Above are papers related to the following paper: [Paper_ID] Paper #103430. 	[Title] Input to State Stabilizability for Parameterized Families of Systems Key Words: Nonlinear stability, Robust control, [Abstract]  Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #1121569. 	[Title] A Characterization of Integral Input to State Stability [Abstract] Just as input to state stability (iss) generalizes the idea of finite gains with respect to supremum norms, the new notion of integral input to state stability (iiss) generalizes the concept of finite gain when using an integral norm on inputs. In this paper, we obtain a necessary and sufficient characterization of the iiss property, expressed in terms of dissipation inequalities. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #141171. 	[Title] New Characterizations of Input to State Stability [Abstract] We present new characterizations of the Input to State Stability property. As a consequence of these results, we show the equivalence between the ISS property and several (apparent) variations proposed in the literature. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #75318. 	[Title] A Smooth Converse Lyapunov Theorem for Robust Stability [Abstract] This paper presents a Converse Lyapunov Function Theorem motivated by robust control analysis and design. Our result is based upon, but generalizes, various aspects of well-known classical theorems. In a unified and natural manner, it (1) allows arbitrary bounded time-varying parameters in the system description, (2) deals with global asymptotic stability, (3) results in smooth (infinitely differentiable) Lyapunov functions, and (4) applies to stability with respect to not necessarily compact invariant sets. 1. Introduction. This work is motivated by problems of robust nonlinear stabilization. One of our main Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #1154074. 	[Title]  [Abstract] Report SYCON-93-09 Recent Results on Lyapunov-theoretic Techniques for Nonlinear Stability ABSTRACT This paper presents a Converse Lyapunov Function Theorem motivated by robust control analysis and design. Our result is based upon, but generalizes, various aspects of well-known classical theorems. In a unified and natural manner, it (1) includes arbitrary bounded disturbances acting on the system, (2) deals with global asymptotic stability, (3) results in smooth (infinitely differentiable) Lyapunov functions, and (4) applies to stability with respect to not necessarily compact invariant sets. As a corollary of the obtained Converse Theorem, we show that the well-known Lyapunov sufficient condition for "input-to-state stability" is also necessary, settling positively an open question raised by several authors during the past few years. Please summarise all the given information.

Paper #103430 has the title `Input to State Stabilizability for Parameterized Families of Systems Key Words: Nonlinear stability, Robust control,
` and the abstract `nan`.
Question: Which category should Paper #103430 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #103430 has the title `Input to State Stabilizability for Parameterized Families of Systems Key Words: Nonlinear stability, Robust control,
` and the abstract `nan`.
Question: Which category should Paper #103430 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].

This paper should be classified into: Neural_Networks