Unit 13, lesson 77

Delay Differential Equations

Why a delay differential equation needs a whole history function as initial data, how the method of steps builds its solution, why its state is infinite-dimensional, and how characteristic roots reveal delay-induced instability.

  • Video 77
  • Perturbation, Delay and Differential-Algebraic Equations

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, tt is the independent variable and y′=dy/dty' = dy/dt. 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 τ>0\tau > 0 has the form

y′(t)=f(t,y(t),y(t−τ)),y'(t) = f\bigl(t, y(t), y(t - \tau)\bigr),

so the rate of change at time tt depends on the state at the earlier time t−τt - \tau, and possibly on the present state too. The expression y(t−τ)y(t - \tau) is the value of yy at the time t−τt - \tau, not the number y(t)−τy(t) - \tau. 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 yy changes now, look back one delay and see what yy was then.

Example For y′(t)=−y(t−1)y'(t) = -y(t - 1) the delay is 11, and the rate at time tt is minus the value one time unit earlier. A delay lets even a single first-order equation oscillate. The function y=sin⁡(πt/2)y = \sin(\pi t/2) solves

y′(t)=−π2 y(t−1),y'(t) = -\frac{\pi}{2}\,y(t - 1),

because the delayed value is y(t−1)=sin⁡(πt/2−π/2)=−cos⁡(πt/2)y(t - 1) = \sin(\pi t/2 - \pi/2) = -\cos(\pi t/2), so the right side equals π2cos⁡(πt/2)\tfrac{\pi}{2}\cos(\pi t/2), which is y′(t)y'(t). An autonomous equation y′=g(y)y' = g(y) without delay and with gg Lipschitz cannot do this. A nonconstant solution of it never has y′=0y' = 0, 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 y′(t)=f(t,y(t),y(t−τ))y'(t) = f(t, y(t), y(t - \tau)) with initial time t0t_0, a history function is a continuous function φ\varphi on [t0−τ,t0][t_0 - \tau, t_0], and the initial condition is y(t)=φ(t)y(t) = \varphi(t) for t0−τ≤t≤t0t_0 - \tau \le t \le t_0. A solution on [t0−τ,t0+β)[t_0 - \tau, t_0 + \beta) with β>0\beta > 0 is a continuous function that equals φ\varphi on the history interval, is differentiable on (t0,t0+β)(t_0, t_0 + \beta) with a right derivative at t0t_0, and satisfies the equation for t0≤t<t0+βt_0 \le t < t_0 + \beta. The value φ(t0)\varphi(t_0) alone is not enough data, because for t0≤t<t0+τt_0 \le t < t_0 + \tau the equation uses the values of yy at the times of [t0−τ,t0)[t_0 - \tau, t_0). The solution is usually not differentiable at t0t_0 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 τ\tau must be prescribed. The present value is only the last point of that window.

Example For y′(t)=−y(t−1)y'(t) = -y(t - 1) with t0=0t_0 = 0, the rate at t=0t = 0 uses y(−1)y(-1) and the rate at t=12t = \tfrac{1}{2} uses y(−12)y(-\tfrac{1}{2}). For 0≤t≤10 \le t \le 1 integration gives

y(t)=φ(0)−∫−1t−1φ(u) du.y(t) = \varphi(0) - \int_{-1}^{t - 1} \varphi(u)\,du.

The histories φA(s)=1\varphi_A(s) = 1 and φB(s)=1+s\varphi_B(s) = 1 + s on [−1,0][-1, 0] share the value φA(0)=φB(0)=1\varphi_A(0) = \varphi_B(0) = 1. They give yA(t)=1−ty_A(t) = 1 - t and yB(t)=1−t2/2y_B(t) = 1 - t^2/2 on [0,1][0, 1], so yA(1)=0y_A(1) = 0 but yB(1)=12y_B(1) = \tfrac{1}{2}. 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 τ>0\tau > 0 be constant and φ\varphi continuous on [t0−τ,t0][t_0 - \tau, t_0]. For t0≤t≤t0+τt_0 \le t \le t_0 + \tau the delayed time t−τt - \tau lies in [t0−τ,t0][t_0 - \tau, t_0], where y=φy = \varphi is known, so there the delay equation reduces to the ordinary initial-value problem

y′(t)=f(t,y(t),φ(t−τ)),y(t0)=φ(t0).\begin{gathered} y'(t) = f\bigl(t, y(t), \varphi(t - \tau)\bigr), \\[0.4em] y(t_0) = \varphi(t_0). \end{gathered}

Once yy is known on [t0,t0+τ][t_0, t_0 + \tau], the same reasoning gives an ordinary problem on [t0+τ,t0+2τ][t_0 + \tau, t_0 + 2\tau], whose initial value y(t0+τ)y(t_0 + \tau) comes from the previous step, and so on forward in time. If ff 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 [t0,t0+β)[t_0, t_0 + \beta). For a linear equation y′(t)=p(t)y(t)+r(t)y(t−τ)+g(t)y'(t) = p(t)y(t) + r(t)y(t - \tau) + g(t) with continuous coefficients, each step is a linear equation that can be solved on the whole step, so the solution exists for all t≥t0t \ge t_0. When ff does not depend on y(t)y(t), each step is a single integration. For y′(t)=−a y(t−τ)y'(t) = -a\,y(t - \tau) with a≠0a \ne 0, a jump in y′y' at t0t_0 reappears as a jump in y′′y'' at t0+τt_0 + \tau, in y′′′y''' at t0+2τt_0 + 2\tau, 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 y′(t)=−y(t−1)y'(t) = -y(t - 1) with the history φ=1\varphi = 1 on [−1,0][-1, 0], the first step gives y′=−1y' = -1 on [0,1][0, 1], so y=1−ty = 1 - t. On [1,2][1, 2] the delayed value is y(t−1)=1−(t−1)=2−ty(t - 1) = 1 - (t - 1) = 2 - t, so y′=t−2y' = t - 2 with y(1)=0y(1) = 0, and for 1≤t≤21 \le t \le 2

y(t)=t22−2t+32.y(t) = \frac{t^2}{2} - 2t + \frac{3}{2}.

Both pieces give y(1)=0y(1) = 0 and y′(1)=−1y'(1) = -1, and y(2)=−12y(2) = -\tfrac{1}{2}. The constant 32\tfrac{3}{2} is fixed by the joining value, not chosen freely. Smoothness changes at the joins. At t=0t = 0 the history has slope 00 while the solution starts with slope −1-1, so the graph has a corner. At t=1t = 1 the first derivatives agree, but the second derivative is 00 on the left and 11 on the right. A third step gives

y(t)=−t36+3t22−4t+176y(t) = -\frac{t^3}{6} + \frac{3t^2}{2} - 4t + \frac{17}{6}

on [2,3][2, 3], with y(3)=−16y(3) = -\tfrac{1}{6}.

Infinite-dimensional state

Definition For a delay equation with constant delay τ>0\tau > 0, the state at time tt is the segment yty_t of the solution over the last delay interval, defined by yt(θ)=y(t+θ)y_t(\theta) = y(t + \theta) for −τ≤θ≤0-\tau \le \theta \le 0. With a continuous history, every segment belongs to the space C[−τ,0]C[-\tau, 0] of continuous functions on [−τ,0][-\tau, 0]. 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 t0t_0. The space C[−τ,0]C[-\tau, 0] is infinite-dimensional, since the functions 1,θ,θ2,…1, \theta, \theta^2, \dots on it are linearly independent. For a system of nn first-order ordinary differential equations the state is a point of Rn\mathbb{R}^n, 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 y′(t)=−y(t−1)y'(t) = -y(t - 1) the formula of the history card gives

y(1)=φ(0)−∫−10φ(u) du,y(1) = \varphi(0) - \int_{-1}^{0} \varphi(u)\,du,

so the value at t=1t = 1 depends on the average of the whole history. The histories φ(s)=1+ks\varphi(s) = 1 + ks all have φ(0)=1\varphi(0) = 1, and they give y(1)=k/2y(1) = k/2, so the present value allows every real number at t=1t = 1. 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 λ\lambda of the characteristic equation below gives a solution eλte^{\lambda t}, there are infinitely many roots, and exponentials with distinct exponents are linearly independent.

Characteristic roots of a delay equation

Definition For y′(t)=−a y(t−τ)y'(t) = -a\,y(t - \tau) with real constants a≠0a \ne 0 and τ>0\tau > 0, substituting y=eλty = e^{\lambda t} with complex λ\lambda and canceling the nonzero factor eλte^{\lambda t} gives the characteristic equation

λ+ae−λτ=0.\lambda + a e^{-\lambda\tau} = 0.

Each root λ\lambda gives the solution eλte^{\lambda t}, and for a complex root its real and imaginary parts are real solutions. Since λ\lambda also appears in an exponent, the left side is not a polynomial. The equation has infinitely many complex roots, because multiplying by τeλτ\tau e^{\lambda\tau} turns it into zez=−aτz e^{z} = -a\tau with z=λτz = \lambda\tau, whose solutions are the values at −aτ-a\tau of the infinitely many branches of the Lambert W function. Only finitely many roots lie in any half-plane Re⁡λ≥γ\operatorname{Re}\lambda \ge \gamma, because such a root satisfies ∣λ∣=∣a∣e−τRe⁡λ≤∣a∣e−γτ\lvert \lambda \rvert = \lvert a \rvert e^{-\tau \operatorname{Re}\lambda} \le \lvert a \rvert e^{-\gamma\tau}. The stability theorem for linear retarded equations with constant coefficients states that if every root has Re⁡λ<0\operatorname{Re}\lambda < 0, then every solution, for every continuous history, tends to 00 exponentially, and that if some root has Re⁡λ>0\operatorname{Re}\lambda > 0, some solutions grow exponentially. For a=0a = 0 the equation is y′=0y' = 0, and λ=0\lambda = 0 is its only root, so the condition a≠0a \ne 0 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 a=1a = 1 and τ=1\tau = 1 the characteristic equation is λ+e−λ=0\lambda + e^{-\lambda} = 0. It has no real root, because g(λ)=λ+e−λg(\lambda) = \lambda + e^{-\lambda} has its smallest value g(0)=1>0g(0) = 1 > 0. Its rightmost roots are approximately

−0.318±1.337i,−2.062±7.589i,−2.653±13.949i,\begin{gathered} -0.318 \pm 1.337i, \\[0.4em] -2.062 \pm 7.589i, \\[0.4em] -2.653 \pm 13.949i, \end{gathered}

and the others lie further left. All real parts are negative, so every solution of y′(t)=−y(t−1)y'(t) = -y(t - 1) tends to 00 exponentially. The slowest modes decay like e−0.318te^{-0.318t} while oscillating with angular frequency about 1.3371.337. The values y(2)=−12y(2) = -\tfrac{1}{2}, y(3)=−16y(3) = -\tfrac{1}{6} and y(4)=524y(4) = \tfrac{5}{24} found by the method of steps from the history φ=1\varphi = 1 show the start of such a decaying oscillation. For a>0a > 0, real roots exist exactly when aτ≤1/ea\tau \le 1/e, because the function λeλτ\lambda e^{\lambda\tau} has smallest value −1/(eτ)-1/(e\tau) 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 y′(t)=−a y(t−τ)y'(t) = -a\,y(t - \tau) with a>0a > 0, the equation without delay is y′=−ayy' = -ay, whose solutions decay. With a delay τ>0\tau > 0, the zero solution is asymptotically stable exactly when aτ<π/2a\tau < \pi/2. If 0<aτ<π/20 < a\tau < \pi/2, no root has Re⁡λ≥0\operatorname{Re}\lambda \ge 0. Indeed, a root λ=p+iq\lambda = p + iq with p≥0p \ge 0 would satisfy ∣λ∣=ae−pτ≤a\lvert \lambda \rvert = a e^{-p\tau} \le a, so ∣qτ∣≤aτ<π/2\lvert q\tau \rvert \le a\tau < \pi/2 and cos⁡(qτ)>0\cos(q\tau) > 0, while the real part of the characteristic equation says

p=−ae−pτcos⁡(qτ)<0,p = -a e^{-p\tau}\cos(q\tau) < 0,

a contradiction. By the stability theorem every solution then decays exponentially. A root λ=iω\lambda = i\omega on the imaginary axis needs cos⁡(ωτ)=0\cos(\omega\tau) = 0 and ω=asin⁡(ωτ)\omega = a\sin(\omega\tau), which first happens at ω=±a\omega = \pm a and aτ=π/2a\tau = \pi/2. Differentiating the characteristic equation with respect to τ\tau gives

dλdτ=−λ21+λτ,\frac{d\lambda}{d\tau} = -\frac{\lambda^2}{1 + \lambda\tau},

whose real part at λ=ia\lambda = ia, aτ=π/2a\tau = \pi/2 is a2/(1+π2/4)>0a^2/(1 + \pi^2/4) > 0, so the pair ±ia\pm ia moves into the right half-plane as τ\tau increases. Further crossings occur only at aτ=π/2+2kπa\tau = \pi/2 + 2k\pi, all of them to the right, and a root with Re⁡λ≥0\operatorname{Re}\lambda \ge 0 always satisfies ∣λ∣≤a\lvert \lambda \rvert \le a, so no root can arrive in that half-plane from infinity. Hence some root has Re⁡λ>0\operatorname{Re}\lambda > 0 for every aτ>π/2a\tau > \pi/2.

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 a=π/2a = \pi/2, τ=1\tau = 1 is the equation of the first card, and its solution sin⁡(πt/2)\sin(\pi t/2) oscillates forever with constant amplitude, so the solutions do not all decay. For a=1a = 1 and τ=2\tau = 2, so that aτ=2>π/2a\tau = 2 > \pi/2, the rightmost roots are about 0.086±0.837i0.086 \pm 0.837i, and solutions started from the history φ=1\varphi = 1 oscillate with amplitude growing roughly like e0.086te^{0.086t}. 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

  1. Use the method of steps to solve y′(t)=2y(t−1)y'(t) = 2y(t - 1) with the history φ=1\varphi = 1 on [−1,0][-1, 0] for 0≤t≤20 \le t \le 2, and find y(2)y(2).
Show the answer

On [0,1][0, 1] the delayed value is 11, so y′=2y' = 2 with y(0)=1y(0) = 1, and y=1+2ty = 1 + 2t, which gives y(1)=3y(1) = 3. On [1,2][1, 2] the delayed value is y(t−1)=1+2(t−1)=2t−1y(t - 1) = 1 + 2(t - 1) = 2t - 1, so y′=4t−2y' = 4t - 2 with y(1)=3y(1) = 3. Integrating gives, for 1≤t≤21 \le t \le 2,

y(t)=2t2−2t+3.y(t) = 2t^2 - 2t + 3.

At the join both pieces have value 33 and slope 22. Finally y(2)=8−4+3=7y(2) = 8 - 4 + 3 = 7.

  1. A classmate says that y′(t)=−y(t−1)y'(t) = -y(t - 1) with y(0)=1y(0) = 1 has exactly one solution for t≥0t \ge 0. Test the claim with the histories φA(s)=1\varphi_A(s) = 1 and φC(s)=1+2s\varphi_C(s) = 1 + 2s on [−1,0][-1, 0]. Does the result contradict uniqueness?
Show the answer

Both histories have the value 11 at s=0s = 0. The history φA\varphi_A gives yA(t)=1−ty_A(t) = 1 - t on [0,1][0, 1]. For φC\varphi_C, the formula y(t)=φ(0)−∫−1t−1φ(u) duy(t) = \varphi(0) - \int_{-1}^{t-1} \varphi(u)\,du gives

yC(t)=1−[u+u2]−1t−1=1+t−t2.\begin{aligned} y_C(t) &= 1 - \bigl[u + u^2\bigr]_{-1}^{t - 1} \\[0.4em] &= 1 + t - t^2. \end{aligned}

It solves the equation, since yC′(t)=1−2ty_C'(t) = 1 - 2t and −φC(t−1)=−(2t−1)=1−2t-\varphi_C(t - 1) = -(2t - 1) = 1 - 2t. Now yA(1)=0y_A(1) = 0 while yC(1)=1y_C(1) = 1, 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 y(0)=1y(0) = 1 is not a complete initial-value problem. With each full history the method of steps gives exactly one solution.

  1. Without delay, y′=−2yy' = -2y makes every solution decay. The same feedback with a delay τ>0\tau > 0 gives y′(t)=−2y(t−τ)y'(t) = -2y(t - \tau). For which delays do all solutions decay? Check that sin⁡2t\sin 2t is a solution at the threshold delay, and say what happens for slightly larger delays.
Show the answer

Here a=2a = 2, so all solutions decay exactly when 2τ<π/22\tau < \pi/2, that is, for 0<τ<π/4≈0.7850 < \tau < \pi/4 \approx 0.785. At τ=π/4\tau = \pi/4,

−2sin⁡(2(t−π4))=−2sin⁡(2t−π2)=2cos⁡2t,\begin{aligned} &-2\sin\bigl(2(t - \tfrac{\pi}{4})\bigr) \\[0.4em] &\quad = -2\sin\bigl(2t - \tfrac{\pi}{2}\bigr) \\[0.4em] &\quad = 2\cos 2t, \end{aligned}

which is the derivative of sin⁡2t\sin 2t, so this solution oscillates with constant amplitude and does not decay. As τ\tau passes π/4\pi/4, the roots ±2i\pm 2i move to the right with Re⁡(dλ/dτ)=4/(1+π2/4)≈1.15\operatorname{Re}(d\lambda/d\tau) = 4/(1 + \pi^2/4) \approx 1.15, so for slightly larger delays some solutions are growing oscillations, and the same is true for every τ>π/4\tau > \pi/4. The stability of y′=−2yy' = -2y says nothing about the delayed equation, which is the common mistake this question tests.

How this lesson connects