N. Amann, D. H. Owens, and E. Rogers. Iterative learning control for discrete time systems with exponential rate of convergence. Technical Report 95/14, Centre for Systems and Control Engineering, University of Exeter, 1995. Home/Search Document Details and Download
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Some results on Iterative Learning Control with disturbances - Norrlöf, Gunnarsson (1998) (Correct)
.... Arimoto et al. [2] in 1984 and since than many papers have been addressing robot control in combination with iterative learning control, e.g. 4] 11] 13] 7] and [9] The convergence properties of the algorithm were addressed already in [2] and are further covered in many articles e.g. 10] [1], and [8] In this paper the fundamental properties of the ILC algorithm applied as a complement to conventional feed forward and feed back control will be illustrated. Focus will be on disturbance affects but also convergence and robustness will be discussed. 1Better means here with respect to ....
N. Amann, D. H. Owens, and E. Rogers. Iterative learning control for discrete time systems with exponential rate of convergence. Technical Report 95/14, Centre for Systems and Control Engineering, University of Exeter, 1995.
On The Use Of Learning Control For Improved Performance In.. - Gunnarsson, Norrlöf (1997) (1 citation) (Correct)
....i.e. that the updating procedure of the input signal converges. This issue was addressed already in [1] where some (restrictive) convergence conditions were presented. The convergence properties have then been further studied by several authors. See, for example, 4] 5] 6] 7] 8] and [9]. Even though a main objective for ILC has been to generate an input signal without using prior knowledge of the process to be controlled it turns out that some kind of more or less explicit model of the process is needed in order to design a suitable iterative learning control law. Some ....
N. Amann, D.H. Owens, and E. Rogers. "Iterative Learning Control for Discrete Time Systems with Exponential Rate of Convergence". Technical report, Report Number: 95/14, Centre for Systems and Control Engineering, University of Exeter, Exeter, United Kingdom, 1995.
An Iterative Learning Control Method for Continuous-Time.. - Chow, Fang (1998) (2 citations) (Correct)
....of ILC is to determine a control input iteratively, resulting in the plant s ability to track the given reference signal or the output trajectory over a finite time interval. ILC has been further explored and is now one of the appealing fields of research in control systems [6] 9] 10] 16] [18]. The most widely used iterative learning algorithm is the PID type algorithm because this enables the conventional PID like system for processing the error. Geng et al. in [6] however, pointed out that all PID type ILC techniques inevitably suffer from tight restriction. The understanding of ....
.... then introduced the two dimensional (2 D) system theory [7] 8] to the LCS [6] In fact, one of the major shortcomings experienced in the ILC is the establishment of a suitable mathematical model to clearly describe the dynamics of the control system and the behavior of the learning process [6] [18]. As there are two independent dynamic processes in the 2 D system, we are able to use one of them to reflect the system dynamics in the time domain and the other to reflect the Manuscript received March 28, 1996; revised September 11, 1996, March 6, 1997, and November 3, 1997. This paper was ....
N. Amann, D. H. Owens, and E. Rogers, "Iterative learning control for discrete-time systems with exponential rate of convergence," Proc. Inst. Elect. Eng.---Control Theory Appl., vol. 143, no. 2, 1996.
Using Iterative Learning Control to Get Better Performance.. - Norrlöf, Gunnarsson (1997) (Correct)
.... than many papers has been addressing robot control in combination with iterative learning control, e.g. 2] 5] and [10] The convergence properties when using iterative learning control is another very important aspect, addressed already in [1] and further covered in many articles e.g. 6] [7], 9] In this paper iterative learning control is studied as a complement to conventional feedforward and feed back control. We will mainly consider linear systems, but also study the effects of non linear friction. The aim is to illustrate the fundamental properties of the ILC algorithm applied ....
N.Amann, D.H.Owens, and E.Rogers. Iterative learning control for discrete time systems with exponential rate of convergence. Technical Report 95/14, Centre for Systems and Control Engineering, University of Exeter, 1995.
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