Continuous Simulation refers to a computer model of a physical system that executes continuously and changes over time according to a set of parameters.[1][2]
History
It is notable as one of the first uses ever put to computers, dating back to the Eniac in 1946. Continuous simulation allows prediction of rocket trajectories, hydrogen bomb dynamics (N.B. this is the first use ever put to the Eniac), electric circuit simulation[3], and robotics[4]. Established in 1952, The Society for Modeling & Simulation (SCS) is a nonprofit, volunteer-driven corporation dedicated to advancing the use of modeling & simulation to solve real-world problems. Their first publication strongly suggested that the Navy was wasting a lot of money through the inconclusive flight-testing of missiles, but that the Simulation Council's analog computer could provide better information through the simulation of flights. Since that time continuous simulation has been proven invaluable in military and private endeavors with complex systems. No Apollo moon shot would have been possible without it.
Modern applications
Continuous simulation is what you find inside WII stations, commercial flight simulators and jet plane auto pilots[5], and advanced engineering design tools[6]. Indeed, much of modern technology that we enjoy today (along with technology that can destroy the planet) would not be possible without continuous simulation.
Mathematical theory
In continuous simulation, the continuous time response of a physical system is modeled using ODEs.
Newton's 2nd law, F = ma, is a good example of a single ODE continuous system. Numerical integration methods such as Runge kutta, or Bulirsch-Stoer are used to solve the system of ODEs. By coupling the ODE solver with other numerical operators and methods a continuous simulator can be used to model many different physical phenomena such as flight dynamics, robotics, automotive suspensions, hydraulics, electric power, electric motors, human respiration, polar ice cap melting, steam power plants etc. There is virtually no limit to the kinds of physical phenomena that can be modeled by a system of ODE's. Some systems though can not have all derivative terms specified explicitly from known inputs and other ODE outputs. Those derivative terms are defined implicitly by other system constraints such as Kirchoff's law that flow of current into a junction must equal flow out. To solve these implicit ODE systems a converging iterative scheme such as Newton-Raphson must be employed.
Other types of simulation
References
- ^ Continuous Simulation description from University of Utrecht
- ^ Definition of Simulation with reference to "continuous simulation" at Encyclopedia.com
- ^ Electric circuit simulation from Memorial University Canada
- ^ "Intelligent Robotic Systems", pub. Springer Link ISBN:978-0-306-46062-3
- ^ http://dx.doi.org/10.1016/S0967-0661(99)00202-6 Robust sampled-data H∞-flight-controller design for high α stability-axis roll maneuver
- ^ VisSim Visual Simulation Language for Continuous Simulation and Model Based Development