Sparse online kernelized actor-critic Learning in reproducing kernel Hilbert space

Nussbaum‐based robust adaptive control for nonlinear switching systems with switching unknown control coefficients

“…Theorem 1. Under Assumption 1, for the system (10) with the Nussbaum-type gain design ( 18), ( 39), ( 59), virtual control design ( 16), (37), controller design (57), and adaptive law design ( 19), ( 40), ( 60), the DSC filters in (20), (41), the system output x 1 (t) can track the reference output x d (t) asymptotically with the boundedness of all signals in the closed-loop system being guaranteed.…”

“…Recently, since many engineering systems are governed by switching dynamics, including power systems [1][2][3] and electronic circuit systems, [4][5][6] switching systems have been extensively investigated. [7][8][9] Besides, in engineering practice, the dynamics of most physical systems are essentially nonlinear, 10,11 and much attention has been paid to nonlinear switching systems. 12 Among them, the strict feedback nonlinear switching systems, representing many practical systems such as circuit systems, 13 multi-agent systems, 14 robotic manipulators, 15 and networked systems, 16 are widely researched, where the main difficulty lies in the nonlinear switching dynamics, complicating the control design and stability analysis.…”

Event‐triggered robust control for multi‐player nonzero‐sum games with input constraints and mismatched uncertainties

“…Due to dynamic uncertainties in practical systems, the controller has to be robust to avoid the control performance deterioration of the closed‐loop system; in turn, this implies that the control system is effective whenever the actual system slightly deviates from its nominal conditions. During the past few decades, many robust control (RC) methods have been developed for nonlinear systems in the control community 1‐8 . Lin et al 2 transformed the RC problem into an optimal control (OC) problem by introducing a modified performance index function.…”

“…During the past few decades, many robust control (RC) methods have been developed for nonlinear systems in the control community. [1][2][3][4][5][6][7][8] Lin et al 2 transformed the RC problem into an optimal control (OC) problem by introducing a modified performance index function. To remove the requirement of knowing the system dynamics, Wang et al 3 extended this strategy to deal with uncertain nonlinear systems by employing model parameters learned on the input-output data.…”