My first exposure to model predictive control, MPC, was in late 1979 when I attended a meeting called by Bob Otto, ISA Fellow. Bob had just returned from the AIChE 86th Annual National Meeting where he sat in on Charlie Cutler and Ramaker’s presentation of their paper Dynamic matrix control-a computer control algorithm. This landmark work by Shell was the fore runner of modern day model predictive control, MPC. Bob’s assessment was that this technology represented one of the most important developments he had seen in process control. The power of MPC technology comes from the fact that the controller is generated based on a process step response or impulse response model and is designed to minimize the control error over a prediction horizon. Control performance is determined by parameters that specify penalty on error and penalty on move. Soon after Shell’s public announcement of their work on dynamic matrix control, Charlie went on to form the DMC Corporation. Since that time, major suppliers of MPC technology have successful addressed a variety of applications. The wide spread acceptance of MPC technology is well documented in the paper by Professors Joe Qin and Tom Badgwell, A survey of industrial model predictive control technology.
In the early-80’s, Bob Otto lead an initiative within Emerson to explore the feasibility of embedding MPC technology within a distributed control system. This research focused primarily on single loop applications as documented in the paper Development of a Multivariable forward modeling controller by Bob Otto and Kelvin Erickson. Field trails were conducted using a prototype of single loop MPC. One of the technical challenges that prevented general deployment of this technology at that time was the need to provide a robust means of process identification. Also, it was not feasible at that time to embed general MPC in the controller because of the associated CPU and memory requirements.
By the later-90’s, the availability of low cost memory and vastly improved processor performance made it feasible to fully embed MPC technology within the control system. By embedding MPC in the control system, a control system supplier can provide an environment that makes it easier and quicker to engineer and commission MPC applications. Also, by embedding MPC in the controller, it is possible to address applications that require faster control execution e.g. 1sec period of execution. In many cases, embedded MPC control is a valid alternative to the traditional PID based strategies for deadtime compensation, feedforward and override control. If you have no experience with MPC, then some examples of how MPC may be effectively used to replace traditional PID based strategies are contained in the following:
These examples are based on the DeltaV MPC capability introduced in 2000, DeltaV Predict. This initial capability was targeted at smaller applications (no larger in size than 8×8). The DeltaV advanced control team later developed DeltaV PredictPro to address larger applications (as large as 40×80 in size).