By selecting proper manipulated variables, the PEMFC does not exhibit sign change in gain and hence can be controlled by using a linear controller.
This paper studies the problem of control for a class of fuzzy system models by using a linear output controller.
Using MATLAB/Simulink S-functions combined with the differential flatness property of the robot, trajectory tracking is carried out in closed loop by using a linear flat controller.
The main result in the paper is that the delay margin can be made arbitrarily large by using a linear periodic controller.
These characterisation techniques are then used to show that a linear controller can control the conditions within a bubbling bed.
The best linear model can then be used to design a linear controller that robustly stabilizes the linear system in presence of the nonlinear modeling error.
The closed-loop response is very easily tuned using the proposed nonlinear approach, and the nonlinear controller uses significantly less current than a linear controller because no bias currents are required in the electromagnets.
On the basis of prior work, a linear controller design is used to control the front steer angle and the resulting steering control loop behaviour is explicitly considered in the prediction model of the outer MPC.
A neural flight control system is used to actuate the gains of a linear controller for gain scheduling purposes without any explicit system identification.
Experimental results of the boost converter using sliding mode fuzzy control are evaluated in comparison with experimental results using a linear PID and PI controller.
