ILC for Input Nonlinearities
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This chapter aims to tackle three nonlinear inputs, namely input saturation, input dead-zone and input backlash. In Sect. 3.1, a boundary ILC law is designed to smoothly address input saturation, by adopting hyperbolic tangent functions under identical condition. Section 3.2 divides input dead-zone into a linear input and a unknown bounded term, which is estimated by an ILC law from iteration to iteration. An adaptive ILC law is then proposed to guarantee the learning convergence of the Euler–Bernoulli beam in the presence of input dead-zone. In Sect. 3.3, two adaptive ILC laws are designed to smoothly cope with the non-differentiability of input backlash for a Timoshenko beam system.