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In this case a1 = grad u(M1 ) , a2 = grad u(M2 ) . We have

u =

 

1

 

 

 

 

y ,

 

 

u

=

 

1 x

,

 

u

= − 1

 

xy ,

x

2z x

 

 

y

 

 

2z y

 

 

 

 

z

 

 

z 2

 

 

a =

1

i +

1

 

j 2k

,

 

 

 

a = −

1

i

1

j k ;

 

 

 

 

 

 

 

 

1

 

2

 

 

 

2

 

 

 

 

 

 

 

 

 

 

 

2

 

 

 

2

 

2

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1

 

 

 

 

1

 

 

 

1

 

 

 

 

 

1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

+

 

 

 

 

 

 

 

 

 

2 (1)

 

 

 

 

 

 

 

 

2

2

2

 

 

 

1

 

cos ϕ =

 

 

 

 

 

 

 

 

 

 

 

2

 

 

 

 

=

.

 

 

 

 

 

 

 

 

 

 

 

1

+

1

 

+ 4

 

1

 

+

1

+ 1

 

 

3

Since

 

 

 

 

 

 

 

 

 

4

4

 

4

 

4

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1 .

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ϕ = arccos

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3

 

 

 

 

 

 

 

 

 

5. Examine z = x2 2y3 2x + 6y for relative extrema.

 

Solution. If we set

 

 

z

 

 

 

 

 

 

 

 

 

 

 

 

 

 

z

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

= 2x 2 and

 

 

 

= −6y 2 + 6 ,

 

 

 

 

 

 

x

 

y

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Then according to (2.11) we will have

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2x 2 = 0,

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2

+ 6 = 0.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6y

 

 

 

 

 

 

 

 

 

 

This gives x1,2 = 1 and y1,2 = ± 1. Thus M1 (1; 1)

and M 2 (1; 1) are the

critical points.

Now we apply the second-derivative test. Finding the partial derivatives of the second order for the given function:

 

2 z

= 2

,

 

2 z

= 0 ,

 

2 z

 

= −12 y .

 

x2

 

xy

 

y 2

 

 

 

 

 

 

 

 

 

At M1 (1; 1) ,

 

 

 

 

 

= 2 (12) 0 = −24 < 0 .

 

A = 2 , B = 0 ,

C = −12 ,

Since

< 0 , there is no relative extremum at M1 (1; 1) .

 

 

 

 

At M 2 (1; 1) ,

 

 

 

A = 2 , B = 0 , C = 12 ,

 

= 24 > 0 .

Since

> 0 and A > 0 , there is a relative minimum at M 2 (1; 1) . The

minimum output is obtained when x = 1 and y = - 1. At this point the value of the

function is zmin

= z(1; 1) = −3 .

6. Examine

z = x3 + xy 2 + x2 y for relative extrema.

 

41

Solution. Solving

zxzy

= 3x2 + y2 + 2xy = 0,

= 2xy + x2 = 0,

we get the critical point M (0; 0) . Now

2 z

= 6x + 2y ,

2 z

= 2y + 2x ,

2 z

= 2x .

x2

xy

y

2

 

 

 

 

At M (0; 0) all the second-order

derivatives are zero, hence

A = B = C = = 0 and the second-derivative test gives no information. However at M (0; 0) the value of the function is z(0; 0) = 0 .On a straight line y = 0 the

function z = x3 . For all x > 0

z(x;

0) = x3 > 0 , but if

x < 0 z(x, 0) = x3 < 0 .

Hence, a nearby point M (0; 0)

function has positive and negative values. There

is no relative extremum at M.

 

u = x2 + y 2 + 2z 2

 

7. Find the relative extrema of

subject to the constraint

x y + z = 1.

Solution. Transforming z, which is a function of three variables, into a function of two variables such that the new function reflects constraint x y + z = 1. Solving it for z, we get

z = 1x + y

which when substituted for x in u gives: u = x2 + y 2 + 2(1 x + y)2 .

Since u is now expressed as a function of two variables, to find relative extrema we follow the usual procedure of setting its partial derivatives equal to 0:

ux = 2x 4(1x + y) = 0 ;

x 2(1x + y) = 0,y + 2(1x + y) = 0;

 

u = 2y +4(1x + y) = 0 ;

 

y

 

y = − x,

x = 2 / 5,

 

5x = 2;

y = −2 / 5.

Hence the only critical point of u(x, y) subject to constraint x y + z = 1 is

 

2

 

2

 

M

 

;

 

.

5

5

 

 

 

By using the second-derivative test on u = x2 + y 2 + 2(1 x + y)2 at M, we

have:

 

 

 

 

 

 

 

 

2u

= 6

;

2u

= −4

;

2u

= 6

,

x2

xy

y 2

 

 

 

 

 

 

 

 

 

42

 

 

 

 

(M ) = 6 6 (4)2 = 20 > 0 and A = 2u = 6 > 0 .

x2

Computing z = 1 52 52 = 15 .

Thus the function u = x2 + y2 +2z2 , subject to the constraint, has a relative minimum at point M1 (0, 4; 0, 4; 0, 2) . At this point the value of the function is

umin = u(M1) = 0, 4 .

z = 3x + 2y3

 

 

 

 

8. Find the relative extrema of

subject to the constraint that x

and y must satisfy

 

x2

+ y2 = 1, x 0.

 

 

 

 

 

 

 

 

4

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Solution. Function z can be described parametrically:

 

 

 

 

 

 

 

 

 

 

π

 

π

 

 

 

 

 

x = 2 cos t , y = sin t , t

 

;

 

. Then we get

 

 

 

 

2

2

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

z(t) = 6 cos t + 2sin3 t .

 

To examine z(t) for relative extrema:

 

 

 

 

 

 

 

 

 

 

z(t) = −6sin t + 6sin 2 t cost = 3sin t(sin 2t 2) ;

 

 

 

 

 

sin t(sin 2t 2) = 0, sin t = 0,

 

t = πn, n Z .

 

 

 

π

 

π

 

 

 

 

 

 

 

For t

 

;

 

 

we have t = 0

. It is the only critical point. If t <

0, then z >

2

2

 

 

 

 

z(t) has a relative maximum at

t = 0 . We

0 and if t > 0, then z< 0. Hence

calculate xmax = 2 cos 0 = 2 , ymax = sin 0 = 0 and zmax = 6 .

 

Thus the function z = 3x + 2 y3 , subject to the constraint

x2

+ y 2

= 1, x 0 ,

 

has a relative maximum at (2; 0) .

 

 

 

 

4

 

 

 

 

 

 

 

 

 

 

9. Find

the

relative extrema of z = 8 2x 4y subject to the

constraint

x2 + 2y 2 12 = 0 .

Solution. The first step is to form a certain function by Lagrange. L = 8 2x 4y + λ(x2 + 2y 2 12) ,

Then compute the partial derivatives and find where they are all simultaneously 0:

 

L

= −2

+ 2λx =

0,

 

 

 

 

 

 

 

 

 

x

 

 

λx = 1,

x

= 1/ λ,

 

 

 

 

 

 

 

L

= −4

+ 4λy =

0,

 

 

λy = 1,

 

 

= 1/ λ,

 

y

 

 

y

 

 

 

 

 

 

2

+ 2 y

2

= 12;

 

2

= 1/ 4,

 

L

= x2

+ 2y2 12

=

x

 

 

λ

 

 

∂λ

0;

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

43

 

 

 

 

 

 

 

hence there are

two critical points

of z. If λ = 1/ 2 , then

λ = −1/ 2 , then

x = y = −2 . Thus at

M1 (2; 2) and M 2 (2;

relative maximum, a relative minimum, or neither of these. Using the second-derivative test we find d 2 L :

x = y = 2 and if 2) may exists a

 

 

 

 

 

 

2 L

= 2λ ;

2 L

= 4λ ;

2 L

= 0 ;

 

 

 

 

 

 

 

x2

y2

xy

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

d 2 L = 2λdx2 + 2 0dxdy + 4λdy2

= 2λ(dx2 + 2dy2 ) .

 

If λ = 1/ 2 then d 2 L > 0 , thus at M1 (2; 2)

there is provide the minimum of

z on the

circle x2 + 2y 2 12 = 0 ; if λ = −1/ 2

then d 2 L < 0 , namely

at

M 2 (2; 2) there is provide the maximum of z on the circle. Compute

 

 

 

 

 

zmin = z(2; 2) = −4 , zmax = z(2; 2) = 20 .

 

10. Find the largest and smallest values of a function z = x2 + xy + 2 y 2

on

a polygon D = {(x, y)

 

x 1, y x + 1, y

 

x

 

1} .

 

 

 

 

 

 

 

 

 

 

 

y

 

 

В

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2

 

 

 

 

Solution. Solving

 

 

 

 

 

 

 

 

 

 

 

 

1

D

 

 

 

 

 

 

z

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

А

 

 

 

 

 

x = 2x + y = 0,

x = 0,

 

 

 

 

 

 

 

 

 

–1 М

 

 

С x

 

 

z

 

 

 

 

 

 

 

 

 

1

 

 

 

= x + 4y = 0

y = 0,

 

 

y

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

–1

К

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Fig. 1.17

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

we get the critical point M (0; 0) which lies on D (fig. 1.17).

It is necessary to consider the behavior of z on the boundary of D, which consists of four edges labeled АВ, ВС, СК and КА.

On АВ: y = x + 1, x [1;1] . Thus, if (x, y) is on AB,

z = x2 + x(x + 1) + 2(x + 1)2 = 4x2 + 5x + 2 .

 

 

5

 

 

 

Since x goes from –– 1 to 1 on AB, the minimum of z on AB is at M1

 

 

3

 

,

 

.

 

 

 

 

 

 

 

 

 

 

8

 

8

On ВС: x = 1, y [0; 2] . Thus, if (x, y) is on BC,

 

 

 

 

 

 

 

z = 1+ y + 2 y2 .

 

 

 

 

 

The minimum of z is at y = −1/ 4 [0; 2] . In other words,

we

will not

consider M2(1; - 1 ), because it does not lie on BC .

 

 

 

 

 

4

 

 

 

 

 

44

 

 

 

 

 

On КС: y = x 1, x [0;1] . Thus, if (x, y) is on AB,

z = x2 + x(x 1) + 2(x 1)2 = 4x2 5x + 2 .

 

 

 

Since x goes from 0 to 1 on КС, the minimum of z on КС is at M2(

5

; -

3 ).

The last, on КА: y = − x 1, x [1; 0] . Thus, if (x, y) is on AB,

8

 

8

 

 

 

z = x2 + x(x 1) + 2(x 1)2 = 2x2 + 3x + 2 .

 

 

 

Since x goes from –– 1 to 0 on КА, the minimum of z on КА is at M3(-

3

; -

1 ).

4

 

 

4

Compute values of z(x, y) at points M, M1 , M 2 , M 3 , other at A, B,C and K: z(M ) = 0 , z(M1 ) = 7 /16 , z(M2 ) = 7 /16 , z(M 3 ) = 7 / 8 , z(A) = 1 ,

z(B) = 11 , z(C) = 1, z(K) = 2 .

Namely,

 

 

 

max z(x, y) = z(1; 2) = 11 ;

min z(x, y) = z(0; 0) = 0 .

 

 

 

 

D

 

D

 

 

 

Self-test and class assignments

 

Т.3

 

 

 

 

 

Find the equations of the tangent plane and normal line to the given

surface z(x, y)

at the given point М.

 

1.

z = x2 + 3y 2

, M (2,1) .

 

2.

sin 2 x + sin 2

y + cos2 z = 2 , M (π / 2, π / 4, π / 4) .

3.xyz = e x+ y+ z + 1, M (2,1,1) .

4.x2 3x + y2 + 2xy + 2xz 2zy + 2 = z2 , at the cross points with x –– axis.

5. Compute the directional derivative of u = xy 2 + z3 xyz at M (1; 1; 2)

in the direction of the vector consisting of x- and y-axes, the angles respectively

α = 60° and β = 45° .

6. Compute the directional derivative of

z = ln(x2 + y 2 )

at

M (2; 1) in the

direction from M to N (6; 4) .

 

 

 

 

 

7. Compute the directional derivative of

z = x2 3xy + 2y 2

at

M (1; 1)

in

the direction of its gradient.

 

 

 

 

 

8. Find a gradient of function u = ze xy+ 2z at point M (1; 0; 0) .

 

 

9. Find the points where a gradient of function z = ln(x y 1 )

is equal to

i + j .

 

 

 

 

 

10. Find an angle between the gradients of a function

z = arctg(x / y)

at

points M1 (1; 1) and M 2 (1; 1) .

 

 

 

 

 

45

 

 

 

 

 

Examine the given functions for relative extrema.

11.

z = x2

4xy + 5y 2 2x + 10y .

12.

z = x3 + 3xy 2 15x 12y .

13.

z = x2

+ xy + y 2 4 ln x 10 ln y .

14.

z = 2x4 + xy3 .

15.

z = x

1 + y + y 1 + x .

16.

z = e x2 y (5 2x + y) .

Find the relative extrema

of

the

given functions u(x, y, z) subject to the

given constraint f(x, y) = 0.

 

 

 

 

 

 

 

 

17.

u = x2 y 2 ,

if x + 2y 6 = 0 .

18.

u = xyz ,

if

 

x + y + z = 6 .

19.

u = 4x2 + y 2 ,

if

 

1

+

 

2

4 = 0 .

 

 

 

 

 

 

x

 

y

 

20.

u = xy 2 z 2 ,

if

 

x + 4y 2z 10 = 0 .

21.

u = 16 10x 24y ,

if

 

x2 + y 2

169 = 0 .

22.

u = 4x2 + 2y 2 + z 2 ,

if

 

x2 + y 2

+ z 2 1 = 0 .

Find the largest and smallest values of the given functions z(x, y) on the given polygons D.

23.

z = x 2 xy + y 2 3x + 3y , D = {(x, y)

 

 

 

x 0, y 0, x y 3} .

 

24.

z = x3 + y3 3x 9 y + 9 , D = {(x, y)

 

 

 

x

 

+

 

y

 

3} .

 

 

 

 

 

 

 

 

25.

z = 3x2 + 3y 2 x y , D = {(x, y)

 

 

x 5, y 0, y x 1}.

 

26.

z = 2x2 y x3 y x2 y 2 , D = {(x, y)

 

x 0, y 0, x + y 6} .

 

27.

z = 4 2x2 y 2 , D = {(x, y) y 0, y 1 x2 } .

Answers

1.

4x + 6y z 7 = 0 ,

x 2

=

y 1

=

z 7

.

 

 

2. y z = 0 ,

 

 

x − π / 2

=

y − π / 4

=

 

 

 

 

 

 

 

 

 

 

4

 

6

 

 

 

1

 

 

 

 

 

 

 

 

 

 

0

 

1

 

=

z − π / 4

.

3.

y + z + 2 = 0 ,

 

x 2

=

y + 1

 

=

z + 1

.

 

4.

M1(1;0;0), x y 2z 1 = 0,

 

1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0

 

 

3

 

 

 

 

3

 

 

 

 

 

 

 

 

 

 

 

 

 

x 1

=

y

 

=

z

;

M2 (2;0;0), x + 2y + 4z 2 = 0,

 

x 1

=

y

=

z

. 5. 5 або –6. 6. 22 / 25 .

 

 

1

 

2

 

1

 

2

4

 

1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

7.

2.

8.

gradu = ek .

9. (2; 1), (0; ––1). 10. 180° .

 

11. (–5;–3) is a point of the

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

46

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

relative minimum. 12. (2; 1) is a point of the relative minimum. (–2; –1) is a point of the relative maximum. 13. (1; 2) is a point of the relative minimum. 17.(–2; 14) –– point of

the relative minimum subject to the constraint. 18. umax = f(2, 2, 2) = 8. 21. (5; 12) is a point of the relative minimum subject to the constraint. (–5; –12) is a point of the relative

maximum subject to the constraint. 23. zmin = f (1; 1) = −3 ,

zmax = f (0; 0) = 4 .

24. zmin = f (3; 0) = −9 , zmax = f (3; 0) = 27 .

25.

zmin = f (1/ 6; 1/ 6) = −1/ 6,

zmax = f (5;

4) = 114.

26. zmin = 0, zmax = f (1; 0,5) = 0,25.

27. zmin = f (1; 0) = f (1; 0) = 2 , zmax = f (0;

0) = 4.

 

 

 

 

Individual tasks

 

 

 

Т.3

 

 

 

3.1. Find the equations of the tangent plane and the normal line to the given surface z(x, y) at the given point М.

3.1.1. z =

x2 + y

2

,

 

M (2;

2) .

3.1.2. z =

x2

xy + y 2

, M (1; 2) .

x3 + y3

 

 

 

 

x + y

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3.1.3. z = sin(exy 1) , M (1;1) .

3.1.4. z =

 

 

 

x

 

 

 

, M (2; 1) .

y(x + y)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3.1.5. z = 3 x2 + y2 +10, M (1; 4) .

3.1.6. z = ln(x2 y2 4), M(3;2).

3.1.7. z = arctg(ex22xy ) ,

M (2; 1) .

3.1.8. z = ex2 3xy+ 2 y2 ,

M (1;1) .

3.1.9. z =

(x y

2

)e

x

2 + y

,

M (1; 1) .

3.1.10. z = x

3

y

2

+ arctg

x

,М(1;1).

 

 

 

 

 

y

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3.1.11. z = (x2 + y 2 x)e xy , M (1; 0) .

3.1.12. z = arctg

 

x + y

, М(2;0).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

x y

 

 

3.1.13. z = x3 y2 + 3x + 2y , M (1; 2) .

3.1.14. z = 3 x4 + y4 + 10, (1;2).

3.1.15. z = 4 x3 xy + y3

, M (1; 1) .

3.1.16. z =

x xy + y

,

M (1; 0) .

 

 

 

 

 

 

 

 

 

 

 

 

 

x2 + y 2

 

 

3.1.17. z =

3.1.19. z =

3.1.21. z =

3.1.23. z =

x2

+ y 2

, M (1;1) .

3.1.18. z =

x y

, M (1;1) .

x3

+ y3

x3 + y3

 

 

 

e x2 xy+ y2 , M (1; 0) .

3.1.20. z =

3x2 y , M (2; 3) .

ln(2x2 7 y2 ) , M (2; 1) .

3.1.22. z =

5x2 + 4 y , M (2; 1) .

x2 + 2 y2 2x 1, M (2; 1) .

 

 

 

47

3.1.24.z = (x2 + 4xy y 2 3)3 , M (1;1) .

3.1.25.z = xy + x2 + y2 , M (3; 4) .

3.1.26.z = ln(x2 3xy + y 2 + 2) , M (2; 1) .

3.1.27.z = (x + 2 y) x2 + y2 , M (1; 0) .

 

 

 

 

π

 

π

3.1.28.

z = arctg(cos x +sin y) ,

M

 

 

;

 

.

3

 

 

 

 

 

6

3.1.29. z = 3 x2 + 3xy 4x + 3y 1,

M (1; 2) .

3.1.30.z = ln(x2 3xy y 2) , M (4; 1) .

3.2.Find the angle between the gradient of the given function u and v at the given point М.

3.2.1.

u = arctg( x / y) , v = ln(x 2 + y ) , M (1;1) .

3.2.2.

u = 3x2 + 4y2 + z2 , v = 4 2x + 5y + 3z , M (1;1; 3) .

3.2.3.u = arcsin(xy) , v = arccos(xy) , M (3;1/ 4) .

3.2.4.u = x3 y + xz 2 + y 2 z , v = xyz + yz 2 , M (1; 0;1) .

Find the angle between the gradient of a function u at points M1 and M2 .

3.2.5.u = xy 2 z 4 , M1 (1; 2;1) , M 2 (1; 1; 0) .

3.2.6.u = xy z 2 , M1 (4;1;1) , M 2 (1; 9; 1) .

3.2.7.u = 3 xy + 3 yz + 3 xz , M1 (1; 8;1) , M2 (1; 1; 1) .

3.2.8.u = arctg(x + y2 z) , M1 (1;1;1) , M 2 (0;1; 2) .

Compute the directional derivative of the given functions u at M1 in the direction from M1 to M2 .

3.2.9. u = x2 + xy + y3 , M1 (1; 0) , M 2 (2;1) .

3.2.10.u = ln(x2 3x + y2 ) , M1 (3; 1) , M 2 (2; 3) .

3.2.11.u = e x2 y (x + y)2 , M1 (0;1) , M 2 (1; 2) .

3.2.12. u = sin 2 x cos 2y , M1 (π / 4; π / 3) , M2 (π / 3; 0) .

Compute the directional derivative of u at M1 in the direction of its gradient at M1 .

3.2.13. u = 3 x + y 2 + z3 , M1 (3; 4; 2) .

48

3.2.14.

u = x2 + y 2

(x2 + z 2 )1/ 2 , M1 (3; 4; 4) .

3.2.15.

u = ln( xy +

yz ) , M1 (1; 4;1) .

3.2.16. u = arcctg(xy2 z) , M1 (1; 1; 2) .

Find gradu and | gradu | of u at М.

3.2.17. u = xy 2 z 3 + x ( yz)1 , M (1; 2; 2) .

3.2.18. u = xyz + x2 + y 2 + z 2 2 , M (1; 4;1) .

3.2.19.u = ln(x3 + y3 + z3 ) , M (1; 1; 2) .

3.2.20.u = x2 + y2 + z2 , M (6; 2; 3) . Find the points where gradu = a .

3.2.21.u = x2 + xy + yz + xz , a = 5i + 3 j + 2k .

3.2.22.u = x2 + y 2 + z 2 + 3xy + 2y + xz , a = −i + 4k .

3.2.23. u =

x3

+ xy 2 + z 2 , a = 4i + 4 j k .

 

3

 

3.2.24.u = x2 + 2 y2 z2 xy + 2x 4z , a = 5i + 2 j . Find the points where | gradu |= b .

3.2.25.u = ln(x2 + y 2 ) , b = 2 .

3.2.26.u = arctg xy , b = 3 .

3.2.27.u = x + 2y , b = 1 .

Find the directional derivative of u at M in the direction of its radius-vector.

3.2.28. u = arcsin

x

, M (1;1; 2) .

 

yz

 

3.2.29.u = x2 + y2 + z2 , M (1; 2; 2) .

3.2.30.u = ln sin(x + 2yz) , M (0; π / 6;1) .

3.3. Examine the given functions for relative extrema.

3.3.1. z = 4x +

y 2

+ 2y + y 2 .

3.3.2.

z = ln(xy) +

1

+

2

.

 

x

 

 

 

x

 

y

3.3.3. z = x2 + 8xy + 20y2 20y .

3.3.4. z = 3 + 6x x2 xy y2 .

 

 

 

49

 

 

 

 

 

3.3.5. z = ln(x4 y) +

1

+

1

3x .

 

 

 

 

 

x

y

3.3.7. z = 9x +

y 2

+ 6y + 3y 2 + 2 .

 

 

x

 

 

3.3.9. z = 27x3 + 18xy2 153x 72y .

3.3.11.

z = x4 + y 4 2x2 + 4xy 2y 2 .

3.3.13.

z = ex2 y2 (2x2 + y2 ) .

3.3.15.

z = x2 + xy + y2 6x 9 y .

3.3.17.

z = x2 + 5y 2 + 2x + 4xy 6 y .

3.3.19.

z = y

x 2y 2 x + 14y .

3.3.21.

z = 2y

3x 8y 2 3x + 28y .

3.3.23.

z = (x + y) ln(x + y) + x2 .

3.3.25.

z = (x + 2 y) ln(x + 2y) + 4y 2

3.3.27.

z = x3 + y3 3xy2 9x + 9 y .

3.3.19.

z = (x 2) y + 1 x2 + 4x y .

3.3.6. z = ln(xy2 ) + 5y + 6x . xy

3.3.8. z = 2x y + y + ln x + 1 . x

3.3.10. z = 3(x 1)(x + y) + y2 . 3.3.12. z = x(x + y + 1) + 3y2 . 3.3.14. z = 6x x2 xy y2 .

3.3.16. z = ln(x

2 y) +

4 y + 3x

.

 

 

 

 

 

 

 

 

xy

3.3.18.

z =

x2

x

1

2y .

4 y3

 

y

 

 

 

 

 

 

3.3.20.z = 9x + ( y 1)2 + 3y2 .

x1

3.3.22.z = x3 + 8y3 6xy + 3 .

3.3.24.z = xy(6 x y) .

3.3.26.z = 27x3 + 8y3 18xy .

3.3.28.z = x y x2 y + 6x .

3.3.30.z = 1 + 2y x2 2x . y y3

3.4. Find the largest and smallest values of the given functions z(x, y) on the given polygons D .

3.4.1. z = 3x2 + y2 2xy 4x,

,

 

 

 

 

 

 

 

= {(x, y)

 

1 x 2, 1 y x + 1} .

D

 

3.4.2. z = x3 12xy + y3 ,

 

 

= {(x, y)

 

0 x 4, 0 y 2} .

D

 

3.4.3. z = x2 2xy y2 + 4x ,

 

 

 

 

 

= {(x, y)

 

 

 

y 0, x ≥ −3, x + y ≤ −1} .

 

D

 

3.4.4. z = xy(3 x y) ,

 

= {(x, y)

 

x 0, y ≥ −2, x + y 6} .

D

 

3.4.5. z = x3

+ 3y 2 ,

 

 

 

 

 

x2 + y 2 4} .

 

 

= {(x, y)

 

 

D

 

3.4.6. z = x2

y2 + 3xy 5x y,

 

 

 

= {(x, y)

 

x 3,

y 2, 2x + y 0} .

 

 

D

 

3.4.7. z = x2

+ 2xy y 2 4x ,

 

 

 

 

={(x, y)

 

x 3,

y 0, y x +1} .

 

 

D

 

3.4.8. z = (x y)2 + y 2 + 2x ,

 

= {(x, y)

 

x 0, y 0, x + y + 4 0} .

D

 

 

 

 

 

 

 

 

 

 

 

 

 

50

 

 

 

 

 

 

 

 

 

 

 

 

 

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