A data-driven approach for on-line tuning of minimum variance (MV) PID controller is
proposed in this paper for a linear system subject to stochastic disturbances, in which none …

Many methods are proposed in the literature for control of nonlinear systems based on multi
model approaches. Most of these methods are by simulation. An experimental investigation …

In addition to process elements like time delay, the PID structure of the controller can pose
fundamental limitations on the achievable control performance. A key difficulty in …

Since most chemical processes exhibit severe nonlinear and time-varying behavior, the
control of such processes is challenging. In this paper, a novel two-layer online adjust …

This study proposes an adaptive optimal predictive control (AOPC) for the upflow anaerobic
sludge blanket (UASB) reactor with recirculation, employing a PDE-ODE system. Effectively …

English In this study, an adaptive neuro fuzzy inference system (ANFIS) based inverse
controller design is presented for liquid level control application of a spherical tank. First, an …

This paper describes an extension to the detrended fluctuation analysis method for control
loop performance where the primary focus is on controller setpoint tracking capabilities. The …

A novel data-driven technique for performance assessment of multivariate control loops that
takes into account the interactions within the system is proposed. The technique merges the …

This paper is concerned with air handling units (AHUs), the performances of which directly
influence those of heating, ventilation and air conditioning systems. An autotuning receding …

The inverse fuzzy model can be used as a controller in an open loop fashion to produce
perfect control if there does not exist any disturbance or parameter variation in the system. In …