The end-user must develop the LabVIEW instrument file.ĭetails for setting up LabVIEW with Equilibar Flow Control Valve On-site personnel can tune the PID settings in the program to optimize the valve’s performance for each application. Use the LabVIEW program on the laptop to send signals between I/O control boards, the flow meter and the Equilibar electronic pressure regulator.
On this page you will find specific information about using LabVIEW as a PID controller for a flow control loop with an Equilibar FCV.īelow is a schematic showing how the system is generally set up. Water Hammer and Chatter with Equilibar Back Pressure RegulatorsĮquilibar valves function as back pressure regulators by design and can be set up and used in flow control applications using a flow meter and control logic as explained on our flow control page.įor a review of the various types of control systems you can use to set up an Equilibar FCV for flow control, please visit our “ getting started with flow control ” page.Diaphragm Selection for Equilibar Regulators.Considerations for Oxygen Rich Applications.
The BLDC motor drive with RWNN-PID controller through simulation results proves a better in the performance and stability compared with using conventional PID and classical WNN-PID controllers.
The parameters of the proposed controller are optimized using Particle Swarm Optimization (PSO) algorithm. The proposed controller is applied for controlling the speed of BLDC motor which provides a better performance than using conventional controllers with a wide range of speed. The Recurrent Wavelet Neural Network (RWNN) is proposed, in this paper, with PID controller in parallel to produce a modified controller called RWNN-PID controller, which combines the capability of the artificial neural networks for learning from the BLDC motor drive and the capability of wavelet decomposition for identification and control of dynamic system and also having the ability of self-learning and self-adapting.
Therefore, it is not easy to obtain a good performance by applying conventional PID controller. The BLDC motor is a multivariable and nonlinear system due to variations in stator resistance and moment of inertia. In recent years, artificial intelligence techniques such as wavelet neural network have been applied to control the speed of the BLDC motor drive.
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