Anupab Kerdlam1. Iterative learning and internal model control applied to diesel engine throttle. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2014.
Iterative learning and internal model control applied to diesel engine throttle
Abstract:
Iterative learning control is an adaptive, feed-forward, performance enhancing control technique. Its advantages include its simple algorithm, its stability without the need of persistently exciting input, and its being plant-model-independent. Internal model control is a feedback control technique. Its main advantage includes its ability to deal with plant having time delay or non-minimum phase. However, the internal model control requires accurate plant model. Model uncertainty can cause performance deterioration. In this paper, iterative learning control is used to improve the performance of the internal model control. Two practical schemes in combining the iterative learning control with internal model control are explored. The first scheme consists of an internal model control as feedback and a frequency-domain iterative learning control as a performance-enhancing feed-forward to reduce tracking error. The second scheme is model matching where the iterative learning control reduces the model output error. Based on actual experiments on a Diesel engine throttle in our laboratory, discussions are made regarding their performance comparison.
King Mongkut's University of Technology North Bangkok. Central Library