Hot answers tagged

17

No, e(t) being zero does not imply that u(t) is also zero. It only implies that the output of the "P" process is zero. Remember, the "I" and "D" processes have memory — they depend on the past behavior of e(t). u(t) is zero only if the sum of all three processes is zero.


10

Mars rovers don't move very fast, that is an important part. The "drivers" from Earth plan a rover movement for months, testing out scenarios, studying the topography, etc. Specific movements are planned the day before and are coded up, simulated, and when everything checks out, are sent to the rover as commands. For example, the Spirit Rover was (is) on ...


5

Is the nominal model the desired model? (i.e. do we want to reach it?) In much the same way as I'd like a rich stranger to die and bequeath $100 million to me, yes, it's the desired model. Is the nominal model an imprecise idealization of the plant to simplify the mathematics? The nominal model is somewhere between your best guess of how the plant ...


5

This system: Actually uses the Motor's back EMF as a feedback signal, it does not use the speed information directly. From a back EMF viewpoint, this is a closed system (the back EMF is directly controlled). From a motor speed viewpoint, this is an open system (the speed is not directly controlled). However, this system: does use the speed of the motor ...


4

There can be a couple of scenarios. Consider a system \$\frac{1}{s (s+1)}\$. A PI controller is \$\frac{0.9 s+0.27}{s}\$. In steady state after the controller has made \$y=r\$, the error \$e\$ and its integral are both zero. In this case when \$e=0\$ then \$u=0\$. If there is a nonzero input going to this system, the output will keep on increasing. For a ...


4

Take a motor control PID for example. The motor (once running) will have small load perturbations that will cause it to overshoot or undershoot the zero error case, so then the system will react and cause the motor to slightly overshoot in the opposite direction. If you were to zoom in on a graph of the error, it would be little zig zags across the zero ...


4

You do already have a D-term when control velocity. It is the differentiation of the position, so no need to do double differentiation - not stable. simulate this circuit – Schematic created using CircuitLab EDIT: User DKNguyen has probably found a good reason why PI instead of PID is used: Let' take for exapmle a real servo driver having 62.5us ...


4

The path commands sent from Earth are general instructions on where to go. Earth operators can roughly plan paths 40 minutes in advance by studying terrain and obstacles, and in some cases by simulating the anticipated conditions with terrestrial equipment which is differently weighted to simulate Mars gravity. The control systems operating in real time ...


3

When in doubt, check the service manual. Audio signal from the input RCA jacks is routed through a LC78212 analog switch IC for source selection, then directly to the volume pot, which is shown in the center of the block diagram. Note this pot has an extra pin for loudness control. If you replace it with a pot which does not have this extra pin, the "...


3

The concept of "real time" is a stretchable thing. If your controlled object is, say, a metallurgical oven, then, depending on the size of it the real control time may be from seconds to minutes or even hours. So you need to define more clearly what kind of sampling rate is sufficient to make a robust and stable control for your object. To determine which ...


3

This is going to take some work. The biggest problem is the 1 kHz is fairly close to 60 Hz, being only a factor of 16 different. A simple filter will (at best) reduce line frequency by a factor of 16 compared to your tone. So, if you inject 1 V rms into the power line, your received signal will (again, this is best case) have 1 V rms at 1 kHz, and (120/16) ...


3

Robust means that your controller will be less affected by plant variations. For example, if your plant transfer function is a crude approximation, you should aim for a more robust controller. It is loosely related to the concept of robustness https://en.wikipedia.org/wiki/Robust_control Aggressive means fast rise time. If your model is really accurate, ...


3

They can be used for either. A thermostat, such as a bimetallic strip type, is an on-off controller which is used in a closed loop to control room temperature. As the temperature rises above setpoint the heat is turned off. As the temperature falls below setpoint the heat is turned on. The same heating system could be run from a timer that applies heat for ...


2

It is basic block diagram algebra. First, you write out the algebraic equations and solve for the unknowns \$x1\$ and \$x2\$. $$\text{x1}=\frac{0.05 (\text{Ua}-0.1 \text{x2})}{0.01 s+1}$$ $$\text{x2}=\frac{-\text{Mx}+\text{x1}-2 Y}{0.5 s+1}$$ Next you write the output equation as \$Y= \frac{1}{s} x2\$ and solve for \$Y\$ in terms of the two inputs \$Ua\$ ...


2

These terms are not engineering specs, and not particularly standard. "Aggressive" would suggest fast rise time, possibly with overshoot. "Robust" suggests that the system "works" across a large set of different inputs.


2

The back EMF is an inherent characteristic that is a factor in determining the motor's torque vs. speed curve. Without feedback, the motor speed is not indeterminate. It varies as load change as determined by the slope of the torque vs. speed curve. The back EMF gives the motor a certain amount of built-in feedback, but the effect is limited. The gain can ...


2

The D term is very sensitive to noise so can be difficult to deal with since noise can be a relatively high frequency, especially if your sample rates are higher since it captures more of the noise and steep slopes. You can see this by taking a real waveform with noise on it and graphing it's derivative with high sample rates. The slopes of the noise ...


1

To put the PNP transistor in cutoff you need to bring THERM up to the transistor's emitter voltage, 5V, instead of just 3.3V. You could connect R18 to 5V but that might damage the temperature sensor. The general solution to this problem is to add an NPN transistor that will drive the base of Q3. The NPN transistor can be switched with the 3.3V sensor ...


1

I would suggest that you investigate simply driving the PS_ON# signal to both ATX power supplies from the same source. The source would come from the motherboard in the box with the computer. This diagram shows how it would be interconnected: This will result in when the soft power switch in the computer subsystem is activated the PS_ON from the ...


1

Probably at least P+I control to get ~0 error at the floor positioning. Self-tuning PID or fuzzy logic for higher performance. Plus some clever scheduling and positioning logic to optimize the use of multiple elevators. The classic control system used in early elevators is the Ward-Leonard, which uses no electronics, just a M-G set. Diagram from here ...


1

The term "feeedback" is used when a portion of the output signal is coupled back to the input. Hence, it is important to verify the input node. In your circuit, we have two inputs: A reference input v(s) and a disturbance input T(s) and two corresponding transfer functions H1=out/v(s) and H2=out/T(s). For H1 the forward gain Hf is the product of all three ...


1

You will probably be OK using 100k pot instead of the 50k in an audio amplifier volume control application. The 50k pot will be driving a high impedance amplifier stage following, which is likely to be substantially higher than the max 25k output impedance of a 100k pot (compared to the max 12.5k of a 50k pot). Given that the output impedance varies as the ...


1

The state space representation looks like this mathematically \$ \dot{x} =A x + Bu\$ \$ y = C x +Du\$ This is what it looks like in block diagram form: Source: https://en.wikipedia.org/wiki/State-space_representation The reason for the integrator is this: \$\dot{x} =A x \$ \$ x s =A x \$ \$ x =A \frac{x}{s} \$


1

All four of the matrices interact with the system at different points. I think the best way to understand them is to look at the formulae while referring to the general diagram: Figure 1: "Vector block diagram for a linear system [...]" When you look at the above diagram we can see that the four matrices are in various points that correlate with their ...


Only top voted, non community-wiki answers of a minimum length are eligible