This paper explores automating the qualitative analysis of physical systems. It describes a program, called PLR, that takes parameterized ordinary differential equations as input and produces a qualitative description of the solutions for all initial values. PLR approximates intractable nonlinear systems with piecewise linear ones, analyzes the approximations, and draws conclusions about the original systems. It chooses approximations that are accurate enough to reproduce the essential properties of their nonlinear prototypes, yet simple enough to be analyzed completely and efficiently. It derives additional properties, such as boundedness or periodicity, by theoretical methods. I demonstrate PLR on several common nonlinear systems and on published examples from mechanical engineering.
Recommendations
Approximate solution of linear ordinary differential equations with variable coefficients
In this paper, a novel, simple yet efficient method is proposed to approximately solve linear ordinary differential equations (ODEs). Emphasis is put on second-order linear ODEs with variable coefficients. First, the ODE to be solved is transformed to ...
Finite difference approximations for two-sided space-fractional partial differential equations
Fractional order partial differential equations are generalizations of classical partial differential equations. Increasingly, these models are used in applications such as fluid flow, finance and others. In this paper we examine some practical ...
System of linear ordinary differential and differential-algebraic equations and pseudo-spectral method
In this paper, first we introduce, briefly, pseudo-spectral method to solve linear Ordinary Differential Equations (ODEs), and then extend it to solve a system of linear ODEs and then Differential-Algebraic Equations (DAEs). Furthermore, because of ...