An Optimization-Based Iterative Learning Control Design Method for UAV’s Trajectory Tracking

Iterative Learning Control for Hybrid Systems

Volume 1: Adaptive/Intelligent Sys. Control; Driver Assistance/Autonomous Tech.; Control Design Methods; Nonlinear Control; Robotics; Assistive/Rehabilitation Devices; Biomedical/Neural Systems; Building Energy Systems; Connected Vehicle Systems; Control/Estimation of Energy Systems; Control Apps.; Smart Buildings/Microgrids; Education; Human-Robot Systems; Soft Mechatronics/Robotic Components/Systems; Energy/Power Systems; Energy Storage; Estimation/Identification; Vehicle Efficiency/Emissions ◽

10.1115/dscc2020-3191 ◽

2020 ◽

Author(s):

Kirti D. Mishra ◽

K. Srinivasan

Keyword(s):

Hybrid Systems ◽

Iterative Learning Control ◽

Design Method ◽

Tracking Error ◽

Control Design ◽

Learning Control ◽

Iterative Learning ◽

Linear Matrix ◽

Triangular Structure ◽

Form Representation

Abstract Iterative learning control (ILC) has been growing in applicability, along with growth in theory for classes of linear and nonlinear systems, and this study extends the theory of ILC to hybrid systems. A lifted form representation of hybrid systems with input-output dependent switching rules is developed, and the proposed lifted form representation is modeled as a switched system with arbitrary/unconstrained switching rules in the trial domain for control design. The causality of hybrid systems in the time domain results in the (lower) triangular structure of switched systems in the trial domain, the triangular structure enabling systematic and efficient control design. A unique aspect of the control design method developed for ILC of hybrid systems in this study is that a solution to the required set of linear matrix inequalities (LMIs) is guaranteed to exist under mild assumptions, which is in contrast to many other studies proposing LMI based solutions in controls literature. The proposed method is validated numerically for a motion control application, and robust and monotonic convergence of the tracking error to zero is demonstrated.

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Discrete Fourier Transform Based Iterative Learning Control Design for Linear Plants With Experimental Verification

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.3072149 ◽

2009 ◽

Vol 131 (3) ◽

Cited By ~ 9

Author(s):

C. T. Freeman ◽

P. L. Lewin ◽

E. Rogers ◽

D. H. Owens ◽

J. J. Hatonen

Keyword(s):

Fourier Transform ◽

Discrete Fourier Transform ◽

Experimental Verification ◽

Iterative Learning Control ◽

Design Method ◽

Control Design ◽

Learning Control ◽

Iterative Learning ◽

Control Algorithms ◽

Straightforward Manner

This paper considers the design of linear iterative learning control algorithms using the discrete Fourier transform of the measured impulse response of the system or plant under consideration. It is shown that this approach leads to a transparent design method whose performance is then experimentally benchmarked on an electromechanical system. The extension of this approach to the case when there is uncertainty associated with the systems under consideration is also addressed in both algorithm development and experimental benchmarking terms. The robustness results here have the applications oriented benefit of allowing the designer to manipulate the convergence and robustness properties of the algorithm in a straightforward manner.

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