Control Engineering Practice最新文献

英文中文

Stability-guaranteed data-driven nonlinear predictive control of water distribution systems

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-23 DOI: 10.1016/j.conengprac.2025.106243

Saskia A. Putri, Faegheh K. Moazeni

Stability in the operation of water distribution systems (WDSs) is paramount to maintaining efficient and reliable water delivery. Nonlinear model predictive control (NMPC) emerged as a suitable control strategy due to WDSs’ inherent nonlinearity and cross-coupling dynamics. However, classical NMPC is formulated under a finite horizon and does not guarantee closed-loop stability. It also relies heavily on intricate model-based dynamics, a cumbersome and time-consuming process for large-scale WDSs. This paper proposes a comprehensive control strategy that employs a data-enabled model identification technique, replacing physics-based models and ensuring stability and recursive feasibility via quasi-infinite horizon NMPC. The main objective of this work is to satisfy the water demand at every time step while guaranteeing a stable pressure head and energy-efficient pump operation in the WDS. A complete stability and feasibility analysis of the control strategy is also provided. Extensive simulations validate the proposed method demonstrating (1) data-driven model accuracy with an unseen and noisy dataset exhibiting 0.01% error and (2) optimal WDS operation under nominal and robust conditions, ensuring demand compliance, cost-savings by 8% ($18k annually), and pressure head stability within 5% of the steady-state value.

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引用次数: 0

Multivariable robust control of sirius modular current source prototype

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-22 DOI: 10.1016/j.conengprac.2025.106244

Thiago T. Cardoso , Pedro M. de Almeida , André A. Ferreira , Gabriel O. Brunheira , Bruno E. Limeira , Pedro G. Barbosa , Vinícius F. Montagner

This paper presents the design and experimental validation of a multivariable robust control strategy applied to the Brazilian Synchrotron Light Laboratory booster current source. The source, tasked with delivering a triangular waveform current, necessitates precise tracking with an error tolerance of less than 100 parts per million, in order to precisely inject electrons into the storage ring. Characterized by a complex, high-order multi-input multi-output structure with multiple series and parallel power modules, the system complexity is addressed through a model reduction technique based on the Hankel norm. Leveraging the reduced-order plant during controller design not only simplifies the system but also results in a lower-order controller. To guarantee robust stability and performance for the full-order plant, the approximation error is reintroduced as uncertainty into the reduced-order model. The controller design employs a weighted

H_{\infty}

approach. Experimental validation using a small-scale prototype confirms the effectiveness of the proposed methodology in achieving precise tracking and robust performance.

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引用次数: 0

Parameter-free ultralocal model-based predictive current control method for grid-tied inverters using extremum seeking control

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-22 DOI: 10.1016/j.conengprac.2025.106253

Xiaoxiao Huo, Po Li

This paper delves into the control engineering challenges faced by grid-tied inverter systems stemming from uncertainties such as unidentified physical parameters, unmodeled dynamics, and disturbances. To mitigate these challenges, this paper introduces a parameter-free ultralocal model method based on extremum seeking control (ESC). Firstly, the unmodeled part of the system is estimated using the extended state observer (ESO), and the current is predicted using the ultralocal model. Secondly, an online optimizer for ultralocal model control gain parameter based on ESC is designed to adjust the control gain, aiming to minimize current prediction error. This approach effectively disentangles the control performance from reliance on physical parameters and mitigates the impact of system uncertainties. Ultimately, the efficacy of the proposed approach is validated by hardware-in-the-loop (HIL) experiments and compared with conventional model-based and model-free current predictive control strategies. The comparative analysis underscores the method’s potential to significantly enhance disturbance rejection capabilities and overall system robustness.

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引用次数: 0

Experimental validation of scenario-based stochastic model predictive control of nanogrids

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-22 DOI: 10.1016/j.conengprac.2025.106249

Vahid Hamdipoor , Hoai Nam Nguyen , Bouchra Mekhaldi , Johan Parra , Jordi Badosa , Fausto Calderon Obaldia

In microgrids and nanogrids, challenges arise from the inherent intermittency of renewable energy sources and the need to meet uncertain energy demand from users. To address these uncertainties, this paper investigates a two-layer, scenario-based stochastic Model Predictive Control (MPC) for a real lab-scale photovoltaic (PV)-based nanogrid. The high-level layer, which operates slowly and over longer time horizons, computes optimal reference values for the low-level layer based on predictions of uncertainty in PV generation and consumer load. The low-level layer, which operates on shorter time horizons and at higher frequencies, relies on scenario-based MPC. Scenario-based MPC has several advantages, such as not requiring prior knowledge of the underlying probability distribution. However, it can suffer from significant computational burdens, especially in real-time applications like nanogrid control. To overcome this challenge, this paper employs the Alternating Direction Method of Multipliers (ADMM) to efficiently solve the optimization problem. First, real PV and load data are used to characterize the scenarios. Then, the proposed scheme is experimentally validated on a PV-based nanogrid. The results show that the two-layer scenario-based MPC outperforms the two-layer chance-constrained MPC and significantly improves performance compared to a rule-based energy management system.

{"title":"Experimental validation of scenario-based stochastic model predictive control of nanogrids","authors":"Vahid Hamdipoor , Hoai Nam Nguyen , Bouchra Mekhaldi , Johan Parra , Jordi Badosa , Fausto Calderon Obaldia","doi":"10.1016/j.conengprac.2025.106249","DOIUrl":"10.1016/j.conengprac.2025.106249","url":null,"abstract":"<div><div>In microgrids and nanogrids, challenges arise from the inherent intermittency of renewable energy sources and the need to meet uncertain energy demand from users. To address these uncertainties, this paper investigates a two-layer, scenario-based stochastic Model Predictive Control (MPC) for a real lab-scale photovoltaic (PV)-based nanogrid. The high-level layer, which operates slowly and over longer time horizons, computes optimal reference values for the low-level layer based on predictions of uncertainty in PV generation and consumer load. The low-level layer, which operates on shorter time horizons and at higher frequencies, relies on scenario-based MPC. Scenario-based MPC has several advantages, such as not requiring prior knowledge of the underlying probability distribution. However, it can suffer from significant computational burdens, especially in real-time applications like nanogrid control. To overcome this challenge, this paper employs the Alternating Direction Method of Multipliers (ADMM) to efficiently solve the optimization problem. First, real PV and load data are used to characterize the scenarios. Then, the proposed scheme is experimentally validated on a PV-based nanogrid. The results show that the two-layer scenario-based MPC outperforms the two-layer chance-constrained MPC and significantly improves performance compared to a rule-based energy management system.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"157 ","pages":"Article 106249"},"PeriodicalIF":5.4,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on coordinated control of electro-hydraulic composite braking for an electric vehicle based on the Fuzzy-TD3 deep reinforcement learning algorithm

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-21 DOI: 10.1016/j.conengprac.2025.106248

Zhengrong Chen , Renkai Ding , Qin Zhou , Ruochen Wang , Binggen Zhao , Yinsheng Liao

In order to improve the energy utilization efficiency of electric vehicles, alleviate range anxiety, and ensure braking stability and comfort, a coordinated control strategy of electro-hydraulic composite braking (EHB) is proposed based on the fuzzy twin delayed deep deterministic policy gradient (Fuzzy-TD3) algorithm. A mathematical EHB system model is established. A particle swarm backpropagation (PSO-BP) neural network is used to determine the braking intensity of driver. Combined with the Fuzzy-TD3 algorithm to optimize the distribution of regenerative braking torque and hydraulic braking torque under normal braking, efficient recovery of braking energy is achieved to ensure braking stability and comfort. For emergency braking, the coordinated control of the anti-lock braking system (ABS) and the regenerative braking system (RBS) is realized by combining the sliding mode control (SMC) and the Fuzzy-TD3 algorithm. This effectively lowers the risk of wheel slip during emergency braking and enhances safety and ride comfort. The results show that compared to the conventional PID control method, the Fuzzy-TD3 control strategy lowers braking time by 11.5 % and 9.5 % under normal and emergency braking conditions, respectively. Additionally, the state of charge (SOC) of the battery increases by 0.487 % and 0.266 %, respectively. These findings are consistent with experimental data and validate the effectiveness of this strategy in improving braking performance and energy recovery efficiency.

{"title":"Research on coordinated control of electro-hydraulic composite braking for an electric vehicle based on the Fuzzy-TD3 deep reinforcement learning algorithm","authors":"Zhengrong Chen , Renkai Ding , Qin Zhou , Ruochen Wang , Binggen Zhao , Yinsheng Liao","doi":"10.1016/j.conengprac.2025.106248","DOIUrl":"10.1016/j.conengprac.2025.106248","url":null,"abstract":"<div><div>In order to improve the energy utilization efficiency of electric vehicles, alleviate range anxiety, and ensure braking stability and comfort, a coordinated control strategy of electro-hydraulic composite braking (EHB) is proposed based on the fuzzy twin delayed deep deterministic policy gradient (Fuzzy-TD3) algorithm. A mathematical EHB system model is established. A particle swarm backpropagation (PSO-BP) neural network is used to determine the braking intensity of driver. Combined with the Fuzzy-TD3 algorithm to optimize the distribution of regenerative braking torque and hydraulic braking torque under normal braking, efficient recovery of braking energy is achieved to ensure braking stability and comfort. For emergency braking, the coordinated control of the anti-lock braking system (ABS) and the regenerative braking system (RBS) is realized by combining the sliding mode control (SMC) and the Fuzzy-TD3 algorithm. This effectively lowers the risk of wheel slip during emergency braking and enhances safety and ride comfort. The results show that compared to the conventional PID control method, the Fuzzy-TD3 control strategy lowers braking time by 11.5 % and 9.5 % under normal and emergency braking conditions, respectively. Additionally, the state of charge (SOC) of the battery increases by 0.487 % and 0.266 %, respectively. These findings are consistent with experimental data and validate the effectiveness of this strategy in improving braking performance and energy recovery efficiency.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"157 ","pages":"Article 106248"},"PeriodicalIF":5.4,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Roll stability control of in-wheel motors drive electric vehicle on potholed roads

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-20 DOI: 10.1016/j.conengprac.2025.106247

Jiantao Wang , Xiaolong Zhang , Yawei Dong , Shuaishuai Liu , Lipeng Zhang

The dynamics performance of in-wheel motors drive electric vehicles can be greatly improved by adjusting the torque and speed of the in-wheel motors, but the increased unsprung mass will bring greater dynamic load impacts on the body when the vehicle runs on potholed roads, which may make the vehicle roll when turning. To improve the roll stability, a collaborative control based on four-wheel differential drive and suspensions active adjustment is proposed. At first, a vehicle-road coupled dynamics model on a potholed road is developed. Next, the spatial stability evolution mechanism of the vehicle and the coupling effects of four-wheel differential drive and active suspensions control on the vehicle are analyzed. Then, a roll stability collaborative controller is constructed, which consists of a four-wheel differential sliding mode variable structure controller and an active suspension adaptive robust sliding mode controller. Finally, the control effects are verified by dynamics simulation and real vehicle test. The results show that the proposed collaborative control method can effectively control the vehicle roll and yaw motion, and improve the spatial stability of the vehicle. The research has potential theoretical and engineering value for improving the active safety of in-wheel motors drive electric vehicles on potholed roads.

{"title":"Roll stability control of in-wheel motors drive electric vehicle on potholed roads","authors":"Jiantao Wang , Xiaolong Zhang , Yawei Dong , Shuaishuai Liu , Lipeng Zhang","doi":"10.1016/j.conengprac.2025.106247","DOIUrl":"10.1016/j.conengprac.2025.106247","url":null,"abstract":"<div><div>The dynamics performance of in-wheel motors drive electric vehicles can be greatly improved by adjusting the torque and speed of the in-wheel motors, but the increased unsprung mass will bring greater dynamic load impacts on the body when the vehicle runs on potholed roads, which may make the vehicle roll when turning. To improve the roll stability, a collaborative control based on four-wheel differential drive and suspensions active adjustment is proposed. At first, a vehicle-road coupled dynamics model on a potholed road is developed. Next, the spatial stability evolution mechanism of the vehicle and the coupling effects of four-wheel differential drive and active suspensions control on the vehicle are analyzed. Then, a roll stability collaborative controller is constructed, which consists of a four-wheel differential sliding mode variable structure controller and an active suspension adaptive robust sliding mode controller. Finally, the control effects are verified by dynamics simulation and real vehicle test. The results show that the proposed collaborative control method can effectively control the vehicle roll and yaw motion, and improve the spatial stability of the vehicle. The research has potential theoretical and engineering value for improving the active safety of in-wheel motors drive electric vehicles on potholed roads.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"157 ","pages":"Article 106247"},"PeriodicalIF":5.4,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Anti-wheelie systems for high-performance motorcycles: A Nonlinear Model Predictive Control approach

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-20 DOI: 10.1016/j.conengprac.2024.106224

Luca Caiaffa , Fabio Maran , Matteo Furlan , Stivi Peron , Alessandro Beghi , Mattia Bruschetta

The global proliferation of Powered Two-Wheel (PTWs) underscores the need for increasingly effective active safety systems in motorcycles. Among others, the Anti-wheelie (AW) system is one of the most peculiar and safety-critical, aiming at limiting front wheel lift, preventing from possible vehicle instability, loss of control, and, in general, increased accident risk for motorcyclists. In this paper, an AW system based on an always-active, closed-loop control action that relies on a refined vehicle dynamics model is proposed. A Nonlinear Model Predictive Control strategy is leveraged to track an optimal pitch angle, ensuring maximum acceleration while maintaining safe interaction with the rider by constraining the reduction in applied torque. The control system is implemented on Raspberry Pi hardware, coupled to the vehicle’s Electronic Control Unit (ECU). Preliminary tuning was conducted in a high-fidelity co-simulation environment, and experimental tests were conducted with a sport-commercial vehicle showing satisfactory control performance even in extreme maneuvers. The effectiveness of the control action is further validated through suspension travel measurements and feedback from professional test drivers.

{"title":"Anti-wheelie systems for high-performance motorcycles: A Nonlinear Model Predictive Control approach","authors":"Luca Caiaffa , Fabio Maran , Matteo Furlan , Stivi Peron , Alessandro Beghi , Mattia Bruschetta","doi":"10.1016/j.conengprac.2024.106224","DOIUrl":"10.1016/j.conengprac.2024.106224","url":null,"abstract":"<div><div>The global proliferation of Powered Two-Wheel (PTWs) underscores the need for increasingly effective active safety systems in motorcycles. Among others, the Anti-wheelie (AW) system is one of the most peculiar and safety-critical, aiming at limiting front wheel lift, preventing from possible vehicle instability, loss of control, and, in general, increased accident risk for motorcyclists. In this paper, an AW system based on an always-active, closed-loop control action that relies on a refined vehicle dynamics model is proposed. A Nonlinear Model Predictive Control strategy is leveraged to track an optimal pitch angle, ensuring maximum acceleration while maintaining safe interaction with the rider by constraining the reduction in applied torque. The control system is implemented on Raspberry Pi hardware, coupled to the vehicle’s Electronic Control Unit (ECU). Preliminary tuning was conducted in a high-fidelity co-simulation environment, and experimental tests were conducted with a sport-commercial vehicle showing satisfactory control performance even in extreme maneuvers. The effectiveness of the control action is further validated through suspension travel measurements and feedback from professional test drivers.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"157 ","pages":"Article 106224"},"PeriodicalIF":5.4,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Disturbance observer-based saturated optimal super-twisting integral sliding mode midcourse guidance against maneuvering targets

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-17 DOI: 10.1016/j.conengprac.2025.106242

Wenxue Chen, Jiawei Gao, Changsheng Gao

This work addresses the problem of calculating midcourse guidance command in ballistic missile defense techniques against a maneuvering target. An improved optimal sliding mode guidance scheme is proposed based on the optimal control and sliding mode control techniques, which consider zero-effort-miss (ZEM), energy consumption, input saturation, and autopilot lag dynamics. The guidance problem is formulated as a nonlinear, uncertain, weakly observable system and modified to describe the equivalent guidance model by introducing the virtual state variables. The proposed guidance scheme is only needed to design the lateral acceleration in the instantaneous rotation plane of LOS (IRPL) by offering the line-of-sight (LOS) rotation coordinate frame as the reference frame of the three-dimensional relative kinematic model. Besides, the minimization of a performance index is guaranteed by introducing the optimal control theory. This proposed guidance scheme incorporates a novel hybrid extended state observer (NHESO) to estimate the system’s unmeasured states and disturbances in an integrated manner. Afterward, an integral sliding mode guidance algorithm is elucidated to resist interferences by introducing the integral sliding mode control theory. Also, the super-twisting algorithm is presented as the reaching law to avoid the chattering problem. Finally, the superior performance of the designed midcourse guidance scheme is validated in contrast to existing guidance laws, particularly energy consumption and robustness.

{"title":"Disturbance observer-based saturated optimal super-twisting integral sliding mode midcourse guidance against maneuvering targets","authors":"Wenxue Chen, Jiawei Gao, Changsheng Gao","doi":"10.1016/j.conengprac.2025.106242","DOIUrl":"10.1016/j.conengprac.2025.106242","url":null,"abstract":"<div><div>This work addresses the problem of calculating midcourse guidance command in ballistic missile defense techniques against a maneuvering target. An improved optimal sliding mode guidance scheme is proposed based on the optimal control and sliding mode control techniques, which consider zero-effort-miss (ZEM), energy consumption, input saturation, and autopilot lag dynamics. The guidance problem is formulated as a nonlinear, uncertain, weakly observable system and modified to describe the equivalent guidance model by introducing the virtual state variables. The proposed guidance scheme is only needed to design the lateral acceleration in the instantaneous rotation plane of LOS (IRPL) by offering the line-of-sight (LOS) rotation coordinate frame as the reference frame of the three-dimensional relative kinematic model. Besides, the minimization of a performance index is guaranteed by introducing the optimal control theory. This proposed guidance scheme incorporates a novel hybrid extended state observer (NHESO) to estimate the system’s unmeasured states and disturbances in an integrated manner. Afterward, an integral sliding mode guidance algorithm is elucidated to resist interferences by introducing the integral sliding mode control theory. Also, the super-twisting algorithm is presented as the reaching law to avoid the chattering problem. Finally, the superior performance of the designed midcourse guidance scheme is validated in contrast to existing guidance laws, particularly energy consumption and robustness.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"157 ","pages":"Article 106242"},"PeriodicalIF":5.4,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Composite speed control based on an improved gain-adaptive super-twisting sliding mode observer for a permanent magnet synchronous motor

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-16 DOI: 10.1016/j.conengprac.2025.106241

Zichen Guo , Junlin Li , Minxiu Yan , Gaoyuan Wang

To solve the problem that the speed control system of a surface-mounted permanent magnet synchronous motor is prone to external disturbances and time variations in motor parameters, a non-singular fast terminal sliding mode (NSFTSM) composite control method based on a gain-adaptive super-twisting sliding mode lumped disturbance observer (GA-STLD-SMO) is proposed. First, a mathematical model of PMSM with disturbance is established. Second, the traditional current loop PI control is replaced by proportional integral-Quasi-proportional resonance (PI-QPR) control, so that the current control has better precision. The speed loop controller is designed as a non-singular fast terminal sliding mode controller (NSFTSMC) to avoid singularity and jitter phenomena. Moreover, a sliding mode observer of rotational inertia (SMOORI) is designed based on the perturbations observed by the GA-STLD-SMO. The observed disturbance and moment of inertia are compensated into the speed controller. The stability and convergence of the system in finite time are proven by Lyapunov’s second method, and the performance of the proposed controller is tested and simulated. The final experimental results indicate that in the step response, the control method proposed in this paper is 8.9% smaller in overshooting, 85.8% faster in regulation time, and 20.8% smaller in steady-state error than the control method with the worst control effect among the comparative methods; meanwhile, in the anti-disturbance experiments, the control method in this paper is the smallest in the disturbed bias, and has a superior robustness.

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引用次数: 0

Expensive deviation-correction drilling trajectory planning: A constrained multi-objective Bayesian optimization with feasibility-oriented bi-objective acquisition function

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-01-15 DOI: 10.1016/j.conengprac.2025.106240

Jiafeng Xu, Xin Chen, Yang Zhou, Menglin Zhang, Weihua Cao, Min Wu

While conducting large-depth vertical drilling, correcting well trajectory deviations is a critical and challenging task. Designing a feasible deviation-correction trajectory becomes an expensive constrained multi-objective optimization problem due to the need for refined modeling of large-depth wellbore stability analysis. There is a pressing need for advanced drilling trajectory planning methods designed to handle robust constraints and to consider refined geological formation modeling, as current surrogate model-assisted optimization algorithms lack efficiency and balance among feasibility, convergence, and diversity. A Gaussian process-assisted Bayesian Multi-Objective Evolutionary Algorithm (MOEA) based on the reference point-based Non-dominated Sorting Genetic Algorithm (NSGA-III) is developed to manage the expensive wellbore stability objective. While surrogate models can effectively mitigate the computational expense, they may not adequately satisfy the stringent trajectory planning constraints. To enhance the constraint handling ability, an intricately devised infill criterion, Feasibility-oriented Bi-objective Acquisition Function (FBAF), tends to select promising feasible solutions to infill into the next generation. The deviation-correction trajectory planning simulation experiment was carried out under limited evaluations with real vertical well data. The results of empirical attainment function analysis demonstrate that the proposed FB-NSGA-III reduces the number of evaluations and exhibits superior performance compared to 11 other traditional surrogate-assisted MOEAs, particularly in terms of feasibility. FB-NSGA-III successfully prevents the back-hook by avoiding constraint violations and maintaining curvature within the specified safety and directional drilling tool build-up range.

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