Question 2.8: In the mechanical system shown in Fig. 2.27, the relationshi...

In the mechanical system shown in Fig. 2.27, the relationship between the force exerted by the spring and the change of the spring’s length measured from the spring’s relaxed position has been approximated mathematically by the following nonlinear equation:

F_{NLS}=f_{NL}(x)=2.5\sqrt{x} .       (2.68)

Obtain a linearized mathematical model of the system that approximates the system dynamics in a small vicinity of the normal operating point determined by the average value of the input force, \overline{F}_i=0.1N.

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This problem is solved following the five-step linearization process introduced earler in this section.
Step 1. The mathematical model of the system is a second-order nonlinear differential equation:

m\ddot{x}+b\dot{x}+ f_{NL}(x)=F_i ,                 (2.69)

m\ddot{x}+b\dot{x}+2.5\sqrt{x} =F_i .                (2.70)

Step 2. The normal operating point is defined by the given constant input force \overline{F}_i=0.1N and by the corresponding displacement \overline{x}. One can find the unknown value of \overline{x} from model equation (2.70) by settingF_i=\overline{F}_i and x = \overline{x} which yields

m\ddot{\overline{x} } +b\dot{\overline{x} }+2.5\sqrt{\overline{x} } =\overline{F}_i .                    (2.71)

The first two terms of Eq. (2.71) drop out because\overline{x} is, by definition, a constant, and does not vary with time.Hence

2.5\sqrt{x} =\overline{F}_i,        (2.72)

\overline{x}=\left(\frac{0.1}{2.5} \right)^2=0.0016 m.                    (2.73)

Thus the normal operating point corresponding to the constant portion of the input force of 0.1 N is a deflection of 0.0016 m.
Step 3. Introduce the incremental variables by substituting x=\overline{x}+\hat{x} \space and \space F_i=\overline{F}_i+\hat{F}_i into Eq. (2.71):

m\ddot{\hat{x}}+b\dot{\hat{x}}+f_{NL}(\overline{x}+\hat{x})=\overline{F}_i+\hat{F} _i .            (2.74)

Step 4. The nonlinear term in Eq. (2.74) is approximated by the first two terms of the Taylor’s series expansion:

f_{NL}(\overline{x}+\hat{x} )\thickapprox 2.5\sqrt{\overline{x} }+\left(\frac{2.5}{2\sqrt{\overline{x} } } \right)\hat{x}=0.1+31.25\hat{x}.         (2.75)

Step 5. Substitute the linear approximation in Eq. (2.75) into (2.74) to get the following result:

m\ddot{\hat{x} }+b \dot{\hat{x} }+0.1+31.25\hat{x}=\overline{F}_i+\hat{F}_i                  (2.76)

Note that the constant portion of the input force appears on both sides of Eq. (2.76) and therefore cancels out, leaving a linear second-order ordinary differential equation (ODE):

m\ddot{\hat{x} }+b \dot{\hat{x} }+31.25\hat{x}=\hat{F}_i .             (2.77)

Note that the coefficient of the incremental displacement term occupies the position where one normally finds a spring constant. In point of fact, this is the incremental stiffness k_{inc} of the NLS in the vicinity near the normal operating position established by the force \overline{F}_i = 0.1N:

m\ddot{\hat{x} }+b \dot{\hat{x} }+k_{inc}\hat{x} =\hat{F}_i               (2.78)

where

k_{inc}=31.25N/m.             (2.79)

To further illustrate this important concept, both the linearized and nonlinear spring characteristics can be plotted by use of MATLAB. Appendix 3 is a tutorial on the MATLAB environment, and readers not well versed in its usage are encouraged to review the tutorial before proceeding with the book material.
The nonlinear function to be plotted is given by Eq. (2.68). The linearized model of the spring is represented by a straight line tangent to the nonlinear function at the normal operating point (\overline{x} = 0.0016 m). The slope of the straight line is the incremental stiffness, 31.25 N/m and its y intercept is 0.05 N, which can be found by substitution of the coordinates of the normal operating point into a general equation for the tangent line. Thus the approximated linearized spring force equation is

F_{NLS}\approx 31.25x +0.05.       (2.80)

The following MATLAB commands can be used to generate the plots:

 

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>> x = [0.0:0.0001:0.01]; % set up a vector of x values
>> Fnls = 2.5*xˆ0.5; % compute NLS force
>> Flins = 31.25*x+0.05; % compute linearized spring force
>> plot (x, Fnls, x, Flins) % plot both force against deflection
>> xlabel(‘Deflection (m)’) % add x and y labels and grid to plot
>> ylabel(‘Force (N)’)
>> grid

The plot is shown in Fig. (2.28). The main outcome of the linearization process performed in Example 2.8 was the incremental stiffness of the spring (k_{inc}), which is equal to the slope of the line that is tangent to the nonlinear function at the normal operating point of interest. Some interesting observations can be made from the plot.
First, it can be seen that the slope of the tangent line (and the incremental stiffness) will vary a great deal, depending on the location of the normal operating point, from a very large positive number near the point of zero deflection (approaching infinity) to a more modest value of 31.25 N/m at a deflection of 0.0016 m. Second, it is quite clear that the linearization error, or the difference in the vertical direction between the nonlinear function and the tangent line, will increase as the spring deflection deviates from the normal operating point. Finally, it can also be observed that the linear approximation is better as the normal operating point moves farther away from the spring-relaxed position, x = 0.
In summary, although linearized models should be used whenever possible (because they lend themselves to powerful analytical methods), it should be kept in mind that they constitute local (usually for small deviations from a nominal operating point) approximations of the nonlinear system and that the results obtained with linearized models provide a simplified picture of the actual system behavior.

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