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This limits its wide application to interval dynamic systems.
Interval dynamic response analysis of vehicle-bridge interaction system with uncertain parameters is studied in this paper.
Huang et al. ([1994a]) developed an interval dynamic programming (GDP) method for waste management, which couples interval linear programming with dynamic programming.
Interval dynamic equations of the geared system are solved by use of the CIM in combination with the variable-step Runge-Kutta numerical integration method.
Combining the interval extension of function with the perturbation theory of dynamic response, the method for interval dynamic response analysis is derived.
Thus, in this paper we probe into the existence and uniqueness of the solutions for a class of semi-linear interval dynamic systems, after developing a complete normed quasi-linear space.
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In the simulation, we consider an 18-interval dynamic game for simulations.
In the proposed method, the inversion of the invertible sub-interval dynamic stiffness matrix is approximated by a modified approximate interval-value Sherman Morrison Woodbury formula to overcome the drawbacks arising from the dependency phenomenon of parameters and the unpredictable effect of neglecting the higher order terms in Neumann series.
This election can be made permanent (static clustering) or repeated in some certain time intervals (dynamic clustering).
Summarizing, interval differential dynamic systems are a still open research topic in the context of differential dynamic systems.
Moreover, uncertainty analysis was conducted to give an interval of dynamic response of SHPB tests based on a non-probabilistic interval analysis method.
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