Abstract
Programmable logic controllers (PLCs) have the benefit of being able to withstand a variety of environments while maintaining high reliability compared to computers and other controllers. Traditionally, PLCs have been used for simple ON-OFF control schemes or for proportional-integral-derivative (PID) control. However, recent developments in technology have allowed even low-cost PLCs to implement more advanced and efficient algorithms. This paper investigates a PLC implementation of the specialized Projected Gauss-Seidel (PGS) algorithm. The PGS algorithm is able to quickly and efficiently solve both symmetric and asymmetric mathematical programming problems. The algorithm can be further utilized to solve more complicated problems such as model predictive control (MPC). The focus of this paper is to solve a general constrained optimization problem on a PLC and to expand the capability to solve a MPC example. The DirectLogic Do-More PLC is exploited both for computational efficiency and for memory utilization.
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