# Tag Info

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Your results are correct. I have solved the differential equations in Octave using the ode solver and I get the same results: function dX = elevation(t,X) g = 9.81; m_cw = 1.87; l_w = 0.47; m_uav = 1.17; l_a = 0.66; J_e = 0.91; D_e = 0.04; F_in = 0.68; theta = 0; dX(1) = X(2); dX(2) = (F_in * l_a * cos(theta) + (m_cw*l_w - m_uav*l_a)*...

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As you mention, PID control is for Single Input, Single Output (SISO) control. If you want Multi Input, Single Output (MISO) or Multi Input, Multi Output (MIMO) control, you need to look at other methods of control, such as Linear Quadratic Regulators (LQR) or state space control. MATLAB has a control system toolbox that will do both, and every quality ...

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Time Constant and systems A second order LTI system in Laplace domain: $\hspace{2.5em}$ $H(s) = \frac{{\omega_{n}}^{2}}{s^{2}+\zeta\omega s+{\omega_{n}}^{2}}$ The solution is: $\hspace{2.5em}$ $h(t) = \frac{{\omega_{n}}}{\sqrt{1-\zeta^{2}}}e^{-\zeta {\omega_{n}} t}sin({\omega_{n}} \sqrt{1-\zeta^{2}}t)$ Note that the time constant depends on the product of ...

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You shouldn't use a proportional control. The type of controller you describe (switching from 0 to full load and back to 0 almost instantaneously) is called a bang-bang controller. This controller is often used as a simplified model of a furnace heating system in a house, which can only be on or off. It is important to include a dead band (a range where the ...

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GPIO stands for General Purpose Input Output. Lets assume you want to generate a pulse at pin 39 as in the below image. So when you wire the pulse to pin 39 the underline software will generate the necessary code to configure pin 39 to be an output pin enabling the pin to output a pulse. Below is the code stack between Simulink and Microcontroller. So when ...

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This post is a little dated but thought someone might benefit from another angle. @Solar Mike is correct. The reason you overflow frequently is because your exit valve is undersized for in inlet flows you're specifying. The only remedy is to limit your inlet flows to the range that the exit valve can handle, OR, increase your valve size. You don't ...

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By including $x_0$ as feedback (making $x_0 = x(t)$) you are not linearizing this system. Instead you've created a Linear Parameter-Varying (LPV) system (more specifically a quasi-LPV system since your parameter varies according to your state). Such systems do not obey the same stability properties as Linear Time-Invariant systems so if you're looking to ...

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You can use the saturation block. Set the upper limit to "Inf" (thanks @Petrus1904) and the lower limit to 0. The output of the saturation block should accordingly be only the positive values of whatever input you gave it.

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I solved the issue with a switch function block, it not the best solution but it works for my basic simulation. Thanks again

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If this is the case, the equation either needs a domain readjustment(so, valid from t∈[0.7,∞]) or an equation redefinition. Using a piecewise function would look like: $$M \frac{dv}{dt} = F_t -(\beta_1+\beta_2v^{2}+\beta_3v), t∈[0.7,∞]$$ $$M \frac{dv}{dt} = 0, t∈(0,0.7)$$ Friction, is just a reactionary force. For rolling resistance can be modelled as an ...

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It sounds like you have some experimental data, and from that you would like to be able to estimate the transfer function of your system so that you could use it for control system design purposes. If that's the case, and given that you are using MATLAB, I would suggest looking at the tfest function, which is part of the System Identification Toolbox: ...

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ode solvers are all different. I've recently compared several fixed-time-step and variable-time-step ode solvers, with the same initial conditions, with the same model. Summary: They all give different solutions, sometimes fundamentally different. Matlab/Simulink documentation gives a rough outline of picking the most useful (not the BEST) solver for the ...

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