Title :
A new dynamical linearization based adaptive ILC for nonlinear discrete-time MIMO systems
Author :
Ronghu Chi ; Zhongsheng Hou ; Shangtai Jin ; Danwei Wang
Author_Institution :
Sch. of Autom. & Electr. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China
Abstract :
Most of the available results of adaptive iterative learning control (AILC) hitherto have considered the control systems with known linearly parameterized structures. A dynamical linearization approach is developed for a general nonlinear multiple input multiple output systems. And then a discrete-time adaptive ILC approach is presented to deal with the ILC problems of nonlinear MIMO systems with iteration-varying initial error and reference trajectory. The controller design and analysis is completely data-driven without using any modeling information of the plant, but the measured I/O data only. The almost perfect tracking performance is asymptotically guaranteed by rigirous mathematical analysis.
Keywords :
MIMO systems; adaptive control; control system analysis; control system synthesis; discrete time systems; iterative methods; learning systems; linearisation techniques; nonlinear control systems; performance index; tracking; AILC; I/O data; adaptive iterative learning control; data-driven controller analysis; data-driven controller design; discrete-time adaptive ILC approach; dynamical linearization approach; dynamical linearization based adaptive ILC; general nonlinear multiple input multiple output system; iteration-varying initial error; linearly parameterized structure; mathematical analysis; nonlinear MIMO system; nonlinear discrete-time MIMO system; reference trajectory; tracking performance; Adaptive systems; Convergence; MIMO; Nonlinear systems; Robots; Trajectory; Adaptive iterative learning control; Iteration-varying target trajectories; Nonlinear discrete-time System; Random initial condition; dynamical linearization;
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-1871-6
Electronic_ISBN :
978-1-4673-1870-9
DOI :
10.1109/ICARCV.2012.6485199
