Skip to main content

Calculus III - 3-Dimensional Space: Equations of Lines

In this section we need to take a look at the equation of a line in  R 3 R 3 . As we saw in the previous section the equation  y = m x + b y = m x + b  does not describe a line in  R 3 R 3 , instead it describes a plane. This doesn’t mean however that we can’t write down an equation for a line in 3-D space. We’re just going to need a new way of writing down the equation of a curve. So, before we get into the equations of lines we first need to briefly look at vector functions. We’re going to take a more in depth look at vector functions later. At this point all that we need to worry about is notational issues and how they can be used to give the equation of a curve. The best way to get an idea of what a vector function is and what its graph looks like is to look at an example. So, consider the following vector function. → r ( t ) = ⟨ t , 1 ⟩ r → ( t ) = ⟨ t , 1 ⟩ A vector function is a function that takes one or more variables, one in this case, and returns a vector. Note as we

Differential Equations - First Order: Linear - i


Linear Differential Equations


The first special case of first order differential equations that we will look at is the linear first order differential equation. In this case, unlike most of the first order cases that we will look at, we can actually derive a formula for the general solution. The general solution is derived below. However, we would suggest that you do not memorize the formula itself. Instead of memorizing the formula you should memorize and understand the process that I'm going to use to derive the formula. Most problems are actually easier to work by using the process instead of using the formula.

So, let's see how to solve a linear first order differential equation. Remember as we go through this process that the goal is to arrive at a solution that is in the form y=y(t). It's sometimes easy to lose sight of the goal as we go through this process for the first time.
In order to solve a linear first order differential equation we MUST start with the differential equation in the form shown below. If the differential equation is not in this form then the process we’re going to use will not work.
(1)dydt+p(t)y=g(t)
Where both p(t) and g(t) are continuous functions. Recall that a quick and dirty definition of a continuous function is that a function will be continuous provided you can draw the graph from left to right without ever picking up your pencil/pen. In other words, a function is continuous if there are no holes or breaks in it.
Now, we are going to assume that there is some magical function somewhere out there in the world, μ(t), called an integrating factor. Do not, at this point, worry about what this function is or where it came from. We will figure out what μ(t) is once we have the formula for the general solution in hand.
So, now that we have assumed the existence of μ(t) multiply everything in (1) by μ(t). This will give.
(2)μ(t)dydt+μ(t)p(t)y=μ(t)g(t)
Now, this is where the magic of μ(t) comes into play. We are going to assume that whatever μ(t) is, it will satisfy the following.
(3)μ(t)p(t)=μ(t)
Again do not worry about how we can find a μ(t) that will satisfy (3). As we will see, provided p(t) is continuous we can find it. So substituting (3) we now arrive at.
(4)μ(t)dydt+μ(t)y=μ(t)g(t)
At this point we need to recognize that the left side of (4) is nothing more than the following product rule.
μ(t)dydt+μ(t)y=(μ(t)y(t))
So we can replace the left side of (4) with this product rule. Upon doing this (4) becomes
(5)(μ(t)y(t))=μ(t)g(t)
Now, recall that we are after y(t). We can now do something about that. All we need to do is integrate both sides then use a little algebra and we'll have the solution. So, integrate both sides of (5) to get.
(μ(t)y(t))dt=μ(t)g(t)dt(6)μ(t)y(t)+c=μ(t)g(t)dt
Note the constant of integration, c, from the left side integration is included here. It is vitally important that this be included. If it is left out you will get the wrong answer every time.
The final step is then some algebra to solve for the solution, y(t).
μ(t)y(t)=μ(t)g(t)dtcy(t)=μ(t)g(t)dtcμ(t)
Now, from a notational standpoint we know that the constant of integration, c, is an unknown constant and so to make our life easier we will absorb the minus sign in front of it into the constant and use a plus instead. This will NOT affect the final answer for the solution. So with this change we have.
(7)y(t)=μ(t)g(t)dt+cμ(t)
Again, changing the sign on the constant will not affect our answer. If you choose to keep the minus sign you will get the same value of c as we do except it will have the opposite sign. Upon plugging in c we will get exactly the same answer.
There is a lot of playing fast and loose with constants of integration in this section, so you will need to get used to it. When we do this we will always to try to make it very clear what is going on and try to justify why we did what we did.
So, now that we’ve got a general solution to (1) we need to go back and determine just what this magical function μ(t) is. This is actually an easier process than you might think. We’ll start with (3).
μ(t)p(t)=μ(t)
Divide both sides by μ(t),
μ(t)μ(t)=p(t)
Now, hopefully you will recognize the left side of this from your Calculus I class as nothing more than the following derivative.
(lnμ(t))=p(t)
As with the process above all we need to do is integrate both sides to get.
lnμ(t)+k=p(t)dtlnμ(t)=p(t)dt+k
You will notice that the constant of integration from the left side, k, had been moved to the right side and had the minus sign absorbed into it again as we did earlier. Also note that we’re using k here because we’ve already used c and in a little bit we’ll have both of them in the same equation. So, to avoid confusion we used different letters to represent the fact that they will, in all probability, have different values.
Exponentiate both sides to get μ(t) out of the natural logarithm.
μ(t)=ep(t)dt+k
Now, it’s time to play fast and loose with constants again. It is inconvenient to have the k in the exponent so we’re going to get it out of the exponent in the following way.
μ(t)=ep(t)dt+k=ekep(t)dtRecall xa+b=xaxb!
Now, let’s make use of the fact that k is an unknown constant. If k is an unknown constant then so is ek so we might as well just rename it k and make our life easier. This will give us the following.
(8)μ(t)=kep(t)dt
So, we now have a formula for the general solution, (7), and a formula for the integrating factor, (8). We do have a problem however. We’ve got two unknown constants and the more unknown constants we have the more trouble we’ll have later on. Therefore, it would be nice if we could find a way to eliminate one of them (we’ll not be able to eliminate both….).
This is actually quite easy to do. First, substitute (8) into (7) and rearrange the constants.
y(t)=kep(t)dtg(t)dt+ckep(t)dt=kep(t)dtg(t)dt+ckep(t)dt=ep(t)dtg(t)dt+ckep(t)dt
So, (7) can be written in such a way that the only place the two unknown constants show up is a ratio of the two. Then since both c and k are unknown constants so is the ratio of the two constants. Therefore we’ll just call the ratio c and then drop k out of (8) since it will just get absorbed into c eventually.
The solution to a linear first order differential equation is then
(9)y(t)=μ(t)g(t)dt+cμ(t)
where,
(10)μ(t)=ep(t)dt
Now, the reality is that (9) is not as useful as it may seem. It is often easier to just run through the process that got us to (9) rather than using the formula. We will not use this formula in any of out examples. We will need to use (10) regularly, as that formula is easier to use than the process to derive it.

Solution Process


The solution process for a first order linear differential equation is as follows.
  1. Put the differential equation in the correct initial form, (1).
  2. Find the integrating factor, μ(t), using (10).
  3. Multiply everything in the differential equation by μ(t) and verify that the left side becomes the product rule (μ(t)y(t)) and write it as such.
  4. Integrate both sides, make sure you properly deal with the constant of integration.
  5. Solve for the solution y(t).

Let’s work a couple of examples. Let’s start by solving the differential equation that we derived back in the Direction Field section.



Example 1 Find the solution to the following differential equation.dvdt=9.80.196v


First, we need to get the differential equation in the correct form.
dvdt+0.196v=9.8From this we can see that p(t)=0.196 and so μ(t) is then.
μ(t)=e0.196dt=e0.196tNote that officially there should be a constant of integration in the exponent from the integration. However, we can drop that for exactly the same reason that we dropped the k from (8).
Now multiply all the terms in the differential equation by the integrating factor and do some simplification.
e0.196tdvdt+0.196e0.196tv=9.8e0.196t(e0.196tv)=9.8e0.196tIntegrate both sides and don't forget the constants of integration that will arise from both integrals.
(e0.196tv)dt=9.8e0.196tdte0.196tv+k=50e0.196t+cOkay. It’s time to play with constants again. We can subtract k from both sides to get.
e0.196tv=50e0.196t+ckBoth c and k are unknown constants and so the difference is also an unknown constant. We will therefore write the difference as c. So, we now have
e0.196tv=50e0.196t+cFrom this point on we will only put one constant of integration down when we integrate both sides knowing that if we had written down one for each integral, as we should, the two would just end up getting absorbed into each other.
The final step in the solution process is then to divide both sides by e0.196t or to multiply both sides by e0.196t. Either will work, but we usually prefer the multiplication route. Doing this gives the general solution to the differential equation.
v(t)=50+ce0.196t

From the solution to this example we can now see why the constant of integration is so important in this process. Without it, in this case, we would get a single, constant solution, v(t)=50. With the constant of integration we get infinitely many solutions, one for each value of c.


Back in the direction field section where we first derived the differential equation used in the last example we used the direction field to help us sketch some solutions. Let's see if we got them correct. To sketch some solutions all we need to do is to pick different values of c to get a solution. Several of these are shown in the graph below.
So, it looks like we did pretty good sketching the graphs back in the direction field section.
Now, recall from the Definitions section that the Initial Condition(s) will allow us to zero in on a particular solution. Solutions to first order differential equations (not just linear as we will see) will have a single unknown constant in them and so we will need exactly one initial condition to find the value of that constant and hence find the solution that we were after. The initial condition for first order differential equations will be of the form
y(t0)=y0
Recall as well that a differential equation along with a sufficient number of initial conditions is called an Initial Value Problem (IVP).




Example 2 Solve the following IVP.dvdt=9.80.196vv(0)=48


To find the solution to an IVP we must first find the general solution to the differential equation and then use the initial condition to identify the exact solution that we are after. So, since this is the same differential equation as we looked at in Example 1,we already have its general solution.
v=50+ce0.196tNow, to find the solution we are after we need to identify the value of c that will give us the solution we are after. To do this we simply plug in the initial condition which will give us an equation we can solve for c. So, let's do this
48=v(0)=50+cc=2So, the actual solution to the IVP is.
v=502e0.196tA graph of this solution can be seen in the figure above.
Let’s do a couple of examples that are a little more involved.




Example 3 Solve the following IVP.cos(x)y+sin(x)y=2cos3(x)sin(x)1y(π4)=32,0x<π2


Rewrite the differential equation to get the coefficient of the derivative a one.
y+sin(x)cos(x)y=2cos2(x)sin(x)1cos(x)y+tan(x)y=2cos2(x)sin(x)sec(x)Now find the integrating factor.
μ(t)=etan(x)dx=eln|sec(x)|=elnsec(x)=sec(x)Can you do the integral? If not rewrite tangent back into sines and cosines and then use a simple substitution. Note that we could drop the absolute value bars on the secant because of the limits on x. In fact, this is the reason for the limits on x. Note as well that there are two forms of the answer to this integral. They are equivalent as shown below. Which you use is really a matter of preference.
tan(x)dx=ln|cos(x)|=ln|cos(x)|1=ln|sec(x)|Also note that we made use of the following fact.
(11)elnf(x)=f(x)This is an important fact that you should always remember for these problems. We will want to simplify the integrating factor as much as possible in all cases and this fact will help with that simplification.
Now back to the example. Multiply the integrating factor through the differential equation and verify the left side is a product rule. Note as well that we multiply the integrating factor through the rewritten differential equation and NOT the original differential equation. Make sure that you do this. If you multiply the integrating factor through the original differential equation you will get the wrong solution!
sec(x)y+sec(x)tan(x)y=2sec(x)cos2(x)sin(x)sec2(x)(sec(x)y)=2cos(x)sin(x)sec2(x)Integrate both sides.
(sec(x)y(x))dx=2cos(x)sin(x)sec2(x)dxsec(x)y(x)=sin(2x)sec2(x)dxsec(x)y(x)=12cos(2x)tan(x)+cNote the use of the trig formula sin(2θ)=2sinθcosθ that made the integral easier. Next, solve for the solution.
y(x)=12cos(x)cos(2x)cos(x)tan(x)+ccos(x)=12cos(x)cos(2x)sin(x)+ccos(x)Finally, apply the initial condition to find the value of c.
32=y(π4)=12cos(π4)cos(π2)sin(π4)+ccos(π4)32=22+c22c=7The solution is then.
y(x)=12cos(x)cos(2x)sin(x)+7cos(x)Below is a plot of the solution.




Comments

Popular posts from this blog

Digital Signal Processing - Basic Continuous Time Signals

To test a system, generally, standard or basic signals are used. These signals are the basic building blocks for many complex signals. Hence, they play a very important role in the study of signals and systems. Unit Impulse or Delta Function A signal, which satisfies the condition,   δ ( t ) = lim ϵ → ∞ x ( t ) δ ( t ) = lim ϵ → ∞ x ( t )   is known as unit impulse signal. This signal tends to infinity when t = 0 and tends to zero when t ≠ 0 such that the area under its curve is always equals to one. The delta function has zero amplitude everywhere except at t = 0. Properties of Unit Impulse Signal δ(t) is an even signal. δ(t) is an example of neither energy nor power (NENP) signal. Area of unit impulse signal can be written as; A = ∫ ∞ − ∞ δ ( t ) d t = ∫ ∞ − ∞ lim ϵ → 0 x ( t ) d t = lim ϵ → 0 ∫ ∞ − ∞ [ x ( t ) d t ] = 1 Weight or strength of the signal can be written as; y ( t ) = A δ ( t ) y ( t ) = A δ ( t ) Area of the weighted impulse signal can

Differential Equations - First Order: Bernoulli

In this section we are going to take a look at differential equations in the form, y ′ + p ( x ) y = q ( x ) y n y ′ + p ( x ) y = q ( x ) y n where  p ( x ) p ( x )  and  q ( x ) q ( x )  are continuous functions on the interval we’re working on and  n n  is a real number. Differential equations in this form are called  Bernoulli Equations . First notice that if  n = 0 n = 0  or  n = 1 n = 1  then the equation is linear and we already know how to solve it in these cases. Therefore, in this section we’re going to be looking at solutions for values of  n n  other than these two. In order to solve these we’ll first divide the differential equation by  y n y n  to get, y − n y ′ + p ( x ) y 1 − n = q ( x ) y − n y ′ + p ( x ) y 1 − n = q ( x ) We are now going to use the substitution  v = y 1 − n v = y 1 − n  to convert this into a differential equation in terms of  v v . As we’ll see this will lead to a differential equation that we can solve. We are going to have to be c

Differential Equations - Systems: Solutions

Now that we’ve got some of the basics out of the way for systems of differential equations it’s time to start thinking about how to solve a system of differential equations. We will start with the homogeneous system written in matrix form, → x ′ = A → x (1) (1) x → ′ = A x → where,  A A  is an  n × n n × n  matrix and  → x x →  is a vector whose components are the unknown functions in the system. Now, if we start with  n = 1 n = 1 then the system reduces to a fairly simple linear (or separable) first order differential equation. x ′ = a x x ′ = a x and this has the following solution, x ( t ) = c e a t x ( t ) = c e a t So, let’s use this as a guide and for a general  n n  let’s see if → x ( t ) = → η e r t (2) (2) x → ( t ) = η → e r t will be a solution. Note that the only real difference here is that we let the constant in front of the exponential be a vector. All we need to do then is plug this into the differential equation and see what we get. First notice that

Calculus III - 3-Dimensional Space: Equations of Lines

In this section we need to take a look at the equation of a line in  R 3 R 3 . As we saw in the previous section the equation  y = m x + b y = m x + b  does not describe a line in  R 3 R 3 , instead it describes a plane. This doesn’t mean however that we can’t write down an equation for a line in 3-D space. We’re just going to need a new way of writing down the equation of a curve. So, before we get into the equations of lines we first need to briefly look at vector functions. We’re going to take a more in depth look at vector functions later. At this point all that we need to worry about is notational issues and how they can be used to give the equation of a curve. The best way to get an idea of what a vector function is and what its graph looks like is to look at an example. So, consider the following vector function. → r ( t ) = ⟨ t , 1 ⟩ r → ( t ) = ⟨ t , 1 ⟩ A vector function is a function that takes one or more variables, one in this case, and returns a vector. Note as we

Digital Signal Processing - Miscellaneous Signals

There are other signals, which are a result of operation performed on them. Some common type of signals are discussed below. Conjugate Signals Signals, which satisfies the condition  x ( t ) = x ∗ ( − t ) are called conjugate signals. Let  x ( t ) = a ( t ) + j b ( t ) So,  x ( − t ) = a ( − t ) + j b ( − t ) And  x ∗ ( − t ) = a ( − t ) − j b ( − t ) By Condition,  x ( t ) = x ∗ ( − t ) If we compare both the derived equations 1 and 2, we can see that the real part is even, whereas the imaginary part is odd. This is the condition for a signal to be a conjugate type. Conjugate Anti-Symmetric Signals Signals, which satisfy the condition  x ( t ) = − x ∗ ( − t ) are called conjugate anti-symmetric signal Let  x ( t ) = a ( t ) + j b ( t ) So  x ( − t ) = a ( − t ) + j b ( − t ) And  x ∗ ( − t ) = a ( − t ) − j b ( − t ) − x ∗ ( − t ) = − a ( − t ) + j b ( − t ) By Condition  x ( t ) = − x ∗ ( − t ) Now, again compare, both the equations just as w

Differential Equations - First Order: Modeling - i

We now move into one of the main applications of differential equations both in this class and in general. Modeling is the process of writing a differential equation to describe a physical situation. Almost all of the differential equations that you will use in your job (for the engineers out there in the audience) are there because somebody, at some time, modeled a situation to come up with the differential equation that you are using. This section is not intended to completely teach you how to go about modeling all physical situations. A whole course could be devoted to the subject of modeling and still not cover everything! This section is designed to introduce you to the process of modeling and show you what is involved in modeling. We will look at three different situations in this section : Mixing Problems, Population Problems, and Falling Objects. In all of these situations we will be forced to make assumptions that do not accurately depict reality in most cases, but wi

Differential Equations - Basic Concepts: Definitions

Differential Equation The first definition that we should cover should be that of  differential equation . A differential equation is any equation which contains derivatives, either ordinary derivatives or partial derivatives. There is one differential equation that everybody probably knows, that is Newton’s Second Law of Motion. If an object of mass  m m  is moving with acceleration  a a  and being acted on with force  F F  then Newton’s Second Law tells us. F = m a (1) (1) F = m a To see that this is in fact a differential equation we need to rewrite it a little. First, remember that we can rewrite the acceleration,  a a , in one of two ways. a = d v d t OR a = d 2 u d t 2 (2) (2) a = d v d t OR a = d 2 u d t 2 Where  v v  is the velocity of the object and  u u  is the position function of the object at any time  t t . We should also remember at this point that the force,  F F  may also be a function of time, velocity, and/or position. So, with all these things in

Differential Equations - Partial: Summary of Separation of Variables

Throughout this chapter we’ve been talking about and solving partial differential equations using the method of separation of variables. However, the one thing that we’ve not really done is completely work an example from start to finish showing each and every step. Each partial differential equation that we solved made use somewhere of the fact that we’d done at least part of the problem in another section and so it makes some sense to have a quick summary of the method here. Also note that each of the partial differential equations only involved two variables. The method can often be extended out to more than two variables, but the work in those problems can be quite involved and so we didn’t cover any of that here. So with all of that out of the way here is a quick summary of the method of separation of variables for partial differential equations in two variables. Verify that the partial differential equation is linear and homogeneous. Verify that the boundary condi

Differential Equations - Systems: Repeated Eigenvalues - i

This is the final case that we need to take a look at. In this section we are going to look at solutions to the system, → x ′ = A → x x → ′ = A x → where the eigenvalues are repeated eigenvalues. Since we are going to be working with systems in which  A A  is a  2 × 2 2 × 2  matrix we will make that assumption from the start. So, the system will have a double eigenvalue,  λ λ . This presents us with a problem. We want two linearly independent solutions so that we can form a general solution. However, with a double eigenvalue we will have only one, → x 1 = → η e λ t x → 1 = η → e λ t So, we need to come up with a second solution. Recall that when we looked at the double root case with the second order differential equations we ran into a similar problem. In that section we simply added a  t t  to the solution and were able to get a second solution. Let’s see if the same thing will work in this case as well. We’ll see if → x = t e λ t → η x → = t e λ t η → will also be a

Differential Equations - First Order: Modeling - ii

Example 4  A 50 kg object is shot from a cannon straight up with an initial velocity of 10m/s off a bridge that is 100 meters above the ground. If air resistance is given by 5 v v  determine the velocity of the mass when it hits the ground. First, notice that when we say straight up, we really mean straight up, but in such a way that it will miss the bridge on the way back down. Here is a sketch of the situation. Notice the conventions that we set up for this problem. Since the vast majority of the motion will be in the downward direction we decided to assume that everything acting in the downward direction should be positive. Note that we also defined the “zero position” as the bridge, which makes the ground have a “position” of 100. Okay, if you think about it we actually have two situations here. The initial phase in which the mass is rising in the air and the second phase when the mass is on its way down. We will need to examine both situations and set up an IVP for