A performance optimization algorithm for controller reconfiguration in fault tolerant distributed model predictive control

Zakharov, Alexey; Zattoni, Elena; Yu, Miao; Jämsä‐Jounela, Sirkka‐Liisa

doi:10.1016/j.jprocont.2015.07.006

Cited by 24 publications

(5 citation statements)

References 46 publications

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“…Therefore, it is necessary to take into account the multiple characteristics of the process, which complexity is reinforced by the stringent environmental and safety requirements of the oil well drilling industry. [44][45][46] Such circumstances stimulate further research on control structures that fit into distinct operational levels (control reconfiguration). [47] This controller flexibility is also important for the safety of the operation.…”

Section: Introductionmentioning

confidence: 99%

Transient Open‐Closed Loop Experimental Validation of a Nonlinear Two‐Phase Flow Distributed System

Vega

Carvalho

Oliveira

et al. 2023

Macro Reaction Engineering

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The oil well drilling process is a nonlinear system with transient nature. Conventional drilling is unable to assure safe and cost‐effective operation for fractured, cavernous, and highly permeable carbonate reservoirs, which contain the largest oil reserves worldwide. Concerning drilling technologies, Pressurized Mud Cap Drilling (PMCD) is suitable for the challenging scenario previously mentioned. According to PMCD technique, a sacrificial fluid is injected through the drill string and a light annular mud is pumped in countercurrent through the annulus region (bullheading), without surface return, forcing gas and drilled cuttings back to formation. A two‐phase flow distributed model (Drift Flux Model – DFM) is developed to properly describe the complex nature of the system. Also, an experimental facility, presenting field similarity, is employed to validate the open – closed loop schemes. The main objective of the controller (control reconfiguration with gain scheduling) is to regulate annulus pressure, handling gas kick, drilling fluid losses and inverse response dynamics. Besides, gas injection, migration and bullheading are studied. The simulations, validated through experimental data, highlight the methodology usefulness for field applications.

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Section: Introductionmentioning

confidence: 99%

Transient Open‐Closed Loop Experimental Validation of a Nonlinear Two‐Phase Flow Distributed System

Vega

Carvalho

Oliveira

et al. 2023

Macro Reaction Engineering

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“…In this complex situation, it is necessary to seek new control methods. As a current control algorithm, model predictive control (MPC) is widely used because of its ability to improve control performance [28][29][30][31][32][33][34][35]. Especially for a class of systems whose process is nonlinear and its exact model is difficult to obtain or whose process time delay is large, this method is more popular.…”

Section: Introductionmentioning

confidence: 99%

Genetic-Algorithm-Optimization-Based Predictive Functional Control for Chemical Industry Processes Against Partial Actuator Faults

2020

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Actuator faults, which are common in industrial processes, can make the controller fail to achieve the desired control objectives, which may lead to the degradation of control performance. In order to solve this problem, this paper proposes a predictive functional control based on genetic algorithm optimization. Firstly, an extended dimension discrete switched model is constructed, which consists of a state difference variable, tracking error and a new state variable including tracking error. In this model, the performance index function based on a genetic optimization algorithm is selected, and its parameters are adjusted and the controller is designed. Then, under the obtained control law, the switching signal is designed and the range of uncertainty caused by the actuator fault is given to realize the robustness of the system. At the same time, the corresponding robustly sufficient conditions are presented. The advantage of this design is to avoid the disadvantages of manually adjusting the performance parameters, and the system has good tracking performance. Finally, taking the typical injection molding process of chemical production process as an example, the speed and pressure parameters are controlled, and compared with the traditional control method, the effectiveness and feasibility of the proposed method are verified. INDEX TERMS Chemical industry processes, partial actuator faults, genetic-algorithm-optimization design, predictive functional control

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“…Methods discussed include state feedback control [15], active disturbance rejection control [16] as well as model predictive control (MPC) [17]. MPC is widely recognized as a practical control approach to yield high performance for series systems [18,19,20], where all the information is gathered into one model predictive controller to effect global optimization and ensure high control performance [21]. 1 However, with the development of modern industry, the size of the series system is increasing, resulting in a need to control ever greater numbers of parameters.…”

Section: Introductionmentioning

confidence: 99%

Robust distributed model predictive control for systems of parallel structure within process networks

Zhang

Zhao

Spurgeon

2019

Journal of Process Control

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The parallel structure is one of the basic system architectures found in process networks. In order to achieve robust control of complex process networks, it is necessary to formulate control strategies that specifically accommodate the characteristics of such parallel systems. In this paper, the competitive coupling and competitive constraints in parallel systems are initially defined. A novel robust distributed model predictive control algorithm is then developed for such parallel systems which deals explicitly with competitive couplings, competitive constraints and uncertainties. The Lyapunov Method is used for the theoretical analysis which produces tractable linear matrix inequalities (LMI). Two simulation studies and an experimental trial are provided to validate the effectiveness of the proposed approach. These consider control of 40 user and 100 user gas boiler heating systems as well as control of two continuous stirred tank reactors (CSTRs) which are connected in parallel.

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A performance optimization algorithm for controller reconfiguration in fault tolerant distributed model predictive control

Cited by 24 publications

References 46 publications

Transient Open‐Closed Loop Experimental Validation of a Nonlinear Two‐Phase Flow Distributed System

Transient Open‐Closed Loop Experimental Validation of a Nonlinear Two‐Phase Flow Distributed System

Genetic-Algorithm-Optimization-Based Predictive Functional Control for Chemical Industry Processes Against Partial Actuator Faults

Robust distributed model predictive control for systems of parallel structure within process networks

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