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We have seen the inverse dynamics in Syria, so let's now apply it in practice focus or in MATLAB.

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So first of all, how we will do it, we will first import the model of the desire to the robot manipulator.

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In our case, I will just import at the model of you are five robotic manipulator, then justified the

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PD gains, which are required.

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And this is the time span to execute the whole process.

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OK, so let's we just call the smoothing file and simulate the smerling file, and then we open the

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scopes in order to see them.

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So when you execute this one, it will be executed, and at the end you will see automatically the results

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from the scopes.

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But I will not do that because it will take a bit of time.

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I have done this before and I will show you the results.

12
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But let's first analyze the simulation file.

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As you can see again, we have here our robot manipulator.

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Again, this accept talks and gives out as GIS give out back the cute and cuddly, which are configuration,

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velocity and acceleration, but even not actually if you will not need acceleration.

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So we put the Terminator here in order to avoid the burning in the lab.

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I'm sorry, I'm a bit of sick, so I am sick.

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So that's why my throat is a bit bad.

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I'm sorry for that.

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Anyway, this is our desired trajectory.

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OK, here is our desired orientation, velocity and acceleration.

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As you can see, we have used we have used three or three of them, OK, we use configuration, velocity

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and acceleration.

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We have used velocity to calculator in order to calculate the input for the controller and excuse me,

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configuration for peak controller velocity for the controller.

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OK.

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And we used also velocity acceleration feed forward.

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OK.

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Please remember this.

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We use also acceleration feed forward.

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OK.

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OK.

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And as you can see what we have done, we have to calculate the inverse dynamics here and we give it

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to our robot, the main operator, OK, as an input torque.

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So what we have done, we have tried to compensate for the terms in the modeling of the robotic manipulator

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again, not just for the gravity term.

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OK, let's see.

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And again, here you have the try to visualize what's our error configuration error and what's our velocity

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error?

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OK?

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Let's check if the voltage desired configuration or not.

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OK.

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This is so if you press run button, you will see the results, but I will not do that.

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That's just directly check, as you can see, as you can see, no, our error is much, much smaller.

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OK, let's check this is ten or minus three, OK?

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As you can see these, our error is very small.

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OK, from here, take this OK, and let's zoom it and let's check.

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OK.

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As you can see, the error at the end is 10 to the minus four, which is very, very small.

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As you can see the almost zero 10 to the minus five.

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OK, it's almost zero.

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This controller is better than shear lipide controller.

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OK?

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This is better than PD controller.

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And let's so we did.

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We reached the desired configuration.

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Let's see what's happening with the velocity.

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As you can see, this is our velocity.

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And as you can see at the end, we have reached the velocity error of zero.

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And we this is the velocity of zero because at the end, we have to reach the velocity of zero if our

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robot stops.

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OK, so it start from the zero velocity or any initial velocity, it doesn't matter.

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However, at the end it reaches the desired configuration, so it stops and the velocity becomes zero,

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or it can reach even the desired velocity.

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So the velocity error will be zero.

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It depends just that it changed because of the task.

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OK.

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Or as you can see, we have reached the error of zero, both in terms of velocity tracking and configuration

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tracking.

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And again, you can just do some manipulation with b d gains and you can check what's happening with

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the result and figures.
