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As control systems expand into networks of axes regulating complex motions, meeting specifications is a growing challenge. If the only requirement is to get from A to B, simple step input is usually sufficient. But for motion systems that comprise multiple axes and require smooth, multi-point motions, controlled input is required. For these complex operations, dynamics are linearized around operating points. From there software-based automatic tuning mechanisms can determine optimal test and performance parameters. Besides accomplishing this more efficiently than traditional tuning methods, automatic tuners alleviate more system resonance problems, increase efficiency, and more finely tune axes for high performance.

Identification

This first step in the “automatic” tuning process is to collect data. To begin, a search is carried out for a low-bandwidth controller that will prevent motor drift during measurements. Then the plant (machine) transfer function is measured using a tight list of frequencies. During this procedure a series of commands at different frequencies are fed to the motor, and the resulting motor responses measured. The plant transfer function can be calculated from measured feedback over the specified frequency range. Because machines that absorb energy may experience harmful vibrations, maximum continuous and peak current must be defined by the user for each application to avoid damage.

Controller selection

This is the second step in the automatic tuning process. The goal is to choose a good linear design that minimizes control efforts and counters sensor noise by producing a low-current command at the machine drive. Controllers must also be sufficiently robust to offset uncertainty. Finally, they must have appropriate gain and phase margins to meet application requirements while not exceeding demands or negatively affecting closed-loop performance.

Some of the control schemes for which automatic tuning must work include:

• Speed controllers, which follow a speed trajectory. These controllers include a PI and a low-pass filter. A standard speed controller is usually driven by an external position controller, which is similar to some internal feedback loops. Automatic tuners integrate optional notch filters if needed.

Speed-controlled feedback systems can be tested for square-wave reference commands. Smoothing these commands improves performance.
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• Position controllers, which follow a position trajectory. These controllers use the position trajectory and its derivative (speed) as the trajectory command. Position controllers must include a PID and a low-pass filter. As in speed controllers, automatic tuners independently integrate notch filters when needed.

• Dual-loop position controllers, which follow a position trajectory with an inner speed loop and an outer position loop. The inner-loop controller is a speed controller, while the outer loop is a simple gain controller or a PI filter.

In addition to having a good linear design, controllers should overcome linear phenomena. One threat is loss of stability or too large an overshoot when the current driving the motor saturates. If saturation occurs, the controller must recover quickly. Another linear phenomenon to protect against is an excessively large and noisy limit cycle. At high speeds, encoders can be used as tachometers to stabilize loaded motors. At lower speeds, this is not possible and results in unacceptable limit cycles. Instead, some systems include time-varying, speed-dependent switching controllers integrated with gain-scheduling algorithms to overcome limit cycle problems.

Test execution

All software must be tested before use, and automatic tuners are no exception. the identified motor (together with user-supplied parameters for current saturation and shaft-angle range) is run to calculate key trajectories in which motor current does not saturate and shaft angle remains within its permitted range. Controlled feedback systems can be tested with square-wave reference commands for speed-controlled systems and smooth-position squarewave reference commands for position or dual-loop systems. Actual controller behavior can be determined by evaluating small and big signals. For small signals, controllers don’t saturate the servo amplifier; smallsignal behavior reveals the full controller bandwidth according to settling time.

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