In this paper, an example is demonstrated, where a single two-variable controller is successfully designed to perform both STATCOM AC and DC voltage control function.
This paper presents a model-based multi-variable controller for large-scale air-conditioning systems.
A real-time energy management strategy is employed as the supervisory level controller to generate the optimal values of critical variables, while a model-based multi-variable controller is designed as the low level controller to track the values.
Some experimental studies have been conducted on a 6-DOF EHST and experimental results show that acceleration tracking control performances, including the rate of convergence of the LMS algorithm and acceleration tracking accuracy, have been improved compared to a conventional three-variable controller and adaptive controllers.
Model identification for use in the design of multi-variable controllers should utilize an experimental design that optimizes the resulting robust control stability and performance, irrespective of the eventual controller structure or tuning.
A technique is presented herein for the design and implementation of two two-input-three-output multi-variable controllers which use two piezoceramic patches as actuators, and a further two such patches, as well as an accelerometer, as sensors.
A variable temperature controller and adjustable upstream pressure controller permit measurements of low-permeability membranes and evaluation of temperature related phenomena.
They declared that infrared flux on the polyethylene solution from the emitter can be precisely controlled by both the variable output controller and the distance between the emitter and the glass syringe.
The adaptive fuzzy variable structure controller developed in this paper employs fuzzy controller with nonlinear sliding mode.
