Skip to main content

TUNING OF A PROPORTIONAL–INTEGRAL–DERIVATIVE CONTROLLER USING A MULTIOBJECTIVE GENETIC ALGORITHM NONDOMINATED SORTING GENETIC ALGORITHM-II APPLIED TO A pH PROCESS

The full text article is not available.

At present, only title information is available on ingentaconnect.com for this article. This is due to copyright restrictions.

Abstract:

ABSTRACT

Most control engineering problems are characterized by several, often contradicting, objectives, which have to be satisfied simultaneously. Two widely used methods for finding the optimal solution to such problems are aggregating to a single criterion, and using Pareto-optimal solutions. Here we propose the nondominated sorting genetic algorithm (NSGA-II) to find the constant proportional–integral–derivative (PID) control gains for a chemical neutralization plant. Known to be highly nonlinear and with varying time delay, this plant provides a challenging test bed for nonlinear control strategies. The results confirm that a multiobjective, Pareto-based GA search gives a better performance than a single objective GA. The former method was also used to design a gain-scheduled PID controller. PRACTICAL APPLICATIONS

The control of the pH neutralization process plays a very important role in chemical industries, such as wastewater treatments, polymerization reactions, fatty acid production, biochemical processes, pharmaceuticals, biotechnology and so on. The pH neutralization process shows a strong nonlinear behavior and time-varying nonlinear characteristics resulted from the variation of the feed components or total ion concentrations. In the case of fermentation by the microorganisms, the growth of microorganisms has a pH optimum similar to most biochemical processes. A pH value drifting away from this optimum often inhibits growth of the essential microorganisms, alters the bacterial population and inhibits the desirable enzymatic activities. The result is a delay in the fermentation process, which in turn results in financial loss.

Document Type: Research Article

DOI: https://doi.org/10.1111/j.1745-4530.2008.00356.x

Publication date: 2010-02-01

  • Access Key
  • Free ContentFree content
  • Partial Free ContentPartial Free content
  • New ContentNew content
  • Open Access ContentOpen access content
  • Partial Open Access ContentPartial Open access content
  • Subscribed ContentSubscribed content
  • Partial Subscribed ContentPartial Subscribed content
  • Free Trial ContentFree trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more