Improving disturbance rejection of PID controllers by means of the magnitude optimum method.

The magnitude optimum (MO) method provides a relatively fast and non-oscillatory closed-loop tracking response for a large class of process models frequently encountered in the process and chemical industries. However, the deficiency of the method is poor disturbance rejection performance of some processes. In this paper, disturbance rejection performance of the PID controller is improved by applying the "disturbance rejection magnitude optimum" (DRMO) optimisation method, while the tracking performance has been improved by a set-point weighting and set-point filtering PID controller structure.

Comparative study of decay ratios of disturbance-rejection magnitude optimum method for PI controllers.

One of the key time-domain closed-loop performance requirements is the closed-loop response decay ratio. In this paper, the decay ratios of the disturbance-rejection magnitude optimum (DRMO) tuning method [Vrancić D, Strmcnik S, Kocijan J. Improving disturbance rejection of PI controllers by means of the magnitude optimum method.

Pattern recognition-based supervision of indirect adaptation for better disturbance handling.

An advanced pattern recognition-based supervision algorithm for an indirect adaptive controller is proposed. The aim is to improve performance under certain conditions that are common in the industrial environment, in which indirect adaptive controllers with simple supervision are known to perform poorly or unreliably. Specifically, the problem of large invasive unmeasured disturbances of short or longer duration is addressed.

Comparison of control strategies for nitrogen removal in an activated sludge process in terms of operating costs: a simulation study.

In this paper several control strategies for nitrogen removal are proposed and evaluated in a benchmark simulation model of an activated sludge process. The goal is to determine which control strategy delivers better performance with respect to plant operating costs. In the study, constant manipulated variables and various PI and feedforward control strategies are tested and compared with predictive control, which uses an ideal process model.

Improving disturbance rejection of PI controllers by means of the magnitude optimum method.

The magnitude optimum (MO) method provides a relatively fast and nonoscillatory closed-loop tracking response for a large class of process models frequently encountered in the process and chemical industries. However, the deficiency of the method is poor disturbance rejection when controlling low-order processes. In this paper, the MO criterion is modified in order to optimize disturbance rejection performance, while the tracking performance has been improved by an integral set-point filtering PI controller structure.