Abstract
Nonlinear systems have a range of behaviour not seen in linear vibrating systems. In this chapter the phenomena associated with nonlinear vibrating systems are described in detail. In the absence of exact solutions, the analysis of nonlinear systems is usually undertaken using approximate analysis, numerical simulations and geometrical techniques. This form of analysis has become known as dynamical systems theory (or sometimes chaos theory) and is based on using a system state space. In this chapter the basic ideas of dynamical systems are applied to vibrating systems. Finally, the changes in system behaviour as one (or more) of the parameters is varied are discussed. Such changes are known as bifurcations, and they are highly significant for the understanding of nonlinear systems.
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Notes
- 1.
Think of \(\mathbb {R}\) as representing the set of real numbers on an axis in an n-dimensional space.
- 2.
Throughout, it will be assumed that \(\mathbf {f}\) is a smooth function, such that existence and uniqueness of solutions is always satisfied.
- 3.
For most vibration problems, non-autonomous means the system has time-dependent forcing, and autonomous means that the system is unforced. In fact, a non-autonomous system can usually be represented as autonomous by setting \(t=x_{3}\) and adding an additional equation to the system \(\dot{x}_{3}=1\).
- 4.
Although this linear system can be solved exactly, numerical integration is used as this will be required for the nonlinear examples.
- 5.
These are also sometimes called fixed points but here fixed point will only be used for maps.
- 6.
- 7.
Note that this is now the same as the equation of motion for an unforced, undamped, harmonic oscillator, where the constant is determined by the initial displacement and velocity.
- 8.
In three dimensions this point looks like a horse saddle. See Sect. 2.3.
- 9.
Also known as a heteroclinic orbit, which joins two separate saddle points. Not to be confused with a homoclinic orbit, an orbit which starts and finishes at the same saddle point.
- 10.
Note that the norm is used here because \({\varvec{\xi }}\) is a vector.
- 11.
In fact, the formal definition is that the equilibrium points are hyperbolic. The structure of the trajectories close to a hyperbolic equilibrium point are topologically equivalent to the trajectory structure of the linearized dynamical system, see Guckenheimer and Holmes (1983) for a detailed discussion.
- 12.
An alternative approach is to use the solution \({\varvec{\xi }}={\varvec{\xi }}_{0}\mathrm {e}^{At}={\varvec{\xi }}_{0}P\mathrm {e}^{Jt}P^{-1}\) where \(J\) is the Jordan normal form of \(A\)—see for example Glendinning (1994).
- 13.
In fact the behaviour depends on the multiplicity of the repeated eigenvalue. The degenerate node corresponds to the case where there is only a single eigenvector. For the case with two eigenvectors the degenerate equilibrium point becomes a star see Strogatz (2001). See Seyranian and Mailybaev (2003) for a more detailed discussion of multiplicity.
- 14.
When \(\mathrm {tr} (A) =0\) and \(\det (A)=0\), there is a doubly-degenerate equilibrium point. This is not discussed further here.
- 15.
- 16.
The fact that the undamped solutions persist with the addition of small damping, is an important underlying assumption in vibration analysis.
- 17.
Not to be confused with potential energy.
- 18.
Also known as a homoclinic bifurcation.
- 19.
Also know as a homoclinic orbit, an orbit which starts and finishes at the same saddle point. Not to be confused with a heteroclinic orbit, which joins two separate saddle points.
- 20.
This is the separatrix trajectory which goes directly to the saddle point.
- 21.
In fact they could be closer, but they have been slightly separated to make the figure clearer.
- 22.
- 23.
This term originates from electronics, where it refers to a direct current voltage, but the concept has been extended to any representation of a waveform.
- 24.
This is the representation typically used in linear control theory.
- 25.
Like a root-locus in linear control theory.
- 26.
Aeroelastic divergence is another example.
- 27.
In fact this is a special case, as there is no limit cycle close to the bifurcation point, see Strogatz (2001).
- 28.
There is a third variation called the transcritical bifurcation see Strogatz (2001).
- 29.
- 30.
The derivation of a Duffing oscillator from the snap-through system can be found as the solution to Problem 2.1. Note that the mass is at static equilibrium when \(x=\pm a\), and the springs are at their natural length, \(L\).
- 31.
- 32.
- 33.
A fixed point in a map can be thought of as analogous to equilibrium point in a continuous flow.
- 34.
Also sometimes referred to as the Floquet multipliers of the periodic orbit.
- 35.
This definition is for the lowest order return period i.e. one. Higher order periodicity maps can be defined, and the interested reader can find details in Thompson and Stewart (2002).
- 36.
In discrete systems \(\uplambda \) act as multipliers, so \(|{\uplambda }|>1\), solution grows, unstable; \(|{\uplambda }|<1\), solution shrinks, stable.
- 37.
See Thompson and Stewart (2002) for details of the derivation of this and other maps.
- 38.
- 39.
Note that in general these types of maps are called Poincaré maps, see Strogatz (2001).
- 40.
Running time backwards reverses the stability of solution branches, so in this way brute force can be used in some cases to find unstable solutions like repellers, but not saddles.
- 41.
For example it can capture the down then upward curving trend for \(|v|\) increasing, known as the Stribeck effect.
- 42.
Note that this definition relies on Amonton’s laws of friction. i.e. that the friction force is directly proportional to the normal load and independent of area. This will restrict the situations in which it could be applied in practice.
- 43.
Note both the ball and the wall will deflect. How much depends on the material and geometric properties.
- 44.
Also referred to as the Newtonian coefficient of restitution, this type of impact model assumes that there is no tangential force during the impact. See Stronge (2000) for details of this and other more complex impact cases.
- 45.
See Hodges and Woodhouse (1983) for more details.
- 46.
This is assuming that the frequencies of interest are in the low range. For mid-frequency problem statistical energy analysis is often more appropriate, see Langley (1989).
- 47.
Assuming that the modelling techniques employed are used with sufficient care.
- 48.
Used in this context, this is usually called a Lyapunov function, although limitations exist—see Chap. 3, Sect. 3.2.
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Problems
Problems
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2.1
Derive the equation of motion for the system shown in Fig. 2.20a. Show that this equation can be approximated by the Duffing equation
$$\begin{aligned} m\ddot{x}+c\dot{x}-\mu x+\alpha x^{3}=0, \end{aligned}$$and estimate when this might be a valid assumption.
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2.2
The normal form of the Hopf bifurcation is usually written as
$$\begin{aligned} \dot{x}&=\mu x+y-x(x^{2}+y^{2}), \nonumber \\ \dot{y}&=-x+\mu y-y(x^{2}+y^{2}). \end{aligned}$$(2.35)Show that this system can also be represented as
$$\begin{aligned} \dot{r}&= r(\mu -r^{2}), \\ \dot{\theta }&= -1, \end{aligned}$$in polar coordinates. Examine the stability of the equilibrium point at the origin \((x=0,\ y=0)\) by finding the Jacobian of Eq. (2.35).
-
2.3
A nonlinear system is governed by the following set of first-order differential equations
$$\begin{aligned} \dot{x}_{1}&=x_{2}, \nonumber \\ \dot{x}_{2}&=x_{1}-x_{1}^{2}-\mu x_{2}, \end{aligned}$$(2.36)where \(\mu \) is a parameter which can be varied. Find the equilibrium points for the system when \(0<\mu <\sqrt{4}\) and find the type and stability of each equilibrium point. Sketch typical trajectories in the system state space.
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2.4
Consider the potential functionFootnote 48 given by
$$\begin{aligned} V=\frac{x_{2}^{2}}{2}-\frac{x_{1}^{2}}{2}+\frac{x_{1}^{3}}{3}. \end{aligned}$$Finding the time derivative of \(V\) and substituting for \(\dot{x}_{1}\) and \(\dot{x}_{2}\) gives an indication of the stability of equilibrium points at the origin. For the case when \(x_{1}\) and \(x_{2}\) are small, use this function to determine the stability of the origin for the system given in Eq. (2.36). How does the sign of \(\dot{V}\) relate to the stability?
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2.5
For the system given in Eq. (2.36), when \(\mu \) passes through zero a bifurcation occurs. Use local analysis to explain what happens at the bifurcation point. What type of bifurcation occurs?
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2.6
The dynamics of a damped unforced pendulum can be modelled using the non-linear differential equation
$$\begin{aligned} \ddot{\theta }+\delta \dot{\theta }+\omega ^{2}\sin \theta =0, \end{aligned}$$where \(\theta \) is the angle of the pendulum from the downwards resting position, \(\delta \) is the damping parameter and \(\omega =\sqrt{\frac{g}{l}}\) is the natural frequency of the pendulum where \(g\) is the force due to gravity and \(l\) is the length of the pendulum. Find the equilibrium points for the pendulum in the range \( 2\pi \le \theta \le 2\pi \) when \(\delta ^{2}<4\omega ^{2}\). Indicate the type and stability of each equilibrium point and sketch the pendulum trajectories in the \(\theta ,\dot{\theta }\) plane.
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2.7
For small angles the motion for a pendulum can be approximated by
$$\begin{aligned} \ddot{\theta }+\delta \dot{\theta }+\omega ^{2}(\theta -\frac{\theta ^{3}}{3!})=0. \end{aligned}$$Use the potential (i.e. Lyapunov) function
$$\begin{aligned} V=\frac{1}{2}\dot{\theta }^{2}+\frac{\omega ^{2}}{2}\theta ^{2}-\left( \frac{\omega ^{2}}{3!}\right) \frac{\theta ^{4}}{4} \end{aligned}$$to determine the stability of the point \(\theta =0,\dot{\theta }=0\), by finding the sign of \(\dot{V}\). Assume that \(\omega =1\).
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2.8
The logistic map is a single state mapping which is used to model population dynamics represented as
$$\begin{aligned} x_{n+1} =\lambda x_n(1-x_n), \end{aligned}$$Identify the period one fixed points for the system and their stability. Which bifurcations occur at \(\lambda =1\) and \(\lambda =3\)?
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Wagg, D., Neild, S. (2015). Nonlinear Vibration Phenomena. In: Nonlinear Vibration with Control. Solid Mechanics and Its Applications, vol 218. Springer, Cham. https://doi.org/10.1007/978-3-319-10644-1_2
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