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Adjustable transient performance for unknown nonlinear systems via control gain selection: Application to tower crane
Yajing Zhao1, Xiaoping Liu1, Cungen Liu2
1Department of Electrical and Computer Engineering, Lakehead University, Thunder Bay, P7B 5E1, Ontario, Canada.
Abstract:
This paper proposes a modified adaptive backstepping method with a control gain selection guideline for unknown nonlinear systems, focusing on adjustable transient performances. Unlike conventional backstepping methods that cancel linear cross terms, the proposed approach retains these terms to obtain a symmetric state matrix for the linearized closed-loop system. Based on this structure, a novel control gain determination method is developed to select control gains for achieving a desired settling time while effectively attenuating overshoot. Compared with conventional trial-and-error tuning, the proposed method improves tuning efficiency. Moreover, the potential solvability difficulties of optimization-based pole-placement methods are avoided. Numerical examples with different desired settling times demonstrate adjustable settling time and overshoot attenuation. Simulations and experiments on a tower crane platform further validate the proposed scheme and demonstrate its advantages compared with existing control methods.
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