Design of RTDA controller for industrial process using SOPDT model with minimum or non-minimum zero

Anbarasan, K.; Srinivasan, K.

doi:10.1016/j.isatra.2015.02.016

Cited by 16 publications

(4 citation statements)

References 29 publications

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“…The constrained optimization problem is formulated and solved systematically. The tuning rule proposed for the second order RTDA controller 30 is used to choose the tuning parameters of the local RTDA controllers. Tuning parameters chosen for both the methods is given in Table 6.…”

Section: Simulation Examplesmentioning

confidence: 99%

“…RTDA control algorithm applications in different control problems were reported in various research articles 29‐31 . Different tuning rules for the RTDA control algorithm are available in literature 32,33 .…”

Section: Introductionmentioning

confidence: 99%

“…Different tuning rules for the RTDA control algorithm are available in literature 32,33 . The controller is successfully extended to handle various control problems, including processes with higher order dynamics, 30 and being multivariable with input and output constraints 34 . Though a varied list of RTDA control application studies is available over that last few years, there are no studies to explain a systematic approach for nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

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Scalable multiple linear model RTDA controller formulation for constrained nonlinear processes

Haseena

Srinivasan

2021

Optim Control Appl Methods

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Robustness, tracking, disturbance rejection and overall aggressiveness (RTDA) controller is a next generation control strategy with good robustness, tracking, and regulatory performance. This article proposes a scalable multiple linear model based RTDA (M‐RTDA) control scheme to handle nonlinear processes with or without constraints effectively. Multiple linear models at different operating regions are used to represent the nonlinear dynamics of the system. The optimal local linear models are identified using the gap metric based technique. The linear model and the corresponding RTDA controller at each operating region are combined to get a model‐controller unit. The output of each model controller unit is integrated using a fuzzy scheduling technique to ensure bumpless transfer. The effectiveness of the proposed technique is demonstrated through simulation using nonlinear benchmark processes like pH neutralization and continuous stirred tank reactor (CSTR) process with constraints. The block diagram representation of the scalable M‐RTDA controller is developed, and the step‐by‐step procedure (algorithm) to implement the proposed concept is discussed. The proposed scalable multiple linear model scheme is easily reconfigurable as per the performance/operator requirement without affecting the other local RTDA controllers. The qualitative and quantitative performances are compared with the results of the direct extended multiple model based RTDA (DE‐RTDA) controller and dynamic matrix controller(DMC).

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Section: Simulation Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Scalable multiple linear model RTDA controller formulation for constrained nonlinear processes

Haseena

Srinivasan

2021

Optim Control Appl Methods

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“…2 to design an optimum controller for the nonlinear CSTR process. CSTR is one of the benchmark problems considered by researchers in testing the controller performance as is evident in [6,29,36]. The CSTR process exhibits a high nonlinear relationship between the inlet coolant flow rate (q c (t)) and the concentration C(t).…”

Section: Hmabc-based Optimum Controller For Cstrmentioning

confidence: 99%

Bulletin of the Polish Academy of Sciences: Technical Sciences

Pugazhenthi¹,

Selvaperumal²,

Vijayakumar³

2021

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The artificial bee colony (ABC) algorithm is well known and widely used optimization method based on swarm intelligence, and it is inspired by the behavior of honeybees searching for a high amount of nectar from the flower. However, this algorithm has not been exploited sufficiently. This research paper proposes a novel method to analyze the exploration and exploitation of ABC. In ABC, the scout bee searches for a source of random food for exploitation. Along with random search, the scout bee is guided by a modified genetic algorithm approach to locate a food source with a high nectar value. The proposed algorithm is applied for the design of a nonlinear controller for a continuously stirred tank reactor (CSTR). The statistical analysis of the results confirms that the proposed modified hybrid artificial bee colony (HMABC) achieves consistently better performance than the traditional ABC algorithm. The results are compared with conventional ABC and nonlinear PID (NLPID) to show the superiority of the proposed algorithm. The performance of the HMABC algorithm-based controller is competitive with other state-of-the-art meta-heuristic algorithm-based controllers in the literature.

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A new design of predictive plus PID control for second order plus time delay systems

Hu,

Bai,

Zou

2024

Can J Chem Eng

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This paper proposes two novel predictive proportional‐integral‐derivative (PID) controllers for second‐order non‐self‐balance systems and self‐balance systems with time delays. For second‐order non‐self‐balance systems with time delays, traditional predictive PID controllers suffer from the drawback of failing to return to the setpoint after disturbances. Therefore, this paper introduces a novel double predictive PID controller, termed PPI‐PPD controller, which consists of an inner‐loop predictive PD controller and an outer‐loop predictive PI controller. In second‐order self‐balance systems encountered in practical chemical processes, time delays can lead to longer adjustment times, increased overshoot, and divergence issues. In order to solve these problems, an improved predictive PID (PPID) controller is proposed in this paper, which introduces a compensation link and an anti‐interference link in the traditional predictive PID controller. This enhancement improves the dynamic response and disturbance resistance of the control system. Simulation results demonstrate that both novel predictive PID controllers exhibit excellent control performance and robustness.

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Design of RTDA controller for industrial process using SOPDT model with minimum or non-minimum zero

Cited by 16 publications

References 29 publications

Scalable multiple linear model RTDA controller formulation for constrained nonlinear processes

Scalable multiple linear model RTDA controller formulation for constrained nonlinear processes

Bulletin of the Polish Academy of Sciences: Technical Sciences

A new design of predictive plus PID control for second order plus time delay systems

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