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CSE245: Computer-Aided Circuit Simulation and Verification

CSE245: Computer-Aided Circuit Simulation and Verification. Lecture Note 5 Numerical Integration Spring 2010 Prof. Chung-Kuan Cheng. Numerical Integration: Outline. One-step Method for ODE (IVP) Forward Euler Backward Euler Trapezoidal Rule Equivalent Circuit Model Convergence Analysis

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CSE245: Computer-Aided Circuit Simulation and Verification

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  1. CSE245: Computer-Aided Circuit Simulation and Verification Lecture Note 5 Numerical Integration Spring 2010 Prof. Chung-Kuan Cheng

  2. Numerical Integration: Outline • One-step Method for ODE (IVP) • Forward Euler • Backward Euler • Trapezoidal Rule • Equivalent Circuit Model • Convergence Analysis • Linear Multi-Step Method • Time Step Control

  3. Ordinary Difference Equaitons N equations, n x variables, n dx/dt. Typically analytic solutions are not available  solve it numerically

  4. Numerical Integration • Forward Euler • Backward Euler • Trapezoidal

  5. Numerical Integration: State Equation • Forward Euler • Backward Euler

  6. Numerical Integration: State Equation • Trapezoidal

  7. Equivalent Circuit Model-BE • Capacitor + + + C - - -

  8. Equivalent Circuit Model-BE • Inductor + + - + L - -

  9. Equivalent Circuit Model-TR • Capacitor + + + C - - -

  10. Equivalent Circuit Model-TR • Inductor + + - + L - -

  11. Summary of Basic Concepts Trap Rule, Forward-Euler, Backward-Euler All are one-step methods xk+1 is computed using only xk, not xk-1, xk-2, xk-3... Forward-Euler is the simplest No equation solution explicit method. Backward-Euler is more expensive Equation solution each step implicit method most stable (FE/BE/TR) Trapezoidal Rule might be more accurate Equation solution each step implicit method More accurate but less stable, may cause oscillation

  12. Stabilities Froward Euler

  13. FE region of absolute stability Forward Euler ODE stability region Im(z) Difference Eqn Stability region Region of Absolute Stability Re(z) -1 1

  14. Stabilities Backward Euler

  15. BE region of absolute stability Backward Euler Im(z) Difference Eqn Stability region Re(z) -1 1 Region of Absolute Stability

  16. Stabilities Trapezoidal

  17. Convergence • Consistency: A method of order p (p>1) is consistent if • Stability: A method is stable if: • Convergence: A method is convergent if: Convergence Consistency + Stability

  18. A-Stable • Dahlqnest Theorem: • An A-Stable LMS (Linear MultiStep) method cannot exceed 2nd order accuracy • The most accurate A-Stable method (smallest truncation error) is trapezoidal method.

  19. Convergence Analysis: Truncation Error • Local Truncation Error (LTE): • At time point tk+1 assume xk is exact, the difference between the approximated solution xk+1 and exact solution x*k+1 is called local truncation error. • Indicates consistancy • Used to estimate next time step size in SPICE • Global Truncation Error (GTE): • At time point tk+1, assume only the initial condition x0 at time t0 is correct, the difference between the approximated solution xk+1 and the exact solution x*k+1 is called global truncation error. • Indicates stability

  20. LTE Estimation: SPICE • Taylor Expansion of xn+1 about the time point tn: • Taylor Expansion of dxn+1/dt about the time point tn: • Eliminate term in above two equations we get the trapezoidal rule LTE

  21. Time Step Control: SPICE • We have derived the local truncation error the unit is charge for capacitor and flux for inductor • Similarly, we can derive the local truncation error in terms of (1) the unit is current for capacitor and voltage for inductor • Suppose ED represents the absolute value of error that is allowed per time point. That is together with (1) we can calculate the time step as

  22. Time Step Control: SPICE (cont’d) • DD3(tn+1) is called 3rd divided difference, which is given by the recursive formula

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