Processors suitable for digital control range from standard microprocessors like 8051 to special purpose DSP processors, the primary difference being in the instruction sets and speed(s) of particular instruction(s), such as multiply. Standard microprocessors or general purpose processors are intended for laptops, workstations, and general digital data bookkeeping. Naturally, because digital control involves much numerical computation, the instruction sets for special-purpose DSP processors are rich in math capabilities and are better suited for control applications than the standard microprocessors or general purpose processors.
Processors, such as those found in microwave ovens have a broad range of requirements. For example, the speed, instruction set, memory, word length, and addressing mode requirements are all very minimal for the microwave oven. The consequences of a data error are minimal as well, especially, relative to a data error in a PC/laptop while it is calculating an income tax return. PC’s or laptops, on the other hand, require huge megabytes of memory, and they benefit from speed, error correction, larger word size, and sophisticated addressing modes.
DSP processors generally need speed, word length, and math instructions such as multiply, multiply-and-accumulate, and circular addressing. One typical feature of signal processors not found in general purpose processors is the use of a Harvard architecture, which consists of separate data and program memory. Although separate data and program memory offer significant speed advantages, the IC pin count is higher assuming external memory is allowed because instruction address, instruction data, data address, and data buses are separate. A modified Harvard architecture has been used which maintains some speed advantage, while eliminating the requirement for separate program and data buses, greatly reducing pin count in processors that have external memory capability (almost all have this feature).
While thinking of control versus signal processing applications, in the former, we often employ saturation and therefore absolutely require saturation arithmetic; whereas in the latter, to ensure signal fidelity, in most signal processing applications the algorithms must be designed to prevent saturation by scaling signals appropriately.
The consequences of numerical overflow in control computations can be serious, even destabilizing. In most forms of numerical computation, it is usually better to suffer the non-linearity of signal saturation than the effects of numerical overflow.
For most control applications, it is advantageous to select a processor that does not require much support hardware. One of the most commonly cited advantages of digital control is the freedom from noise in the control processor. Although it is true that controller noise is nominally limited to equalization noise, it is not true that the digital controller enjoys an infinite immunity from noise. Digital logic is designed with certain noise margins, which of course are finite. When electromagnetic radiation impinges on the digital control system, there ia finite probability of making an error. One of the consequences of digital control is that although it can have a very high threshold of immunity, without error detection and correction it is equally likely that the system will make a large error as a small one — the MSB and the LSB of a bus have equal margin against noise.
In addition to external sources of error-causing signals, the possibility for circuit failure exists. If a digital logic circuit threshold drifts outside the design range, the consequences are usually catastrophic.
For operational integrity, error detection is a very important feature.
I hope to compare, if possible, some families of Digital Control processors here, a bit later.
Digital Control of Dynamic Systems, Franklin, Powell and Workman.