(662a) A Methodology to Integrate Process Design and Process Control for Chemical Processes

The current methodologies available to perform the integration of process design and control involve complex optimization problems which require time consuming simulations, even for simple processes. In the present research, a new practical methodology will be introduced to optimally design chemical processes under closed loop control. This new approach applies quadratic Lyapunov stability to ensure process stability whenever the process is affected by perturbations or plant uncertainties during its operation. Instead of simulating the overall plant behavior, the present methodology estimates the maximum variability in the process outputs by applying the concept of quadratic Lyapunov performance to find the worst-case scenario. In addition, the process variability is also used to assign an economic value to the process dynamic performance.

In order to demonstrate its potential, the proposed methodology was used in the design of a mixing tank problem. This problem, introduced by Mohideen et. al. 1996, was selected as a preliminary case study to test the methodology because it is relatively simple and the results of the current approach can be compared to Mohideen's method. Although the problem may seem simple, the optimal design of this process is a difficult task because the final design must reject any possible bounded disturbance and process operating condition uncertainty during normal operation. For this case, three different control strategies were considered to optimally design the mixing tank.

The results show that Mohideen's approach produced the most economical design. However, their design was limited to a fixed number of hours of operation. Also, the manipulated variables that were not used by the control strategy were calculated based on a numerical optimization over the pre specified operation time horizon. In the present approach, although the cheapest design achieved is 20% higher in cost than Mohideen's, the optimal design is not restricted to a certain period of operation, all the available manipulated variables are calculated based on easily implemented control calculations, and process stability is ensured during the entire period of operation. Therefore, the proposed methodology presented here considers a more realistic situation.