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Not only unmatched uncertainties, but also matched uncertainties are discussed in Lyapunov stability sense.
To this end, a novel fuzzy integral sliding manifold function is adopted such that the matched uncertainties are completely rejected while the mismatched ones will not be enlarged during the sliding mode phase.
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In this paper, the robust optimal control of continuous-time affine nonlinear systems with matched uncertainties is investigated by using a data-based integral policy iteration approach.
In our paper, the event-triggered consensus problem of multi-agent system with heterogeneous matching uncertainties is considered.
The controller is designed to tolerate the matched uncertainty, which is considered to be a function of the system states and the control inputs.
For matched uncertainty, it is shown that the optimal control problem is a linear quadratic regulator (LQR) problem, which can be solved to obtain a robust controller for FPUS.
More specifically, the ESO is used to estimate and compensate the mismatched as well as the matched uncertainties while the FTCD is adopted to compute the time derivatives of the virtual control laws and the reference signal.
For matched uncertainty, disturbances can be estimated and are compensated directly through control input [8].
Two strategies are proposed; a nonhigh gain feedback design is employed to achieve robust stability of the controlled system with matched uncertainties, and a parameter diffeomorphism is used as a high gain control to robustify the cancellation of unmatched uncertainties.
Both matched and mismatched uncertainties are considered.
Using the estimates, a sliding mode controller is effectively employed for the matched uncertainties.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com