Almost all motion controllers on the market today can synchronize two or more axes. But too many times, this merely means that the controller has the ability to effectively parallel command signals to two or more drives, or follow a master encoder. While in the strictest sense this can be described as synchronous motion, often it is not enough command to coordinate multiple axes that must work together to produce usable products on machines.
To determine what level of control is needed for synchronous applications, let's look at two typical cases.
On gantry systems, it's very common for two motors to work as a pair on parallel axes running the length of one Cartesian plane. In this case, it would seem logical to command the X and X motors, for example, from the same signal, but it's usually not the answer.
Assume we have a dual-axis press and, as is often the case, one of the rails is loaded more heavily than the other. Under these circumstances, commanding both motors with a common signal will likely cause the less heavily loaded motor to lead the other.
One way to prevent this application-induced error is with a control approach that establishes a 0° angular difference across the (X and X) rails as a reference point. Maintaining the reference point keeps the two motors in line, holding the machine in synch even if the load shifts.
Implementing this type of “lock” control is no easy task. A lock command measures the offset between axes caused by the load, scales it, and then cascades it (with the drive command), producing a “locked-axis signal” for each motor amplifier. In addition, the system's integrity is actively managed by individually adjustable gains for each motor, preventing skew between the two synchronized axes. This attention to detail is required, however, and is often the difference between a working machine and one that functions but is incapable of producing repeatable results.
Another class of motion benefiting from full synchronization is the widely employed camming function. Cams have been used for years to establish complex timing relationships, especially in web processing applications. More frequently, however, teams of servomotors coordinated by cam-emulating algorithms do the same job faster and more reliably — and can be reprogrammed on the fly.
A good example of a discrete motion-centric manufacturing process that relies on electronic camming can be found in any modern plant that makes shotgun shells. A 12-guage shotgun shell costs less than a quarter, but the liability associated with a faulty product could bankrupt many cities. To keep hunters happy and lawyers at bay, ammunition factories must produce high-quality products in high quantity, while maintaining high repeatability despite plant temperature variations, humidity levels, time of day, or how long machines have been running.
Suppose, in this example, that one of the motion system design goals is to maintain a 3:1 angular ratio between the nip rolls and cutting wheel on the web line where the plastic casing is formed. Naturally, the controller must be able to handle round-off error in order to generate digital commands that comply with the required ratio and, more importantly, keep the two axes turning in precise synchronization. This calls for a digital processor with floating-point math and automatic rollover a bit handling function that knows what to do when a register value reaches its limit. Otherwise, cumulative errors will make it impossible to maintain the desired relationship, causing all sorts of manufacturing problems.
There are other complicating factors, however. Extruded materials in a web-handling system must be processed at whatever speed they come off the roll or extruder; all timed operations must be consistent and in synch regardless of unexpected variations in speed. One of the challenges in maintaining this angular ratio between the nip rolls and cutting wheel is that the nips continually change speed in order to exert constant pressure on the hot extruded plastic.
Tool wear and other age-related issues also pose a problem. The variations caused by these mechanisms introduce a sort of phase shift in the angular relationship between the product and cam profile.
One solution is to maintain a cam with different data densities for different stages of a process. A cam can be pointed to a high-density array for dynamic operations — when knives are slicing through product, for example. Then in more static or coarse-movement situations, as when knives hover above product or when they return to a home position, the cam can be pointed to a low-density array.
What's more, manipulating the data arrays to advance or retard phase can extend blade life by ensuring that each engagement begins at the optimal starting point.