Control of a Class of Industrial Processes With Time Delay Based on a Modified Uncertainty and Disturbance Estimator

Parameter effect analysis of particle swarm optimization algorithm in PID controller design

“…Therefore, variable parameters of PSO algorithm such as inertia weight, acceleration factors, and population size are taken into account and effects of these variables on PID controller parameter optimization process are analyzed in this study. During the optimization process, a SOPDT model is used since most of the high order processes can be modeled by either a FOPDT model or a SOPDT model [20]. Both visual and numerical results are provided in the paper to see the effects of each variable on change of fitness value, transient response characteristics, steady-state error, and error-based performance metrics.…”

Uncertainty and disturbance estimator with improved steady‐state performance for grid‐connected power converters

“…Correct filter design allows accurate TUD estimation and subsequent cancellation, yielding outstanding disturbance rejection performance. Basic analysis and design of TUDE-based controllers were revealed in [8][9][10][11][12][13][14][15] and applied to various practical systems in [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. TUDE-based control was recently applied to the field of power electronics and motor drives as well [35][36][37][38][39].…”

Stabilisability analysis and design of UDE‐based robust control

“…In [11], a UDE combined with a modified state predictor is adopted for stabilising a class of input‐delayed systems with non‐linear uncertainties. In [12], a modified UDE is proposed for the control of a class of industrial process with time delay, which introduces a delayed term to the control law. In [13], a non‐linear robust controller is designed for the non‐linear systems with uncertainties and unknown state delay, where the delayed terms are treated as an additional disturbance term.…”