Table of Contents
Specifically, the Distinction block computes the motor's change in position (in counts) and the very first Gain block divides by the sample time. Subsequent Gain obstructs convert the systems from counts/sec to revolutions/sec, and after that from revolutions/sec to revolutions/min. The continuous representing the gear ratio requires to be defined in the MATLAB work area prior to the design can be run.
Minimizing the length of the simulation then running the model produces the list below output for motor speed in RPM. Analyzing the above, we can see that the quote for motor speed is rather noisy. This develops for a number of factors: the speed of the motor is in fact differing, encoder counts are being occasionally missed out on, the timing at which the board is polled does not precisely match the recommended sampling time, and there is quantization associated with reading the encoder.
Consider the following design with a simple first-order filter contributed to the motor speed estimate. This model can be downloaded here. Running this design with the sample time increased to 0. 05 seconds and a filter time constant of 0. 15 seconds produces the list below time trace for the motor speed.
05; filter_constant = 0. 15;. By increasing the tasting duration and including the filter, the speed estimate indeed is much less noisy. This is particularly useful for enhancing the quote of the motor's speed when it is running at a stable speed. A drawback of the filtering, however, is that it includes delay.
In essence we have lost information about the motor's actual action. In this case, this makes determining a model for the motor more tough. When it comes to feedback control, this lag can break down the efficiency of the closed-loop system. Decreasing the time constant of the filter will reduce this lag, however the tradeoff is that the noise will not be filtered also.
Thinking about that our input is a 6-Volt action, the observed reaction appears to have the type of a first-order action response. Taking a look at the filtered speed, the DC gain for the system is then around 170 RPM/ 6 Volts 28 RPM/V. In order to approximate the time constant, nevertheless, we require minimize the filtering in order to better see the true speed of the motor.
01 seconds, we get the following speed response. Remembering that a time consistent defines the time it takes a procedure to attain 63. 2% of its total change, we can approximate the time continuous from the above graph. We will try to "eye-ball" a fitted line to the motor's reaction chart.
Assuming the exact same steady-state performance observed in the more greatly filtered information, we can estimate the time continuous based on the time it takes the motor speed to reach RPM. Because this appears to happen at 1. 06 seconds and the input appears to step at 1. 02 seconds, we can approximate the motor's time consistent to be roughly 0.
Therefore, our blackbox design for the motor is the following. (2) Remembering the design of the motor we stemmed from first concepts, duplicated below. We can see that we anticipated a second-order model, but the reaction looks more like a first-order design. The description is that the motor is overdamped (poles are genuine) which one of the poles dominates the action.
( 3) In addition to the truth that our design is reduced-order, the design is an additional approximation of the real life in that it ignores nonlinear aspects of the real physical motor. Based upon our linear model, the motor's output ought to scale with inputs of different magnitudes. For instance, the response of the motor to a 6-Volt action ought to have the exact same shape as its reaction to a 1-V step, just scaled by a factor of 6.
This is due to the stiction in the motor. If the motor torque isn't big enough, the motor can not "break free" of the stiction. מנועי ווקטור. This nonlinear habits is not recorded in our model. Normally, we utilize a viscous friction model that is linearly proportional to speed, rather than a Coulomb friction design that records this stiction.
You might then compare the predictive capability of the physics-based design to the blackbox design. Another workout would be to generate a blackbox model for the motor based upon its frequency action, similar to what was made with the increase converter in Activity 5b. An advantage of utilizing a frequency action technique to identification is that it makes it possible for identification of the non-dominant characteristics.
In Part (b) of this activity, we develop a PI controller for the motor.
Table of Contents
Find Out More About Single-phase Motor