相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。
Article
Thermodynamics
Sree Harsha Rayasam et al.
Summary: This paper develops a simple physics-based model for accurate modeling and control of the gas exchange process in a modern turbocharged spark-ignited engine. The model is applicable for control algorithm development and considers the impacts of modulation to various actuators. The accuracy of the model is validated through two validation strategies, and a coordinated controller is found to be ideal for tackling the control problem at hand.
INTERNATIONAL JOURNAL OF ENGINE RESEARCH
(2023)
Article
Automation & Control Systems
Alex Thivierge et al.
Summary: Mineral processing plants have a reputation for low energy efficiency. Economic model predictive control (EMPC) could potentially reduce their environmental footprint by considering energy costs, but its benefits are yet to be quantified. This study compared the response of an EMPC system to ore feed disturbances with basic and advanced regulatory control systems, using profits and specific energy as metrics. The results showed that the advanced regulatory control system generated more revenue and had lower energy consumption than the basic system, and EMPC could trade revenue for lower energy consumption with a hybrid criterion.
JOURNAL OF PROCESS CONTROL
(2023)
Article
Chemistry, Multidisciplinary
Simegnsh Bekele Dekebo et al.
Summary: A moving window decision-making algorithm is proposed for optimizing the cleaning schedule of a heat exchanger network system subject to fouling in a refinery crude preheat train. Compared to the conventional multi-period optimal control problem method, our algorithm shows excellent computational time performance while still finding a compatible optimal solution. Determining the optimal moving window size for the given time horizon is crucial for the optimization performance in our algorithm.
APPLIED SCIENCES-BASEL
(2023)
Article
Automation & Control Systems
Lianghao Ji et al.
Summary: This paper proposes a novel adaptive dynamic programming (ADP) method to solve the optimal consensus problem for a class of discrete-time multi-agent systems with completely unknown dynamics. A multi-step-based policy gradient ADP (MS-PGADP) algorithm is introduced, which is more efficient due to its faster reward propagation. A new Q-function is defined to estimate the performance of actions. The proof of optimality and stability of the error system are provided through the Lyapunov stability theorem and functional analysis.
IET CONTROL THEORY AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Zihan Zhang et al.
Summary: This paper proposes a coordinated optimization model between hydrothermal generator maintenance scheduling and long-term unit commitment, considering the network security constraints and coupling characteristics between cascade hydro plants. An improved two-stage heuristic algorithm based on the objective scaling ensemble approach is proposed to accelerate the solution of this complex problem. Simulation results show that the proposed algorithm can speed up the process of finding a near-optimal solution for large-scale systems, and the proposed model can plan out feasible and coordinated maintenance scheduling and long-term unit commitment scheme simultaneously.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Automation & Control Systems
Hang Yi et al.
Summary: This paper proposes a convenient and robust tuning rule for uncertainty and disturbance estimator (UDE)-based control in practical industrial stable processes. The Smith predictor is introduced to anticipate delay-free output, enabling signal synchronizations and restoring stability and performance. A second-order filter is employed in UDE to balance disturbance rejection and noise attenuation. A intuitive tuning rule with prescribed robustness is formulated based on exhaustive evaluations for robustness against model distortion. The promising prospect of UDE-based control in practical application is illustrated through representative simulations and a water level control experiment.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Energy & Fuels
Handan Akulker et al.
Summary: This study proposes a novel mixed-integer nonlinear programming (MINLP) model to compare the effects of carbon emission taxing and cap and trade system on the optimal equipment selection and scheduling of multi-energy microgrids. The results show that carbon dioxide price is a crucial parameter for equipment selection and must be taken into account in the design phase.
Article
Automation & Control Systems
Michele Schiavo et al.
Summary: This paper presents the first experimental results of using an event-based PID regulator for closed-loop control of general anesthesia. The control system uses the bispectral index scale as feedback and regulates the coadministration of propofol and remifentanil. The experiments were conducted on fourteen patients, representing routine clinical practice. The results show that the event-based control system performs consistently with care standards, providing a noise-free infusion profile that mimics anesthesiologists' behavior and reduces control effort on infusion pumps. This proposed solution represents a significant step toward the acceptance and diffusion of closed-loop control systems in routine clinical practice.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Energy & Fuels
Zheng Liang et al.
Summary: Organic Rankine cycle (ORC) is a promising technology for converting low-grade energy into electricity. Conventional ORCs often operate with a single heat source, which can reduce efficiency. This study proposes a superstructure-based method for ORC design that synthesizes heat exchanger network for hybrid heat sources and optimizes the ORC and heat sources' parameters. Results show that implementing hybrid heat sources improves the system performance.
Article
Automation & Control Systems
Zhonghao Xie et al.
Summary: This paper proposes a robust method for PLS based on the idea of least trimmed squares (LTS), which effectively deals with high-dimensional regressors. By formulating the LTS problem as a concave maximization problem, the complexity of solving LTS is simplified. The results from simulation and real data sets demonstrate the effectiveness and robustness of the proposed approach.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Guoxing Wen et al.
Summary: This article proposes a fuzzy logic system (FLS)-based adaptive optimized backstepping control using reinforcement learning (RL) strategy for a class of nonlinear strict feedback systems with unmeasured states. The proposed method constructs an observer-critic-actor architecture based on FLS approximations in each backstepping step to optimize the virtual and actual controls. The observer estimates the unmeasurable states while the critic and actor evaluate control performance and perform control behavior, respectively. The optimized control method avoids the requirement of design constants and simplifies the RL algorithm, making it more easily applicable and widely extendable.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Zhuo-Yun Nie et al.
Summary: This study demonstrates the integration of the Ziegler-Nichols tuning method into the framework of active disturbance rejection, leading to a unified tuning approach applicable to a wide range of industrial processes. This new method allows practitioners to understand and validate the tuning process using their own language of bandwidth and phase characteristics, with extensive simulation results provided to illustrate its effectiveness.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Xiangxiang Meng et al.
Summary: This paper proposes an optimized control strategy for the quadruple-tank liquid level system (QTLLS) based on actual production requirements. The strategy combines the Hamiltonian system model and disturbance observer, achieving good dynamic response and steady-state performance. Simulation and experimental results confirm its superiority over PID control and SMC.
JOURNAL OF PROCESS CONTROL
(2022)
Article
Automation & Control Systems
Xiangxiang Meng et al.
Summary: This paper proposes a novel input/output feedback linearization control method using a nonlinear disturbance observer (NDOB) for a quadruple-tank liquid level (QTLL) system. By establishing the mathematical model and designing a controller, and applying a disturbance observer for compensation control, better control performance than traditional methods is achieved.
Article
Engineering, Mechanical
Alejandro Pinon et al.
Summary: This paper presents a case study of a MIMO adaptive predictive controller (MIMO-APC) based on an ARX model. The controller has been successfully used in various industrial applications and aims to bridge the gap between the theory of predictive adaptive control and its practical implementation in the industry. Validation with simulated processes demonstrates significant performance improvements compared to previously published MIMO control strategies.
Article
Computer Science, Interdisciplinary Applications
Michele Schiavo et al.
Summary: This study aims to design a PID-based control system for regulating the depth of hypnosis in total intravenous anesthesia and takes into account the clinical practice. The experimental results demonstrate that the control system can achieve adequate anesthesia without manual intervention from the anesthesiologist.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Computer Science, Interdisciplinary Applications
Oguzhan Dogru et al.
Summary: PID controllers are widely used in industrial processes, but their parameter tuning is challenging. This study proposes an efficient method that formulates the PID tuning problem as a reinforcement learning task with constraints. It achieves satisfactory training performance on a model and then fine-tunes on the real process, minimizing training time and wear.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Automation & Control Systems
Nathan P. Lawrence et al.
Summary: Deep reinforcement learning is an optimization-driven framework for controlling dynamical systems. Implementing deep RL algorithms on real physical systems presents challenges such as interplay between software and hardware, experiment design and sample efficiency, training subject to input constraints, and interpretability of the algorithm and control law. Using a PID controller as the trainable RL policy offers simplicity and a well-understood form.
CONTROL ENGINEERING PRACTICE
(2022)
Article
Thermodynamics
Yao Shi et al.
Summary: This article proposes a dual-mode fast dynamic matrix control (FDMC) algorithm based on singular value decomposition (SVD) and dynamic matrix control (DMC) to address the issue of long computation time in model predictive control (MPC) for organic Rankine cycle (ORC) systems. The simulations demonstrate the effectiveness and rapidity of the proposed algorithm in ensuring tracking performance while improving calculation speed.
Review
Multidisciplinary Sciences
Stephen Bassi Joseph et al.
Summary: This paper provides a comprehensive review of modern and classical strategies for tuning PID controller parameters using metaheuristic algorithms. It also presents some open problems for future research.
Article
Engineering, Chemical
Tsai-Wei Wu et al.
Summary: A novel control strategy is developed in this work for an intensified hybrid reactive-extractive distillation system using only temperature measurements, addressing the challenging issues in the design configuration. By using temperature and temperature-difference control loops as surrogates for quality control loops, the best control structures are demonstrated to be resilient to measurable throughput disturbances and adaptable to different system characteristics.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Yongming Li et al.
Summary: This article presents an adaptive neural network output feedback optimized control design for strict-feedback nonlinear systems with unknown internal dynamics. By constructing optimal cost functions for subsystems and using the actor-critic architecture, virtual and actual optimal controllers are developed to ensure the boundedness of all closed-loop signals. The proposed strategy also guarantees that system states are always confined within some preselected compact sets.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Automation & Control Systems
Yongming Li et al.
Summary: This article studies the adaptive optimized formation control problem for second-order stochastic multiagent systems with unknown nonlinear dynamics. Fuzzy logic systems are used to approximate the nonlinear functions in the control design. By employing the actor-critic architecture and Lyapunov stability theory, the proposed optimal formation control strategy ensures that all the error signals are bounded in probability. Simulation examples verify the effectiveness of the proposed formation control approach.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
Yinping Che et al.
Summary: This paper proposes a LV-NILMPC method based on the DFPLS model for trajectory tracking and process disturbance suppression in nonlinear batch processes. By integrating the T-S fuzzy model into the dynamic PLS inner model, the dynamic and nonlinear characteristics of the physical system are constructed. The method has a faster convergence rate and smaller tracking error compared to previous methods, and it is suitable for nonlinear, multivariable, and strong coupling batch processes.
JOURNAL OF PROCESS CONTROL
(2022)
Article
Engineering, Chemical
Vasileios Mappas et al.
Summary: This study proposes a novel approach based on the Multistage Integer Nonlinear Optimal Control Problem (MSINOCP) formulation to solve the Reverse Osmosis (RO) cleaning scheduling problem. The approach provides an automated solution for membrane cleaning scheduling without the need for combinatorial optimization. Simulation results demonstrate that this approach can successfully solve problems with large-scale configurations, long time horizons, and complex dynamic models of the RO process.
Article
Computer Science, Artificial Intelligence
Jie Ding et al.
Summary: This research proposes a fractional order PIDNN controller based on the beetle swarm optimization algorithm for multi-input multi-output systems with strong coupling. The controller introduces the fractional order PID operator to the hidden layer neurons, which improves control accuracy and convergence speed due to the long memory characteristics of fractional order neurons. Additionally, a stability condition for the learning rate is established using the Lyapunov theory, and the BSO algorithm is used to initialize the controller in order to prevent weights from falling into local optima.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Review
Engineering, Chemical
Changsoo Kim et al.
Summary: This paper reviews various mathematical tools for designing control structures in distillation columns, including traditional methods such as SVD and RGA, as well as newer inferential control techniques like PCR and PLSR that rely on statistical methods and machine learning techniques. The discussions also cover complex distillation technologies such as dividing-wall columns, as well as the use of process simulators in aiding control structure design.
CHEMICAL PRODUCT AND PROCESS MODELING
(2022)
Article
Automation & Control Systems
Sreya Ghosh et al.
Summary: A simple frequency domain method is proposed for the design of controllers for multi-input multi-output (MIMO) processes. By evaluating the process transfer function matrix at a low frequency point, the calculation for inverse of the matrix is simplified. Centralized PI controllers are designed using a model matching technique and provide acceptable performances for different types of processes, including high-dimensional processes.
Article
Automation & Control Systems
Nicolo Robuschi et al.
Summary: This study introduces an efficient model for computing a non-causal minimum-fuel energy management strategy for a hybrid electric vehicle on a given driving cycle. The proposed tailored algorithm breaks down the problem into a sequence of nonlinear programs and mixed integer linear programs, demonstrating both solution quality and run time through numerical results.
Article
Computer Science, Interdisciplinary Applications
Eduardo Nolasco et al.
Summary: Roger W.H. Sargent was an unprecedented pioneer in the field of chemical engineering, creating the multidisciplinary field of Process Systems Engineering(PSE) and making significant contributions to optimal control theory. He developed numerical techniques to solve large-scale optimal control problems and his work continues to influence the field today.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Chemistry, Analytical
Mikulas Huba et al.
Summary: This paper discusses the design of a DC motor speed control using an embedded controller, introducing a novel approach with anti-windup implementation and noise-reduction filter design. The proposed tuning method takes into account important aspects such as signal preprocessing, filtering, time delays, modeling, and control signal constraints. The study shows that a well-designed embedded controller can achieve excellent closed-loop performance in noisy process environments with limited control signals.
Review
Automation & Control Systems
Daniel Ioan et al.
Summary: This paper reviews the past and current results and approaches in motion planning using Mixed-integer Programming (MIP). It highlights the efficiency of MIP in selecting from a limited number of alternatives or solving optimization problems over non-convex domains, as well as the importance of various experimental validations in the literature.
ANNUAL REVIEWS IN CONTROL
(2021)
Review
Automation & Control Systems
Rakesh P. Borase et al.
Summary: This article provides a study of modern and classical approaches used for PID tuning and its applications in various domains. It reviews the techniques from classical to modern optimization rules used for PID tuning, aiming to offer a detailed understanding of PID command in different application areas.
INTERNATIONAL JOURNAL OF DYNAMICS AND CONTROL
(2021)
Article
Automation & Control Systems
Elham Mehri et al.
Summary: An adaptive fractional-order sliding mode controller is constructed for a quadruple tank process, considering pump voltages as inputs and water levels as outputs. A non-integer sliding surface and an adaptive mechanism based on Lyapunov are designed to enhance robustness to pump coefficients, ensuring water levels converge to desired values. Simulation results demonstrate the robust performance of the proposed controller.
JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Paul Bendevis et al.
COMPUTERS & CHEMICAL ENGINEERING
(2020)
Article
Computer Science, Interdisciplinary Applications
S. D. Adloor et al.
COMPUTERS & CHEMICAL ENGINEERING
(2020)
Article
Automation & Control Systems
Qingchao Jiang et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2020)
Article
Computer Science, Artificial Intelligence
Alejandro Rodriguez-Molina et al.
APPLIED SOFT COMPUTING
(2020)
Article
Engineering, Chemical
Jefferson Revelo et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2020)
Article
Computer Science, Interdisciplinary Applications
Yingjie Ma et al.
COMPUTERS & CHEMICAL ENGINEERING
(2020)
Article
Automation & Control Systems
Shubham Khandelwal et al.
JOURNAL OF PROCESS CONTROL
(2020)
Article
Automation & Control Systems
David Fernando Novella-Rodriguez et al.
INTERNATIONAL JOURNAL OF CONTROL
(2019)
Article
Automation & Control Systems
Imen Saidi et al.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2019)
Review
Engineering, Multidisciplinary
Anca Maxim et al.
Article
Automation & Control Systems
Alexandro Garro Brito
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2019)
Article
Computer Science, Information Systems
Baran Hekimoglu
Article
Computer Science, Information Systems
Sang-Wha Seo et al.
Article
Computer Science, Information Systems
Sina Razvarz et al.
Article
Computer Science, Interdisciplinary Applications
Marija Stojkovic et al.
COMPUTERS & CHEMICAL ENGINEERING
(2018)
Article
Computer Science, Interdisciplinary Applications
Riham Al Ismaili et al.
COMPUTERS & CHEMICAL ENGINEERING
(2018)
Article
Computer Science, Artificial Intelligence
Shaocheng Tong et al.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2018)
Article
Computer Science, Information Systems
Mohammad Eslami et al.
Article
Thermodynamics
Danijel Jolevski et al.
Article
Engineering, Chemical
Matias Hultgren et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2017)
Article
Engineering, Chemical
Qibing Jin et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2017)
Article
Automation & Control Systems
Pedro Mercader et al.
Article
Automation & Control Systems
Ali M. H. Kadhim et al.
MODELING IDENTIFICATION AND CONTROL
(2016)
Review
Multidisciplinary Sciences
Ian T. Jolliffe et al.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2016)
Article
Computer Science, Artificial Intelligence
Haitao Xing et al.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2016)
Article
Computer Science, Interdisciplinary Applications
Yunfei Chu et al.
COMPUTERS & CHEMICAL ENGINEERING
(2012)
Article
Automation & Control Systems
Christian Kirches et al.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2010)
Article
Statistics & Probability
Herve Abdi
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS
(2010)
Article
Automation & Control Systems
Sebastian Sager
JOURNAL OF PROCESS CONTROL
(2009)
Article
Automation & Control Systems
Mao-Jun He et al.
JOURNAL OF PROCESS CONTROL
(2009)
Article
Computer Science, Software Engineering
Sebastian Sager et al.
MATHEMATICAL PROGRAMMING
(2009)
Article
Automation & Control Systems
Q Xiong et al.
JOURNAL OF PROCESS CONTROL
(2005)
Article
Operations Research & Management Science
U Ledzewicz et al.
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
(2002)
Article
Computer Science, Software Engineering
RH Byrd et al.
MATHEMATICAL PROGRAMMING
(2000)
