Random nonlinear systems (RNSs) are claimed to be superior than well-investigated stochastic nonlinear systems (SNSs) in dealing with general noises. This brief considers the question of adaptive command filtered control… Click to show full abstract
Random nonlinear systems (RNSs) are claimed to be superior than well-investigated stochastic nonlinear systems (SNSs) in dealing with general noises. This brief considers the question of adaptive command filtered control (CFC) of a class of triangular RNSs under asymmetric output constraint. The constrained problem is turned into an unconstrained one by a nonlinear transformation at first. Then by combining CFC with adaptive technique, an adaptive controller is designed recursively to achieve the tracking objective, as well as keeping the output constraint. Finally, the validity of main results is tested via a numerical simulation example.
               
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