Multivariable PI Tuning in Dynamic Position Control of Ships

Martin, P.; Yamamoto, Ikuo; Katebi, M.R.; Grimble, M.J.

doi:10.1016/s1474-6670(17)37054-4

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…Linear models, if they are available can also be used to improve the control design. Among the most common non-parametric PID tuning methods there are : Davison method [25], PenttinenKoivo method [26] , Maciejowski method [27] and the combined method proposed by [28] that combines ideas from the three methods. In this paper, the best values for the PID gains are found using the above multivariable non-parametric PID tuning methods as described in [29].…”

Section: Pid Tuningmentioning

confidence: 99%

Modeling and Supervisory Control Design for a Combined Cycle Power Plant

Abokhatwa¹,

Katebi²

2012

Software Engineering / 781: Control Applications

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The traditional control strategy based on PID controllers may be unsatisfactory when dealing with processes with large time delay and constraints. This paper presents a supervisory model based constrained predictive controller (MPC) for a combined cycle power plant (CCPP). First, a non-linear dynamic model of CCPP using the laws of physics was proposed. Then, the supervisory control using the linear constrained MPC method was designed to tune the performance of the PID controllers by including output constraints and manipulating the set points. This scheme showed excellent tracking and disturbance rejection results and improved performance compared with a stand-alone PID controller's scheme. KEY WORDSCombined cycle power plant, PID Control, Linearization, Supervisory Model Predictive Control.

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Section: Pid Tuningmentioning

confidence: 99%