A Novel Fast Error Convergence Approach for an Optimal Iterative Learning Controller

References

• C. Hua, Y. Qiu, and X. Guan, Enhanced model-free adaptive iterative learning control with load disturbance and data dropout, Int. J. Syst. Sci. 51 (11), 2057 (2020). DOI: 10.1080/00207721.2020.1784492.
   Web of Science ®Google Scholar
• L. Zhou et al., An integrated robust iterative learning control strategy for batch processes based on 2D system, J. Process Control 85, 136 (2020). DOI: 10.1016/j.jprocont.2019.11.011.
   Web of Science ®Google Scholar
• D. Luo, J. Wang, and D. Shen, Iterative Learning Control for Locally Lipschitz Nonlinear Fractional-order Multi-agent Systems, J. Franklin Inst. 357 (11), 6671 (2020). DOI: 10.1016/j.jfranklin.2020.04.032.
   Web of Science ®Google Scholar
• J.-X. Xu, and R. Yan, Iterative learning control design without a priori knowledge of the control direction, Automatica 40 (10), 1803 (2004). DOI: 10.1016/j.automatica.2004.05.010.
   Web of Science ®Google Scholar
• W. Xiong et al., Iterative learning control for discrete-time systems with event-triggered transmission strategy and quantization, Automatica 72, 84 (2016). DOI: 10.1016/j.automatica.2016.05.031.
   Web of Science ®Google Scholar
• L. Li et al., Method to improve convergence performance of iterative learning control systems with bounded noise, J. Franklin Inst. 357 (3), 1644 (2020). DOI: 10.1016/j.jfranklin.2019.11.030.
   Web of Science ®Google Scholar
• Y. Liu et al., Enhanced kalman-filtering iterative learning control with application to a wafer scanner, Inf. Sci. 541, 152 (2020). DOI: 10.1016/j.ins.2020.05.125.
   Web of Science ®Google Scholar
• H. A. Foudeh, P. Luk, and J. Whidborne, Application of norm optimal iterative learning control to quadrotor unmanned aerial vehicle for monitoring overhead power system, Energies 13 (12), 3223 (2020). DOI: 10.3390/en13123223.
   Web of Science ®Google Scholar
• R. Wang, Y. Wei, and R. Chi, Enhanced data-driven optimal iterative learning control for nonlinear non-affine discrete-time systems with iterative sliding-mode surface, Trans. Inst. Meas. Control, 0142331219900593 (2020).
   Web of Science ®Google Scholar
• S. Arimoto, Bettering operation of dynamic systems by learning: A new control theory for servomechanism or mechatronics systems, In The 23rd IEEE Conference on Decision and Control (pp. 1064–1069). IEEE. (1984).
   Google Scholar
• C. Nandi, R. Debnath, and P. Debroy, Intelligent control systems for carbon monoxide detection in IoT environments. Guide to Ambient Intelligence in the IoT Environment, pp. 153–176. Springer, Cham, 2019.
   Google Scholar
• J. Lu et al., Nonlinear monotonically convergent iterative learning control for batch processes, IEEE Trans. Ind. Electron. 65 (7), 5826 (2018). DOI: 10.1109/TIE.2017.2782201.
   Web of Science ®Google Scholar
• X. Zhao, and Y. Wang, Energy-optimal time allocation in point-to-point ILC with specified output tracking, IEEE Access 7 (99), 122595 (2019). DOI: 10.1109/ACCESS.2019.2937972.
   Google Scholar
• Y. Chen and C. Wen, terative learning control: convergence, robustness and applications. Springer, 1999.
   Google Scholar
• Bien Zeungnam, and Jian-Xin Xu, eds. Iterative learning control: analysis, design, integration and applications. Springer Science & Business Media, 2012.
   Google Scholar
• J. Dong, and B. He, Novel fuzzy PID-type iterative learning control for quadrotor UAV, Sensors 19 (1), 24 (2018). DOI: 10.3390/s19010024.
   Web of Science ®Google Scholar
• Q.-Y. Xu, and X.-D. Li, HONN-based adaptive ILC for pure-feedback nonaffine discrete-time systems with unknown control directions, IEEE Trans. Neural Networks Learn. Syst., 31 (1), 212–224 (2019).
   PubMed Web of Science ®Google Scholar
• T. Si, and L. Long, A small‐gain approach for adaptive output‐feedback NN control of switched pure‐feedback nonlinear systems, Int. J. Adapt. Control Signal Process. 33 (5), 784 (2019). DOI: 10.1002/acs.2988.
   Web of Science ®Google Scholar
• D. Meng, and K. L. Moore, Robust iterative learning control for nonrepetitive uncertain systems, IEEE Trans. Automat. Control 62 (2), 907 (2017). DOI: 10.1109/TAC.2016.2560961.
   Web of Science ®Google Scholar
• T. Seel, T. Schauer, and J. Raisch, Monotonic convergence of iterative learning control systems with variable pass length, Int. J. Control 90 (3), 393 (2017). DOI: 10.1080/00207179.2016.1183172.
   Web of Science ®Google Scholar
• X. Li, and D. Shen, Two novel iterative learning control schemes for systems with randomly varying trial lengths, Syst. Control Lett. 107, 9 (2017). DOI: 10.1016/j.sysconle.2017.07.003.
   Web of Science ®Google Scholar
• Y. S. Wei, and X. D. Li, Varying trail lengths-based iterative learning control for linear discrete-time systems with vector relative degree, Int. J. Syst. Sci. 48 (10), 2146 (2017). DOI: 10.1080/00207721.2017.1309590.
   Web of Science ®Google Scholar
• D. Shen, and J.-X. Xu, Adaptive Learning Control for Nonlinear Systems With Randomly Varying Iteration Lengths, IEEE Trans. Neural Netw. Learn. Syst. 30 (4), 1119 (2019). DOI: 10.1109/TNNLS.2018.2861216.
   PubMed Web of Science ®Google Scholar
• S. Liu, and J. R. Wang, Fractional order iterative learning control with randomly varying trial lengths, J. Franklin Inst. 354 (2), 967 (2017). DOI: 10.1016/j.jfranklin.2016.11.004.
   Web of Science ®Google Scholar
• S. Liu, A. Debbouche, and J. Wang, On the iterative learning control for stochastic impulsive differential equations with randomly varying trial lengths, J. Comput. Appl. Math. 312, 47 (2017). DOI: 10.1016/j.cam.2015.10.028.
   Web of Science ®Google Scholar
• D. Meng, and J. Zhang, Deterministic convergence for learning control systems over iteration-dependent tracking intervals, IEEE Trans. Neural. Netw. Learn. Syst. 29 (8), 3885 (2018). DOI: 10.1109/TNNLS.2017.2734843.
   PubMed Web of Science ®Google Scholar
• B. P. Molinari, The time-invariant linear-quadratic optimal control problem, Automatica 13 (4), 347 (1977). DOI: 10.1016/0005-1098(77)90017-6.
   Web of Science ®Google Scholar
• S. Arimoto, S. Kawamura, and F. Miyazaki, Bettering operation of dynamic systems by learning: A new control theory for servomechanism or mechatronics systems, in The 23rd IEEE Conference on Decision and Control, pp. 1064–1069, IEEE, 1985.
   Google Scholar
• S. Riaz, H. Lin, and M. P. Akhter, “Design and Implementation of an Accelerated Error Convergence Criterion for Norm Optimal Iterative Learning Controller,” Electronics, 9 (11), 1766, 2020.
   Google Scholar
• D. Meng, Y. Jia, and J. Du, Stability of varying two-dimensional Roesser systems and its application to iterative learning control convergence analysis, Control Theory Appl. Iet 9 (8), 1221 (2015). DOI: 10.1049/iet-cta.2014.0643.
   Web of Science ®Google Scholar
• H. Ouerfelli, S. B. Attia, and S. Salhi, Switching-iterative learning control method for discrete-time switching system, Int. J. Dyn. Control 6 (4), 1755 (2018).
   Google Scholar
• A. Nusawardhana, S. H. Zak, and W. A. Crossley, Nonlinear synergetic optimal controllers, J. Guidance Control. Dynam. 30 (4), 1134 (2007). DOI: 10.2514/1.27829.
   Web of Science ®Google Scholar
• Lin, M. M., and Chiang C.-Y. An accelerated technique for solving one type of discrete-time algebraic Riccati equations, J. Comput. Appl. Math. 338, 91 (2018).
   Web of Science ®Google Scholar
• J.-X. Xu, and B. Viswanathan, Adaptive robust iterative learning control with dead zone scheme, Automatica 36 (1), 91 (2000). DOI: 10.1016/S0005-1098(99)00100-4.
   Web of Science ®Google Scholar
• L. Aarnoudse et al., Commutation-angle iterative learning control for intermittent data: Enhancing piezo-stepper actuator waveforms, (2020).
   Google Scholar
• S. Riaz, H. Lin, M. Bilal Anwar, and H. Ali, Design of PD-type second-order ILC law for PMSM servo position control, J. Physics: Conference Series, 1707, 2020/11, 012002 (2020).
   Google Scholar
• W. Qiu et al., Integrated predictive iterative learning control based on updating reference trajectory for point-to-point tracking, J. Process. Control 85, 41 (2020). DOI: 10.1016/j.jprocont.2019.11.003.
   Web of Science ®Google Scholar