Atmospheric and Space Flight Dynamics: Modeling and by Ashish Tewari

By Ashish Tewari

Modern aerospace autos, reminiscent of the gap go back and forth, different release cars, and long-range ballistic missiles, don't discriminate among atmospheric and area flight. so much texts on flight dynamics, besides the fact that, make this man made contrast and as a result don't concurrently hide plane and spacecraft. Bridging this hole within the literature, Atmospheric and area Flight Dynamics is a unified presentation, demonstrating that the 2 disciplines have truly developed from an analogous set of actual principles.

Key features:

* creation to a extensive variety of contemporary issues in an obtainable, but mathematically rigorous presentation

* Many numerical examples and simulations using MATLAB® and Simulink® absolutely built-in during the work

* Simulations presented—usually no longer present in books at the similar topic—are either lifelike and instructive

* Examples let readers to simply construct their very own simulations for airplane, missiles, release automobiles, reentry cars, and spacecraft

* software program is used as an academic, hands-on software, relocating clear of the "cookbook" technique present in different works

* Supplementary fabric and MATLAB/Simulink code to be had at http://home.iitk.ac.in/~ashtew/index_files/page0009.htm

* quite a few illustrations and end-of-chapter exercises

* Separate options guide on hand to teachers upon request

Primarily beneficial as a textbook for complex undergraduate and starting graduate-level scholars, the paintings is usually an outstanding reference or self-study consultant for researchers and practitioners in aerospace engineering, aviation, mechanical engineering, dynamics, astrodynamics, aeronautics, and astronautics.

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Additional resources for Atmospheric and Space Flight Dynamics: Modeling and Simulation with MATLAB® and Simulink®

Example text

10 Summary The coordinates of a vector, A, can be resolved in various frames of reference, each of which consists of a right-handed triad formed by the unit vectors i, j, k. The transformation from a frame of reference to another (also called the attitude of a reference frame relative to another) involves an orthogonal rotation matrix, C, the elements of which can be represented by various alternative kinematic parameters, such as Euler angles, Euler axis/principal rotation, Euler symmetric parameters (quaternion), Rodrigues and modified Rodrigues parameters, etc.

50). Of course, the derivation given above is valid only if q4 = 0. 51) where 1√ 1 + c11 − c22 − c33 . 52) 2 Similarly, the two remaining alternative derivations of the quaternion from the rotation matrix involve division by q2 and q3 , respectively. Among all the four possible derivations, the greatest numerical accuracy is obtained for the one that has the largest denominator term, which implies the largest argument in the square root. 1. q1 = ± The quaternion is a compact, nonsingular representation of attitude that results in algebraic (rather than trigonometric) expressions for the elements of the rotation matrix.

10. There is no qualitative modification required in the above implemented Runge–Kutta approach (Appendix A) for solving the nonlinear differential equations when the angular velocity components are varying with time. 4. 5,-1];% angular velocity in rad/s xdot(1,1)=(sin(x(3))*w(1)+cos(x(3))*w(2))/sin(x(2)); xdot(2,1)=cos(x(3))*w(1)-sin(x(3))*w(2); xdot(3,1)=w(3)-(sin(x(3))*cos(x(2))*w(1)+cos(x(3))*cos(x(2))*w(2))/sin(x(2)); than the rotation matrix. However, it suffers from singularities and cannot be applied when principal rotations are larger than θ = 180◦ .

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