# Tag Info

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Some reasons why noise reduction in vehicle cabins is not a standard feature, yet: As @Trevor Archibald states, safety is a very good reason. There is still a need to hear some noises from outside the vehicle such as the sirens of emergency vehicles: police, ambulance, fire fighters truck Hearing car horns from other drivers is still needed The sound of the ...

5

To understand why proportional gain won't drive the error point to zero, it is best just to look at the math. Consider the PID loop shown in the image below. The loop algebra in the $s$ domain comes out to \begin{align} e(s)&=r(s)-y(s)\\ y(s)&=P\ u(s)\\ u(s)&=\left(k_p+\frac{k_i}{s}+k_ds\right)e(s), \end{align} where I have used $P$ ...

5

This angle is determined by the lift characteristics of the rotor and the rotational inertia of the whole helicopter. You are exactly correct that the angle changes the phase of the feedback. For the purpose of discussion let's assume the helicopter has pitched forwards slightly and needs to be corrected backwards, also let's assume a single rotor that ...

5

At the very high level you will need 24V Power supply or a method to generate 24V 24V Motor controller Microcontroller - Arduino is a good place to start There are also prebuild motor controllers that can be programed via computer. These tend to be expensive. I would suggest following web sites similar to the ones listed below. They tend to have blogs, ...

3

The idea of using a feedforward component in a control system is to provide near instant action of the plant output to the input command. So a suitable choice of transfer function which connects the command to the plant input directly is an inverse model of the plant. The feedback control can then serve to 'clean up' any error in the feedforward component ...

3

Microprocessors. The measured value from a sensor (either an analog voltage or any other digital processed value) provides the microprocessor with the current output of the system. Internally, this has stored the desired setpoint, and computes the next control input by indeed taking the difference of the output and the setpoint using any kind of arithmetric ...

3

Based on the information you've given, I believe your professor is suggesting that a friction term can be represented as shown in the following block diagram. The transfer function $G(s)$ relates force ($F(s)$, the input in the diagram) to velocity ($sX(s)$, the output in the diagram) for a mass-spring system. The damping ($\rho$) is represented in the ...

3

This is typically done with a PID (Proportional, Integral, Derivative) control algorithm. There are heaps of literature about designing and optimizing PID controllers, so there's not much sense going into a more specific detail here. Typically you use the PID controller to regulate speed. Assuming your stopping point is also critical, there will be some ...

3

A lead filter implies that the zero has a lower frequency than the pole. While a PD controller with a low-pass-filter does not necessarily imply that order. Also a lead filter (usually) does not have the zero and pole to far apart from each other, meaning that the bode diagram does not get very close to the asymptotes of +1 slope for magnitude and 90° for ...

2

The plant and controller: $$\text{sys}=\frac{4700 s^2+4393 s+3.245\times 10^8}{s^4+7.574 s^3+120200. s^2}$$ $$pid=0.287\, +0.008 s+\frac{0.5}{s}$$ The closed-loop system obtained as $\frac{pid*sys}{1+pid*sys}$: $$csys=\frac{37.6 s^4+1384.04 s^3+2.59961\times 10^6 s^2+9.31337\times 10^7 s+1.6225\times 10^8}{1. s^5+45.174 s^4+121584. s^3+2.59961\times 10^... 2 Your implementation is: for i = 1: size(v_phi,1) y(i) = r(i)*((v_phi(i)/r(i) - v_phi(i+1)/r(i+1)) / (r(i+1) - r(i))); y1(i) = (v_phi(i)/r(i) - v_phi(i+1)/r(i+1)) * (v_phi(i)/r(i)); end That means that the discretization you are using is$$ y_i = r_i \left(\frac{v_{\phi,i}}{r_i} - \frac{v_{\phi, i+1}}{r_{i+1}}\right) \left(\frac{1}{r_{i+1} - r_i}\...

2

This system can be considered "closed loop," since the control input is being determined by some sort of feedback loop (even though the mathematical expression of the feedback loop through the operator is unknown). Also, yes the diagram you've shown is valid. I often work with control systems that have a human operator in the control loop, such as robotic ...

2

So typically there is proportionality and a continuously varying (analogue) output. Correct. This could be an analog voltage or a digital value. In the case of a simple process like a domestic gas boiler, the boiler is either fully on or fully off. Or, say a cooling fan that can only be switched on or off to keep something cold. In these cases, can a ...

2

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 $$v_{\mathrm{in}}(t) = \begin{cases}0, \; \mathrm{for} \; t < 0 \\ 10, \; \mathrm{... 2 Let's start by obtaining the state space form of the closed-loop system (closed loop means that you plug in the equations the expression of the controller). The controller of this specific system has the following form:$$ u = -Kx+r $$This is a full state feedback controller with feedforward gain of 1 (feedforward is the gain by which the input signal is ... 1 Adding to the other answers. I just so happen to have done exactly this. I used a windshield wiper motor and a potentiometer but the principal is the same. Here's my arduino source code: https://pastebin.com/0ezsmi4y And a short video I took of it in action. This is an alternate version that takes RC PWM input instead of serial. I think all the talk about ... 1 You are at the right track. As the DC motor is rather fast for a potential slow microcontroller, using a discrete controller will improve the reliability and stability of the closed-loop system. Even though a DC motor is rather easy to model (speaking of the basic dynamics upto the 3rd order), using system identification can improve parameter estimation ... 1 The System Identification Toolbox app is indeed the solution, but I can understand the amount of choices and options make it rather confusing at first. Especially if you have no prior knowledge to model identification. If you are going to use a PID controller, I simply suggest you perform a frequency identification on the system (as this estimates a transfer ... 1 I would think that this refers to using mathematical and physical principles and equations to predict the behaviour of a control system. The opposite would be to empirically design a control system, by implementing it and measuring it. 1 Suppose we have a system G(s) = \frac{1}{s(s+1)} and controller K (this is purely a gain) and we close the loop:$$T(s) = \frac{KG(s)}{1+KG(s)} = \frac{K\frac{1}{s(s+1)}}{1+K\frac{1}{s(s+1)}} = \frac{K}{s^2+s+K} $$As you might notice, the poles of this closed-loop equation depend on the value of K:$$s^2 + s + K = 0 \rightarrow s = -0.5\pm\sqrt{0....

1

your question is ill-conditioned: If $A$ must have a higher degree than $B$, 2 things can happen: $A$ is a constant, meaning $B$ must be 0: which means you cannot solve the equation as there is no $s$ term in $A(s)(s^2-1)$. Or $A$ is of order one (atleast one $s$) and $B$ is a constant: Which means the function can not be solved as there will be a $s^3$ ...

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First, find the energy balance - basically mass flow x thermal capacity x delta T is the same on both sides. Edit to add There's an error in your energy balance: on the left hand side it's simply $\Delta T$, not the derivative. Also make sure to use the correct values for $c$ as you have two different media. Then, find something like this for your valve: ...

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Since you're worried about an open-loop system, in theory all you need to do is perform standard stability analysis on the open-loop system alone. The source of the input signal to the open loop system is irrelevant if you can prove that it is stable for a known/expected set of input signals. For example, for a linear system you would need to demonstrate its ...

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Biswajit Banerjee already indicated that your code has bugs, which is why your results are so far off. I will explain in more detail where these bugs are: v_phi is a row vector, so size(v_phi, 1) always returns 1 because there is only one row. You want size(v_phi, 2) or better yet, numel(v_phi). Because you're using forward differences to compute the ...

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You can see how to obtain the transfer function of the mass spring system in many well documented links, e.g.: Xengineer 10 min youtube video Youtube Ryan Krauss Series 1, 2 - z, $\omega$, 3 - TFs, 4 - Damping, ... Having said that I couldn't understand what you meant by "it is possible to see the the friction in a mass-friction-spring as the ...

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I apologize in advance for the length of the text but as you can understand these concepts can't be easily defined in few words. I will do some research about the second question and come back to update the answer. 1. The magnitude bode plot of a system indeed represents the ratio you mentio. However, there is not something like a general "good" requirement ...

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As indicated in LM5030 datasheet COMP is output to an error amplifier. The circuit for the LM3411 is as follows The COMP output from the LM5030 is an input to the LM3411 which is an precision secondary regulator. The LM3411 is a low-power fixed-voltage (3.3 V or 5 V) precision shunt regulator designed specifically for driving an optoisolator to ...

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I would call this dead reckoning, because you do not have any actual measurement of the position, but are just calculating it based on the estimated speed of the motor.

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I'm going to derive the transfer function symbolically from the differential equations you provided in the hopes that you might be able to extract the rotational moment of inertia (not the mass directly, you'd have to know the radius of the rotating masses) from the formula. Here are the equations of motion as I interpreted them from your comment. J1 is the ...

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Because by definition, to have a non-zero output, you must have a non-zero error. This means that the output cannot match the setpoint perfectly. Only by adding an integrator can you drive the error to zero while maintaining a non-zero output.

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