Article
Automation & Control Systems
Florentina Nicolau, Witold Respondek, Shunjie LI
Summary: This paper studies feedback linearization of multi-input control-affine systems using a particular class of nonregular feedback transformations, and provides geometric necessary and sufficient conditions to describe these systems.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2022)
Article
Automation & Control Systems
Yahao Chen
Summary: The article investigates feedback linearization problems for nonlinear differential-algebraic control systems (DACS), considering external and internal feedback equivalences, as well as a concept of explicitation with driving variables. Necessary and sufficient conditions for feedback linearization of DACS are provided, showing a close relationship between feedback linearizability and the involutivity of explicitation systems. The results are illustrated with an academic example and a constrained mechanical system.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Computer Science, Information Systems
Na Lin, Ronghu Chi, Biao Huang
Summary: This work proposes a data-driven optimal set-point control (DDOSC) scheme for nonlinear non-affine systems, which bypasses the challenges of modeling complex processes. The proposed method adopts an ideal nonlinear set-point control function in the outer loop, which is transformed into a linear parametric control law using dynamic linearization (DL), and then updated through a parameter updating law. Simulation results demonstrate the effectiveness of the proposed method in improving the performance of the local feedback controller.
INFORMATION SCIENCES
(2023)
Article
Chemistry, Multidisciplinary
Yong-Lin Kuo, Peeraya Pongpanyaporn
Summary: This paper presents a tracking control scheme for nonlinear systems with input constraints by combining continuous-time model predictive control and feedback linearization. The Laguerre functions are used to approximate the control signals, simplifying the formulations and reducing the computational loads. The study also summarizes common linearization schemes and applies the proposed approach to two illustrative examples for performance comparison.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Weiyu Wang, Xin Yin, Lin Jiang, Yijia Cao, Yong Li
Summary: The VSC-MTDC system with offshore wind farms faces uncertainties and nonlinearities that could impact its performance and stability. This paper proposes a PONC approach to improve the robustness of the system by estimating perturbations and designing controllers to compensate for them, achieving robust tracking performance without requiring an accurate system model. The effectiveness of PONC is demonstrated through a 5-terminal VSC-MTDC system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Automation & Control Systems
Weijiang Zheng, Bing Zhu
Summary: This paper presents a stochastic model predictive control (MPC) framework for nonlinear affine systems with stability and feasibility guarantee. The concept of stochastic control Lyapunov-Barrier function (CLBF) is introduced, and a method to construct CLBF is provided by combining an unconstrained control Lyapunov function (CLF) and control barrier functions. The proposed CLBF based stochastic MPC utilizes sampled-data MPC framework to handle states and inputs constraints and to analyze stability of closed-loop systems. Event-triggering mechanisms are also integrated into the MPC framework to improve performance during sampling intervals.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Information Systems
Manal S. Esmail, Mohamed H. Merzban, Ashraf A. M. Khalaf, Hesham F. A. Hamed, Aziza I. Hussein
Summary: This paper proposes a quaternion-based nonlinear feedback controller for attitude and altitude regulation of a quadcopter. The effectiveness and efficiency of the proposed controller are demonstrated through comparison with state-of-the-art quadcopter controllers.
Article
Automation & Control Systems
Mario Baggetta, Giovanni Berselli, Gianluca Palli, Claudio Melchiorri
Summary: Recent technological advances have brought changes to the design of robotics, allowing for safe and dependable physical human-robot interaction and human-like prosthesis. This study presents a new design for an anthropomorphic elbow variable stiffness actuator (VSA) and proposes a dynamic feedback linearization algorithm that takes into account the viscoelasticity of transmission elements. Experimental studies and simulations demonstrate improved trajectory tracking compared to static feedback control algorithms.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Automation & Control Systems
Chung-Cheng Chen, Yen-Ting Chen
Summary: This article presents a new method to achieve multiple performance of highly nonlinear multi-input multi-output full-car uncertain system through optimized control and reduce the amplitudes of system control inputs. By using PSO optimization algorithm to replace the traditional trial-and-error method and locally Jacobian linearized approach, the study aims to achieve optimal control matrices of LQR method.
IET CONTROL THEORY AND APPLICATIONS
(2021)
Article
Automation & Control Systems
Rollen S. D'Souza, Christopher Nielsen
Summary: This paper characterizes the necessary and sufficient conditions for a single-input system to be locally transversally feedback linearizable to a specific submanifold using exterior differential systems.
Article
Automation & Control Systems
Johannes Diwold, Bernd Kolar, Markus Schoeberl
Summary: This article discusses the design of a discrete-time flatness-based tracking control for a gantry crane and demonstrates its practical applicability through measurement results. The approach involves deriving a sampled-data model via Euler-discretization while preserving the flatness of the continuous-time system, and designing the controller in two steps for linearization and stable tracking error dynamics enforcement. The comparison with classical continuous-time approaches shows the discrete-time controller's significant robustness with large sampling times, as well as its facilitation of optimal reference trajectory design and presentation of further measurement results.
CONTROL ENGINEERING PRACTICE
(2022)
Article
Engineering, Chemical
Qiang Zhang, Ping Liu, Yu Chen, Quan Deng, Angxin Tong
Summary: This paper addresses the trajectory tracking control problem for general nonlinear single-input single-output systems. By employing the input-output feedback linearization technique and designing a finite-time disturbance observer-based terminal sliding mode controller, the tracking performance and robustness are improved. The stability analysis is carried out using the Lyapunov method. A boundary layer method is adopted to trade-off between high-frequency control actions and bounded nonzero steady-state error. The proposed method is evaluated through comprehensive numerical simulations and compared to state-of-the-art methods, showing superior performance in terms of disturbance rejection, fast reaction, and small tracking error without high-frequency chattering.
Article
Chemistry, Multidisciplinary
Haibo Huo, Kui Xu, Lixiang Cui, Hao Zhang, Jingxiang Xu, Xinghong Kuang
Summary: This paper presents a control strategy based on input-output feedback linearization technology to control the temperature gradient in SOFC by adjusting the cathode input air flow. Simulation results demonstrate the accuracy of the proposed model in reflecting temperature dynamic characteristics and show that the proposed controller has better effectiveness and efficiency in the presence of external disturbances compared to a compound controller.
Article
Engineering, Mechanical
Luis Martins, Carlos Cardeira, Paulo Oliveira
Summary: This paper presents a novel control architecture for quadrotors using Feedback Linearization technique for tracking attitude and altitude dynamics, while stabilizing horizontal movement without linearization. Linear quadratic controllers with integral action ensure asymptotic tracking in the inner and outer loops, achieving input-to-state stable and exponentially stable tracking. Experimental tests validate the proposed modeling and control system solution.
NONLINEAR DYNAMICS
(2022)
Article
Automation & Control Systems
Marcos Gabriel Judewicz, Sergio Alejandro Gonzalez, Eugenio Martin Gelos, Jonatan Roberto Fischer, Daniel Oscar Carrica
Summary: Three-level boost dc-dc converters have advantages over conventional boost converters, but suffer from output capacitor voltage imbalance. In this paper, an exact feedback linearization control strategy is proposed and its performance is analyzed and simulated. Experimental results show that the proposed control strategy performs well in steady-state and under nonlinear loads.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Chemical
Bartolome Ortega-Delgado, Patricia Palenzuela, Javier Bonilla, Manuel Berenguel, Lidia Roca, Diego-Cesar Alarcon-Padilla
Summary: This work presents the dynamic modeling of a vertical multi-effect evaporator plant designed for a commercial concentrating solar power (CSP) plant and investigates its dynamic response to external disturbances. The results show that simultaneous adjustment of the motive steam and feedwater mass flow rates can maintain the concentrate salinity within safe limits.
Article
Thermodynamics
Patricia Palenzuela, Lidia Roca, Faisal Asfand, Kumar Patchigolla
Summary: The European Commission's new challenge is to limit water consumption in Concentrating Solar Power (CSP) plants, with hybrid cooling systems seen as a potential solution. Experimental evaluation of a hybrid cooling pilot plant showed significant water savings of up to 67% at high ambient temperatures and 80% thermal load. Optimal operating strategies achieving a tradeoff between low water and electricity consumption were identified, with parallel configuration being the most efficient in most cases.
Article
Green & Sustainable Science & Technology
Juan D. Gil, Lidia Roca, Guillermo Zaragoza, Manuel Perez, Manuel Berenguel
Summary: The treatment of high salinity feeds using solar membrane distillation processes is gaining popularity. Batch operation is the most suitable method, but the variability of salinity in the feed water affects the optimal operating conditions. To address this, this study proposes two real-time optimization control approaches, which can save energy and improve the system's daily operation.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Computer Science, Information Systems
M. Munoz, J. L. Guzman, J. A. Sanchez-Molina, F. Rodriguez, M. Torres, M. Berenguel
Summary: This article proposes a cloud solution for building an Internet of Things (IoT) platform in greenhouse crop production. It utilizes RESTful Web services to provide real-time and historical data access, as well as prediction models. The proposed platform also allows users to register new IoT devices and interact with the system through a web application.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Thermodynamics
Igor M. L. Pataro, Juan D. Gil, Jose L. Guzman, Manuel Berenguel, Joao M. Lemos
Summary: This work proposes a hierarchical framework for controlling a solar thermal facility to provide operating conditions for an absorption chiller machine. A case study of the CIESOL thermal plant is conducted with verified subsystems and valves in a simulation environment. Three different models are used for absorption chiller modeling, and a hybrid nonlinear predictive controller is formulated for hierarchical control. A lower layer with PI controllers is designed to handle valve nonlinear dynamics and disturbance rejection. Results show that the hierarchical structure extends the operating time of the solar-powered absorption chiller by approximately 115 minutes compared to conventional operation, with reduced fossil fuel usage.
Article
Engineering, Chemical
Patricia Palenzuela, Diego-Cesar Alarcon-Padilla, Bartolome Ortega-Delgado, Guillermo Zaragoza
Summary: Water scarcity is a pressing issue in many parts of the world, and desalination is seen as a potential solution. However, the high energy consumption of desalination processes, which are primarily powered by fossil fuels, is problematic. Integrating renewable energy sources, such as solar power, into desalination processes could be a promising way to reduce carbon emissions. This study assesses the efficiency and water production of two integrated solar power and desalination systems, using multi-effect distillation and reverse osmosis processes, in combination with a central receiver solar plant.
Article
Mathematics
Pablo Otalora, Jose Luis Guzman, Manuel Berenguel, Francisco Gabriel Acien
Summary: The industrial production of microalgae is a sustainable and interesting process, especially in terms of its applications in wastewater treatment. Neural network models have been developed to optimize the process and characterize the pH dynamics in different raceway reactors. These models are able to predict pH profiles using available measurable process data and demonstrate the potential of artificial neural networks in modeling continuous dynamic systems in the industry.
Article
Automation & Control Systems
Igor M. L. Pataro, Juan D. Gil, Jose L. Guzman, Manuel Berenguel, Joao M. Lemos
Summary: This article presents a study on the pH control of raceway photobioreactors (PBRs) using a learning-based model predictive control (LBMPC) approach. The LBMPC demonstrates satisfactory results and outperforms the conventional nominal MPC strategy, achieving up to four times superior performance in terms of the average error index. The results highlight the importance of employing robust adaptive control strategies for highly nonlinear and multi-disturbed systems like the variant biological-chemical microalgae process in PBRs.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Automation & Control Systems
Igor M. L. Pataro, Rita Cunha, Juan D. Gil, Jose L. Guzman, Manuel Berenguel, Joao M. Lemos
Summary: This study introduces an adaptive optimal model-free controller for solar collector fields (SCFs) that overcomes the challenges of using high-complex models. The proposed controller is based on the Reinforcement Q-Learning algorithm and achieves optimal performance using only plant measurements. It outperforms model-based controllers by handling nonlinearities, time-varying model parameters, and computational costs associated with nonlinear models. Simulations using actual data from a thermal plant demonstrate the effectiveness of the model-free controller, as the Q-Learning algorithm converges to the optimal gains of the Linear Quadratic Tracking (LQT) controller.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Igor M. L. Pataro, Juan D. Gil, Marcus V. Americano da Costa, Lidia Roca, Jose L. Guzman, Manuel Berenguel
Summary: Improving temperature reference tracking is crucial for enhancing the performance of solar thermal plants. This study proposes two control strategies, lead-lag and nonlinear reference feedforwards, to achieve low rise time and no overshoot in temperature reference tracking. Simulation experiments and real-world testing in a solar plant validate the effectiveness of these strategies under different operating conditions.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Automation & Control Systems
Igor M. L. Pataro, Juan D. Gil, Marcus V. Americano da Costa, Lidia Roca, Jose L. Guzman, Manuel Berenguel
Summary: This study proposes a stochastic model predictive control (MPC) based on a chance-constraint formulation for controlling a real solar thermal plant. The controller, named CC practical nonlinear MPC (CC-PNMPC), is implemented in the AQUASOL-II facility to validate and demonstrate the advantages of the proposed control approach. The results show that the stochastic strategy can account for disturbance uncertainties and improve the control system's performance.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Automation & Control Systems
Francisco Garcia-Manas, Francisco Rodriguez, Manuel Berenguel, Jose Maria Maestre
Summary: This paper presents a stochastic model predictive control (SMPC) strategy to maximize the economic profit of a greenhouse crop production. The SMPC strategy considers the uncertainty of market price by using its historical evolution per year as multiple price scenarios in the cost function. The results show that MS-MPC can improve economic profits compared to the use of an average price scenario for the MPC calculations.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Energy & Fuels
Siddharth Sradhasagar, Omkar Subhasish Khuntia, Srikanta Biswal, Sougat Purohit, Amritendu Roy
Summary: In this study, machine learning models were developed to predict the bandgap and its character of double perovskite materials, with LGBMRegressor and XGBClassifier models identified as the best predictors. These models were further employed to predict the bandgap of novel bismuth-based transition metal oxide double perovskites, showing high accuracy, especially in the range of 1.2-1.8 eV.
Article
Energy & Fuels
Wei Shuai, Haoran Xu, Baoyang Luo, Yihui Huang, Dong Chen, Peiwang Zhu, Gang Xiao
Summary: In this study, a hybrid model based on numerical simulation and deep learning is proposed for the optimization and operation of solar receivers. By applying the model to different application scenarios and considering multiple performance objectives, small errors are achieved and optimal structure parameters and heliostat scales are identified. This approach is not only applicable to gas turbines but also heating systems.
Article
Energy & Fuels
Mubashar Ali, Zunaira Bibi, M. W. Younis, Muhammad Mubashir, Muqaddas Iqbal, Muhammad Usman Ali, Muhammad Asif Iqbal
Summary: This study investigates the structural, mechanical, and optoelectronic properties of the BaCuF3 fluoroperovskite using the first-principles modelling approach. The stability and characteristics of different cubic structures of BaCuF3 are evaluated, and the alpha-BaCuF3 and beta-BaCuF3 compounds are found to be mechanically stable with favorable optical properties for solar cells and high-frequency UV applications.
Article
Energy & Fuels
Dong Le Khac, Shahariar Chowdhury, Asmaa Soheil Najm, Montri Luengchavanon, Araa mebdir Holi, Mohammad Shah Jamal, Chin Hua Chia, Kuaanan Techato, Vidhya Selvanathan
Summary: A novel recycling system is proposed in this study to decompose and reclaim the constituent materials of organic-inorganic perovskite solar cells (PSCs). By utilizing a one-step solution process extraction approach, the chemical composition of each layer is successfully preserved, enabling their potential reuse. The proposed recycling technique helps mitigate pollution risks, minimize waste generation, and reduce recycling costs.
Article
Energy & Fuels
Peijie Lin, Feng Guo, Xiaoyang Lu, Qianying Zheng, Shuying Cheng, Yaohai Lin, Zhicong Chen, Lijun Wu, Zhuang Qian
Summary: This paper proposes an open-set fault diagnosis model for PV arrays based on 1D VoVNet-SVDD. The model accurately diagnoses various types of faults and is capable of identifying unknown fault types.
