Abstract
This chapter discusses on simulation methods for dynamic models of both discrete and continuous-time systems. Simulation methods provide both a quantitative answer and a high degree of accuracy for differential problems. Almost any dynamic model that will occur in practical application can be simulated to a reasonable accuracy. By simulating dynamic models, accurate quantitative information about system behavior can be obtained. Though the primary drawback is its non-flexibility with sensitivity analysis, simulation method is the appropriate choice for problems that need quantitative solutions. The simplest method for solving systems of differential equations to any desired degree of accuracy is the Euler method. One of the variations of The Euler method is the Runge-Kutta method, which uses a more sophisticated interpolation between the variables. The chapter also explains the significance of Chaos dynamical systems that can give rise to exotic limit sets called fractals.
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