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The designed methodology is particularly suited for the control of systems learned by recurrent neural networks (rnns), which are known for their enhanced modeling capabilities and for which the increm. In order to establish iss, we define an iss lyapunov function for a difference inclusion, similar to iss lyapunov function defined in jiang and wang (2001) and lazar, heemels, and teel (2013). This letter analyzes the stability properties of a nonlinear model predictive control (mpc) scheme for avoidance
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This control approach introduces an extra penalty for avoidance within the nonlinear tracking mpc framework. In this paper we are interested in stability issues and, therefore, we position our results only with respect to articles on (robust) stability of nonlinear mpc.
