Advanced Dynamic-system Simulation: Model-replication by Granino A. Korn PDF
By Granino A. Korn
Research the most recent recommendations in programming refined simulation structures. This state of the art textual content offers the newest innovations in complicated simulation programming for interactive modeling and simulation of dynamic platforms, akin to aerospace autos, keep watch over platforms, and organic structures. the writer, a number one authority within the box, demonstrates software program that could deal with huge simulation reviews on common own desktops.
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Extra info for Advanced Dynamic-system Simulation: Model-replication Techniques and Monte Carlo Simulation
The simulated rudder deflection rudder is bounded between – rumax and rumax with the limiter function sat() (Section 2-8a), which follows a step statement to ensure correct integration (Section 2-11). Finally, the display command DISPXY x, y, xt, yt calls for simultaneous displays of the missile and target trajectories (y versus x and yt versus xt). Alternative display statements can plot time histories of phi, psi, error, and rudder (Fig. 1-9b). The simulation program can be loaded from a file or an editor window.
Dispxy x, xdot displays xdot versus x (phase-plane plot). Model and display are exercised by the experiment-protocol script preceding the DYNAMIC statement. Successive experiment-protocol lines specify • display colors and curve thickness • the runtime TMAX, the integration step DT, and the number NN of dis- play points • a model parameter ww • the initial value of the state variable x Initial values of time t and of the state variable xdot are not specified and default to 0. The integration routine defaults to a fixed-step second-order Runge–Kutta rule.
A) Limiter Functions lim(x) is a simple unit-gain limiter or half-wave rectifier (see also Section 2-13). The unit-gain saturation limiter sat(x) limits its output between –1 and 1, and SAT(x) limits its output between 0 and 1. More general unit-gain saturation lim- iters are obtained with (limits between – a and a > 0) y = a * sat(x/a) y = lim(x – min) – lim(x – max) (2-3) (limits between min and max > min) (2-4) It is possible to approximate any reasonable continuous function of x as a sum of simple limiter functions, a0 + a1 * lim(x – x1) + a2 * lim(x – x2) + … (2-5) (b) Switching Functions and Comparators The switch function swtch(x – a) in Figure 2-5b switches between 0 and 1 when x = a (see also Section 2-16).
Advanced Dynamic-system Simulation: Model-replication Techniques and Monte Carlo Simulation by Granino A. Korn