2013
DOI: 10.1016/j.jprocont.2013.02.007
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A multivariable IMC-PID method for non-square large time delay systems using NPSO algorithm

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Cited by 39 publications
(39 citation statements)
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“…The numerator of this controller element is given by the desired closed-loop transfer function t i (s) which must be specified with a time delay, relative degree, and RHP zero multiplicity equal or greater than that of g ik (s) to achieve realizability in qd ki (s). In contrast, according to (10), t i (s) appears in the denominator of the corresponding controller elements qo ij (s). Therefore, for realizability, the three previous aspects of t i (s) must be specified less or equal than the least ones of the other g ij (s) elements different from g ik (s) in the row i.…”
Section: Realizability and Closed-loopperformancementioning
confidence: 99%
See 1 more Smart Citation
“…The numerator of this controller element is given by the desired closed-loop transfer function t i (s) which must be specified with a time delay, relative degree, and RHP zero multiplicity equal or greater than that of g ik (s) to achieve realizability in qd ki (s). In contrast, according to (10), t i (s) appears in the denominator of the corresponding controller elements qo ij (s). Therefore, for realizability, the three previous aspects of t i (s) must be specified less or equal than the least ones of the other g ij (s) elements different from g ik (s) in the row i.…”
Section: Realizability and Closed-loopperformancementioning
confidence: 99%
“…Different approaches have been developed in order to design controller for multivariable systems with multiple time delays: some authors have extended the SP to the multivariable case [7][8][9]. In line with the previous ones, other works propose to solve the problem by means of an internal model control (IMC) applied to MIMO processes [10,11]. There is a close relationship between PS and IMC [12] since the SP can expressed in an equivalent IMC structure as shown in Figure 1 where G m is the multi-delay model of the plant.…”
Section: Introductionmentioning
confidence: 99%
“…With the rapid development of swarm intelligent theory, many PID controller parameters self-tuning methods based on the swarm intelligent theory appeared, such as genetic algorithm (GA), particle swarm algorithm (PSO), etc. [10][11][12][13][14]. Genetic algorithm adopts the duplication, crossover and mutation operators, whose performance has a larger dependence on parameters.…”
Section: Open Accessmentioning
confidence: 99%
“…Although satisfactory results were obtained, the output was still undamped and there were many parameters need to be optimized. Bayu Jayawardhana,Hartmut Logemann and Eugene P.Ryan [16] presented a kind of PID control of second-order systems with hysteresis for constant reference signal asymptotic tracking and constant interference signal suppression.But the satisfactory robustness can not be obtained.Zhao and Wang [17] presented that use IMC-PID to control the superheated steam pressure.PID controller is still the most widely used controller in thermal power plant.Alberto Leva [18] introduced the performance and robustness improvement in the IMC-PID tuning method.In addition, the IMC-PID controller can be designed based on different algorithms,such as NPSO algorithm [19],LMI algorithm [20],Novel Bat algorithm [21] and so on.In summary, the IMC-PID controller is still widely applicable to solving the current practical process control problems. It can be believed that the application of IMC-PID control will obtain satisfactory control effect in the future.In this paper, the PID control algorithm based on IMC is studied in the process of second order inertia with pure delay.…”
Section: Introductionmentioning
confidence: 99%