What Is Optimization Toolbox?
What Is Optimization Toolbox? What Is Optimization Toolbox?
2 TutorialMinimization (Continued)Type Notation FunctionConstrained minimizationsuch thatfminconGoal attainmentfgoalattainsuch thatMinimaxsuch thatfminimaxSemi-infinite minimizationsuch thatfseminfBinary integer programmingbintprog2-4
IntroductionEquation SolvingType Notation FunctionLinear equations, n equations, n \ (matrix left division)variablesNonlinear equation of onevariableNonlinear equations, n equations, nvariablesfzerofsolveLeast-Squares (Curve Fitting)Type Notation FunctionLinear least-squares\ (matrix left, m equations, n variables division)Nonnegativelinear-least-squaressuch thatlsqnonnegConstrainedlinear-least-squaressuch thatlsqlinNonlinear least-squaressuch thatlsqnonlinNonlinear curve fittingsuch thatlsqcurvefit2-5
- Page 1 and 2: Optimization Toolbox 3User’s Guid
- Page 3: Revision HistoryNovember 1990 First
- Page 6 and 7: Acknowledgments
- Page 8 and 9: Nonlinear Equations with Finite-Dif
- Page 10 and 11: Quadratic Programming (QP) Subprobl
- Page 12 and 13: Specifying the Options ............
- Page 14 and 15: xivContents
- Page 16 and 17: 1 Getting StartedWhat Is Optimizati
- Page 18 and 19: 1 Getting StartedOptimization Examp
- Page 20 and 21: 1 Getting Started[x, fval] =lsqlin(
- Page 22 and 23: 2 TutorialLarge-Scale Examples (p.
- Page 26 and 27: 2 TutorialUsing the Optimization Fu
- Page 28 and 29: 2 TutorialA choice of line search s
- Page 30 and 31: 2 TutorialThe tutorial uses the fun
- Page 32 and 33: 2 Tutorialfunction evaluations. See
- Page 34 and 35: 2 TutorialTo restrict x inEquation2
- Page 36 and 37: 2 Tutorialceq=[];DCeq = [ ];G conta
- Page 38 and 39: 2 TutorialEquality Constrained Exam
- Page 40 and 41: 2 Tutorialfunction y = findzero(b,
- Page 42 and 43: 2 Tutorial3.7081Sharing Variables U
- Page 44 and 45: 2 Tutorialcomponents.');end% Evalua
- Page 46 and 47: 2 TutorialThe example produces the
- Page 48 and 49: 2 TutorialClosed-Loop ResponseThe p
- Page 50 and 51: 2 Tutorialfunction [Kp,Ki,Kd] = run
- Page 52 and 53: 2 TutorialThe resulting closed-loop
- Page 54 and 55: 2 Tutorialcalling the simulation tw
- Page 56 and 57: 2 TutorialThe last value shown in t
- Page 58 and 59: 2 TutorialStep 1: Write an M-file f
- Page 60 and 61: 2 TutorialLarge-Scale Examples•
- Page 62 and 63: 2 TutorialNote The following table
- Page 64 and 65: 2 TutorialLarge-Scale Problem Cover
- Page 66 and 67: 2 Tutorialoptimset('Display','iter'
- Page 68 and 69: 2 Tutorialeither) then, in this pro
- Page 70 and 71: 2 TutorialNonlinear Least-Squares w
- Page 72: 2 TutorialThe problem is to find x
IntroductionEquation SolvingType Notation FunctionLinear equations, n equations, n \ (matrix left division)variablesNonlinear equation of onevariableNonlinear equations, n equations, nvariablesfzerofsolveLeast-Squares (Curve Fitting)Type Notation FunctionLinear least-squares\ (matrix left, m equations, n variables division)Nonnegativelinear-least-squaressuch thatlsqnonnegConstrainedlinear-least-squaressuch thatlsqlinNonlinear least-squaressuch thatlsqnonlinNonlinear curve fittingsuch thatlsqcurvefit2-5
Change language