 展开更多
关键词 Fuzzy P fuzzy I fuzzy D (FP FI FD) controller fractional order fuzzy P fuzzy I fuzzy D (FOFP FOFI+ FOFD) controller fractional order operator robust control model uncertainty noise suppression.
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