A thermostat that reacts to a temperature measured a minute ago, or a controller that acts on an old reading, changes the system according to where it was rather than where it is. Throughout, is the independent variable and . A delay changes the familiar questions of how much initial data is enough, how a solution is built and when it is stable. This lesson answers them with a history function, the method of steps and the characteristic roots of a delay equation.
Key terms
Delay differential equation
Definition A delay differential equation with a constant delay has the form
so the rate of change at time depends on the state at the earlier time , and possibly on the present state too. The expression is the value of at the time , not the number . An equation of this kind, in which the derivative appears only at the present time, is called retarded. Equations with several delays, with a delay that depends on the state, or with delayed derivatives also occur, and they need more careful treatment.
In plain words The equation reacts to old information. To know how fast changes now, look back one delay and see what was then.
Example For the delay is , and the rate at time is minus the value one time unit earlier. A delay lets even a single first-order equation oscillate. The function solves
because the delayed value is , so the right side equals , which is . An autonomous equation without delay and with Lipschitz cannot do this. A nonconstant solution of it never has , since at a time with zero slope it would meet an equilibrium solution and, by uniqueness, coincide with it. So it is strictly monotone.
History function
Definition For with initial time , a history function is a continuous function on , and the initial condition is for . A solution on with is a continuous function that equals on the history interval, is differentiable on with a right derivative at , and satisfies the equation for . The value alone is not enough data, because for the equation uses the values of at the times of . The solution is usually not differentiable at itself, since its right derivative comes from the equation and its left derivative from the history.
In plain words Before the clock starts, the whole past window of length must be prescribed. The present value is only the last point of that window.
Example For with , the rate at uses and the rate at uses . For integration gives
The histories and on share the value . They give and on , so but . This is not a failure of uniqueness. The two problems have different initial data, because the data are whole functions.
Method of steps
Definition Let be constant and continuous on . For the delayed time lies in , where is known, so there the delay equation reduces to the ordinary initial-value problem
Once is known on , the same reasoning gives an ordinary problem on , whose initial value comes from the previous step, and so on forward in time. If is continuous and locally Lipschitz in its second argument, each step has a unique solution near its starting time, so the delay problem has a unique solution on some interval . For a linear equation with continuous coefficients, each step is a linear equation that can be solved on the whole step, so the solution exists for all . When does not depend on , each step is a single integration. For with , a jump in at reappears as a jump in at , in at , and so on, while the lower derivatives are continuous there.
In plain words March forward one delay at a time. On each new step the delayed values belong to the piece already built, so they are a known function, and the delay equation becomes an ordinary one.
Example For with the history on , the first step gives on , so . On the delayed value is , so with , and for
Both pieces give and , and . The constant is fixed by the joining value, not chosen freely. Smoothness changes at the joins. At the history has slope while the solution starts with slope , so the graph has a corner. At the first derivatives agree, but the second derivative is on the left and on the right. A third step gives
on , with .
Infinite-dimensional state
Definition For a delay equation with constant delay , the state at time is the segment of the solution over the last delay interval, defined by for . With a continuous history, every segment belongs to the space of continuous functions on . Under the hypotheses of the method of steps, the segment at any time determines the solution at all later times for which it exists, just as the history did at . The space is infinite-dimensional, since the functions on it are linearly independent. For a system of first-order ordinary differential equations the state is a point of , but for a delay equation no finite list of numbers can play that role in general.
In plain words To predict a delay system you must remember a whole stretch of its past, and that memory slides forward as time goes on. A stretch of curve carries more information than any finite set of numbers.
Example For the formula of the history card gives
so the value at depends on the average of the whole history. The histories all have , and they give , so the present value allows every real number at . Values at any finite set of past times fix nothing either, because adding a continuous bump that vanishes at those times can change the integral by any prescribed amount. The exponential solutions show the size of the state space too. Each root of the characteristic equation below gives a solution , there are infinitely many roots, and exponentials with distinct exponents are linearly independent.
Characteristic roots of a delay equation
Definition For with real constants and , substituting with complex and canceling the nonzero factor gives the characteristic equation
Each root gives the solution , and for a complex root its real and imaginary parts are real solutions. Since also appears in an exponent, the left side is not a polynomial. The equation has infinitely many complex roots, because multiplying by turns it into with , whose solutions are the values at of the infinitely many branches of the Lambert W function. Only finitely many roots lie in any half-plane , because such a root satisfies . The stability theorem for linear retarded equations with constant coefficients states that if every root has , then every solution, for every continuous history, tends to exponentially, and that if some root has , some solutions grow exponentially. For the equation is , and is its only root, so the condition matters.
In plain words A linear system of ordinary differential equations has finitely many characteristic roots, as many as the dimension of its state. A delay equation has infinitely many, matching its infinite-dimensional state, and the rightmost ones decide whether solutions grow or decay.
Example For and the characteristic equation is . It has no real root, because has its smallest value . Its rightmost roots are approximately
and the others lie further left. All real parts are negative, so every solution of tends to exponentially. The slowest modes decay like while oscillating with angular frequency about . The values , and found by the method of steps from the history show the start of such a decaying oscillation. For , real roots exist exactly when , because the function has smallest value on the real line.
Delay-induced instability
Definition Delay-induced instability is the loss of stability of an equilibrium when a feedback that is stabilizing without delay acts with a large enough delay. For with , the equation without delay is , whose solutions decay. With a delay , the zero solution is asymptotically stable exactly when . If , no root has . Indeed, a root with would satisfy , so and , while the real part of the characteristic equation says
a contradiction. By the stability theorem every solution then decays exponentially. A root on the imaginary axis needs and , which first happens at and . Differentiating the characteristic equation with respect to gives
whose real part at , is , so the pair moves into the right half-plane as increases. Further crossings occur only at , all of them to the right, and a root with always satisfies , so no root can arrive in that half-plane from infinity. Hence some root has for every .
In plain words Feedback that corrects a deviation is stabilizing when it acts on fresh information. If it acts on old information, it keeps pushing after the deviation has already reversed, and with a long enough delay the corrections overshoot more and more.
Example The threshold case , is the equation of the first card, and its solution oscillates forever with constant amplitude, so the solutions do not all decay. For and , so that , the rightmost roots are about , and solutions started from the history oscillate with amplitude growing roughly like . This crossing is a statement about the linear equation. It does not by itself prove that a nonlinear system with delayed feedback settles onto a periodic orbit, which needs a separate nonlinear analysis.
Check yourself
- Use the method of steps to solve with the history on for , and find .
Show the answer
On the delayed value is , so with , and , which gives . On the delayed value is , so with . Integrating gives, for ,
At the join both pieces have value and slope . Finally .
- A classmate says that with has exactly one solution for . Test the claim with the histories and on . Does the result contradict uniqueness?
Show the answer
Both histories have the value at . The history gives on . For , the formula gives
It solves the equation, since and . Now while , so the same point value leads to different futures and the claim is false. There is no contradiction with uniqueness, because the problem with only is not a complete initial-value problem. With each full history the method of steps gives exactly one solution.
- Without delay, makes every solution decay. The same feedback with a delay gives . For which delays do all solutions decay? Check that is a solution at the threshold delay, and say what happens for slightly larger delays.
Show the answer
Here , so all solutions decay exactly when , that is, for . At ,
which is the derivative of , so this solution oscillates with constant amplitude and does not decay. As passes , the roots move to the right with , so for slightly larger delays some solutions are growing oscillations, and the same is true for every . The stability of says nothing about the delayed equation, which is the common mistake this question tests.