Structure selection and tuning of multi-variable PID controllers for an industrial benchmark problem

A new technique is presented based on genetic algorithms (GAs) for designing a multi-variable PID controller. The considered application is a gasifier benchmark problem, for which a number of performance and robustness requirements are defined. In addition, actuator constraints are also considered. The proposed design procedure allows the optimisation of both controller parameters and structure. An advantage of the proposed technique over standard optimal control techniques (H₂ and H_∞ methods) is its ability to take non-linear constraints and dynamics into account in the design algorithm in a straightforward manner. A disadvantage of the proposed technique is the potentially large computation time required by GA. To overcome this problem, the optimisation is performed over several stages. First the structure is optimised, then basic controllers are designed (only PI terms) and finally a derivative term is added if needed. Simulation results on the gasifier problem have confirmed the superiority of the proposed technique in terms of achieved performance and robustness; moreover, the computation time of the overall design procedure is significantly reduced when compared with a standard GA approach. A controller that meets all design objectives under all operating conditions, and satisfies all input-output constraints, is presented.