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The bicycle disk as shown is inherently prone to shimmying and spiraling into an increasing flutter.
I have an Ebike with a very similar disk brake and I have learned my lesson to be cautious with it.
As for controlled caliper force, one could use a scissor mechanism with a hook on the bottom which could be loaded by the desired weights as per the schematic ...
3
The basic thing you are looking at is a dynamometer - a generator mounted on trunnions to measure the reactive force.
So, look at those then use a smaller motor as a generator - the ones I used were capable of controlling 100 to 150 kW - a bit large for what you describe.
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A system is some kind of function that maps an input as a function of t to an output.
$$y(t) = H(u(t))$$
This system is linear if the following holds:
$$y_1 = H(u_1), \quad y_2 = H(u_2)$$
$$\alpha y_1 + \beta y_2 = H(\alpha u_1 + \beta u_2)$$
for any scalar value $\alpha$, $\beta$.
Your driven harmonic oscillator is currently described in such a way the ...
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The position of the calipers isn't what you are adjusting, it's the pressure you exert on them.
Assuming the system is relatively slow (break force ramps up and down ~1 second), then a spring which is tensioned by a servo should work fine for this.
If the spring is stretched further, the breaking force will be increased. Notice that even though the cable is ...
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First of all you could take a look at my answer here Is there any other controller than PID Controller? . It kind of deals with the fact of the various controllers out there.
The problem of the best controller to use is something really debatable. The best controller always depends on what you have to control and in most cases the engineer has to design some,...
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The transient response (or homogeneous solution) of a linear ODE is
$$y_h(t) = \sum_{i=1}^N C_i e^{p_i\cdot t} $$
where $p_i$ is the i-th pole of your system.
Assume you have a pole at location $p_i = \lambda + i\omega$, with $i = \sqrt{-1}$.
The real part ($\lambda$) of this pole will determine the convergence rate towards zero, while the imaginary part $\...
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The final value theorem is for a signal, not a transfer function.
Use the transfer function to express the output signal
$$ V_{\mathrm{out}}(s) = \frac{1}{RCs+1} V_{\mathrm{in}}(s),$$
with input $V_{\mathrm{in}}(s)$. Now, I assume that your input signal is a step-function
$$ v_{\mathrm{in}}(t) = \begin{cases}0, \; \mathrm{for} \; t < 0 \\ 10, \; \mathrm{...
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The System Identification Toolbox app is indeed the solution, but I can understand the amount of choices and options make it rather confusing at first. Especially if you have no prior knowledge to model identification. If you are going to use a PID controller, I simply suggest you perform a frequency identification on the system (as this estimates a transfer ...
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Tracking performance is a two-fold principle:
Transient performance:
The settling time and overshoot. This is where your bandwidth and phase margin play a role. The bandwidth affects the frequency of the response, thus in general, higher bandwidth means shorter rise time and faster response. But it can also oscillate for quite a while, which harms the ...
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