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Point to Point ILC with Receding Horizon Optimization Approach

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Haris Anwaar, Yin YiXin, Muhammad Ammar Ashraf, Salman Ijaz

Haris Anwaar, Yin YiXin, Muhammad Ammar Ashraf and Salman Ijaz. Point to Point ILC with Receding Horizon Optimization Approach. International Journal of Computer Applications 165(11):19-24, May 2017. BibTeX

	author = {Haris Anwaar and Yin YiXin and Muhammad Ammar Ashraf and Salman Ijaz},
	title = {Point to Point ILC with Receding Horizon Optimization Approach},
	journal = {International Journal of Computer Applications},
	issue_date = {May 2017},
	volume = {165},
	number = {11},
	month = {May},
	year = {2017},
	issn = {0975-8887},
	pages = {19-24},
	numpages = {6},
	url = {},
	doi = {10.5120/ijca2017914074},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Iterative learning control is a control technique used for the tracking of a finite duration trajectory. Iterative learning control (ILC) with focus on speed of tracking specific points and tracking error on these points is analyzed in this paper. A technique is introduced which employs the receding horizon optimization to track the points along with the iterative learning control is introduced. In order to increase the efficiency of optimization, use of Laguerre functions is introduced which gives more freedom in parameterizing the optimization trajectory and in tuning the optimization parameters. Hence the technique can be efficiently used to track points within the trajectory with good performance.


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Point to Point Iterative learning control, receding horizon control, Iterative Learning control