Article
Engineering, Mechanical
Jianfeng Wang, Yan Wang, Zhicheng Ji
Summary: This paper investigates the problem of event-triggered optimal control for discrete-time nonlinear systems using the goal representation heuristic dynamic programming (GrHDP) approach without system dynamics description. A novel adaptive event-triggering condition is designed that utilizes the optimal value function and the internal reinforcement signal. The stability of the proposed event-triggered optimal control method is theoretically analyzed. The paper demonstrates that the real performance index is lower than a predefined upper bound. The impact of the triggering condition parameter is also studied, providing a trade-off between performance and resource usage. Three neural networks are employed to implement the GrHDP approach for obtaining the optimal value function and internal reinforcement signal. Two simulations are presented to illustrate the effectiveness of the proposed method.
NONLINEAR DYNAMICS
(2022)
Article
Business, Finance
Wenhao Tan, Yanping Wang, Xiuyuan Guo
Summary: This paper investigates the government intervention in firm operation in emerging markets, focusing on the employment strategy of Chinese listed firms. The study finds that under the constraints of official employment aim, enterprises tend to reduce educational requirements and increase the number of employees. The empirical findings reveal that frequent visits by Chinese officials can lead to an increase in employees, particularly those with lower educational levels, resulting in a decrease in average degree. This relation is stronger in provinces with higher employment aims and when the average academic degree is below a certain threshold.
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
(2022)
Article
Computer Science, Artificial Intelligence
Xueli Wang, Derui Ding, Xiaohua Ge, Qing-Long Han
Summary: This article focuses on the supplementary control of discrete-time nonlinear systems with multiple controllers using goal representation heuristic dynamic programming (GrHDP) and a logarithmic quantizer for network communication management. It introduces a neural network (NN)-based observer to estimate the system state in the presence of quantized influence, and develops a GrHDP algorithm with a reinforced term to implement the supplementary control task based on estimated states and ideal control inputs through a zero-sum game. Stability conditions for the estimated error dynamics of observer states and updated NNs' weights are derived using Lyapunov stability theory. The effectiveness of the proposed method is verified through experiments on a power system and numerically.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Robotics
Jinning Li, Chen Tang, Masayoshi Tomizuka, Wei Zhan
Summary: This study explores the application of offline reinforcement learning in temporally extended tasks. The authors propose a hierarchical planning framework, training a low-level goal-conditioned RL policy and a high-level goal planner. They improve the offline training process to handle out-of-distribution goals. Experimental results show that their method outperforms baselines and non-hierarchical planners in complex tasks.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Computer Science, Interdisciplinary Applications
Chen Zheng, Yushu An, Zhanxi Wang, Haoyu Wu, Xiansheng Qin, Benoit Eynard, Yicha Zhang
Summary: Offline programming is an intuitive and automatic programming generation technique that greatly reduces downtime and labor costs. Current methods, such as CAD-based and vision-based approaches, have limitations in supporting the automatic generation of welding programs for complex workpieces in industries like shipbuilding. A proposed hybrid offline programming method systematically combines CAD, vision, and interactive activities to improve the efficiency, accuracy, and flexibility of robotic welding systems.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Engineering, Multidisciplinary
Michal Rogalewicz, Agnieszka Kujawinska, Adrianna Feledziak
Summary: This paper presents a method for planning the range of quality control while ensuring its reliability and minimizing costs. The methodology was divided into four main stages: (1) selection of the measurement system and definition of the inspection scope and sample size, (2) process control, (3) redefining the scope of control and (4) verification of control cost and reliability after sample size change. The results show that the proposed method successfully reduced the costs of seat belt quality control while maintaining the credibility of the decision based on the assessment.
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
(2023)
Article
Engineering, Multidisciplinary
Jiahong Xu, Lijie Wang, Yang Liu, Hong Xue
Summary: This paper investigates the optimal attitude control problem for a quadrotor UAV with time-varying control effectiveness faults using adaptive dynamic programming. A novel nonlinear conversion function is introduced to achieve finite-time prescribed performance on tracking errors of three attitude angles. An improved value function with a discount factor is proposed to resist the time-varying control effectiveness faults. By integrating concurrent learning technique into adaptive dynamic programming algorithm, a valid approximate optimal control protocol is presented. The developed control scheme is validated through a simulation example. (c) 2023 Published by Elsevier Inc.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Automation & Control Systems
Yinhua Liu, Wenzheng Zhao, Hongpeng Liu, Yinan Wang, Xiaowei Yue
Summary: This study proposes a novel coverage path planning (CPP) method for free-form surface inspection in robotic quality inspection, taking into account the measurement uncertainty and using an optimal viewpoint sampling strategy to improve the scanning precision of key measurement points.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Automation & Control Systems
Yinhua Liu, Wenzheng Zhao, Hongpeng Liu, Yinan Wang, Xiaowei Yue
Summary: A novel CPP method incorporating the measurement uncertainty of key MPs into free-form surface inspection is proposed in this study. By calculating the feasible ranges of measurement uncertainty and using an enhanced rapidly exploring random tree algorithm for viewpoint sampling, the scanning precision of key MPs is significantly improved compared with the benchmark method.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Engineering, Biomedical
Robert M. Hinson, Joseph Berman, William Filer, Derek Kamper, Xiaogang Hu, He Huang
Summary: There has been a debate on the most appropriate way to evaluate EMG-based NMIs. This study found a moderate to strong relationship between offline performance and real-time task performance metrics, supporting the use of offline analyses for optimization of NMIs.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Automation & Control Systems
Guangyu Zhu, Xiaolu Li, Ranran Sun, Yiyuan Yang, Peng Zhang
Summary: In this paper, a new iterative adaptive dynamic programming algorithm called discrete-time time-varying policy iteration (DTTV) algorithm is developed for infinite horizon optimal control problems of discrete time-varying nonlinear systems. The algorithm updates the iterative value function to approximate the index function of optimal performance. The admissibility and convergence properties of the iterative control law are analyzed.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2023)
Article
Chemistry, Analytical
Thomas Idzik, Matthew Veres, Cole Tarry, Medhat Moussa
Summary: Manufacturing is an imperfect process that requires frequent checks and verifications. This work presents an approach to improve defect detection capabilities in an automotive gear facility by incorporating advanced inspection techniques.
Article
Automation & Control Systems
Junfei Qiao, Ruyue Yang, Ding Wang
Summary: This article presents an adaptive batch learning algorithm for optimal control of complex wastewater treatment processes. By learning and evaluating from offline data, the algorithm can improve and optimize control policies to achieve better control performance.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Robotics
Keisuke Okumura, Francois Bonnet, Yasumasa Tamura, Xavier Defago
Summary: This study explores a planning problem for multiple agents called Offline Time-Independent Multiagent Path Planning (OTIMAPP) where holding resources cannot be shared. The objective is to assign paths to each agent, allowing them to reach their destination without blocking other agents, regardless of timing uncertainties. Unlike traditional multirobot path planning, OTIMAPP solutions do not require synchronization between robot actions. The study establishes OTIMAPP theoretically and practically by formalizing the problem, providing solution conditions, analyzing computational complexities, proposing solution algorithms, presenting empirical results, and demonstrating robot executions.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
Article
Computer Science, Artificial Intelligence
Xingyu Wang, Xurong Chi, Yanzhi Song, Zhouwang Yang
Summary: This study proposes a practical active learning method that reduces labeling costs by adaptively allocating labeling resources. It achieves excellent results in benchmark datasets and industrial applications.
PEERJ COMPUTER SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Brojeswar Pal, Amit Sarkar, Biswajit Sarkar
Summary: This study investigates the production of eco-friendly and less harmful green innovative products under an uncertain environment. The results show that green innovation is effective in improving the players' profit margin, and the manufacturer must decide the extent of green innovation to optimize the profits. A dual-channel supply chain is found to be more efficient for green products.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Green & Sustainable Science & Technology
Shubham Kumar Singh, Anand Chauhan, Biswajit Sarkar
Summary: The need for sustainable energy generation has increased due to growing levels of emissions and energy demand. Biofuel, derived from biomass such as animal fat, waste cooking oil, and vegetable oil, is seen as a viable alternative to non-renewable energy sources. A mathematical optimization model is proposed to plan a sustainable supply chain for biodiesel made from waste animal fat. The model aims to minimize the cost, environmental impact, and maximize social impact. The transportation cost accounts for 51.34% of the total cost while the environmental impact of biodiesel production facilities accounts for 99.94% of the total environmental impact. The model can be valuable for policymakers and investors in the biodiesel industry.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Neha Saxena, Biswajit Sarkar, Hui-Ming Wee, Samuel Reong, S. R. Singh, Y. L. Hsiao
Summary: Due to rising consumer concern and corporate responsibility towards the environment, a closed-loop supply chain with a green design is becoming important. This article presents a sustainable supply chain model that incorporates reverse logistics operations for waste reduction. A suitable return policy is discussed for deteriorating items, incorporating an eco-design framework. To address carbon emissions, a penalty tax is introduced. The study compares three optimization techniques based on cooperative and non-cooperative associations.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Operations Research & Management Science
Najibeh Usefi, Mehdi Seifbarghy, Mitali Sarkar, Biswajit Sarkar
Summary: The occurrence of natural and artificial disasters requires precise planning and management in the relief supply chain. A key measure during a crisis is to assist the damaged points. Relief centers should be opened in appropriate locations to cover the needs of the damaged points in the shortest possible time due to limitations in the relief process.
RAIRO-OPERATIONS RESEARCH
(2023)
Article
Mathematics
Shubham Kumar Singh, Anand Chauhan, Biswajit Sarkar
Summary: Sustainable development and environmental pollution have led to the importance of reverse logistics in the resource recovery of end-of-life electronic products. The paper presents a mathematical model for managing the collection, sorting, disassembling, and recycling of e-waste. The model's effectiveness is demonstrated through numerical analysis and sensitivity analysis of key factors.
Article
Mathematics
Surendra Vikram Singh Padiyar, Shiv Raj Vandana, Shiv Raj Singh, Dipti Singh, Mitali Sarkar, Bikash Koli Dey, Biswajit Sarkar
Summary: This study develops a three-echelon supply chain model to address product deterioration during storage or transportation and considers the impact of inflation on supply chain profit. The model shows that a decrease in the inflation rate leads to a continuous increase in total profit.
Article
Computer Science, Artificial Intelligence
Shaktipada Bhuniya, Sarla Pareek, Biswajit Sarkar
Summary: This study introduces different business strategies based on trade credit, revenue sharing contract, variable demand and production rate. Its main aim is to find the best strategy for profit maximization of the supply chain members, and it establishes a theoretical global optimization. The experimental results verify the global optimality of these strategies.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Asif Iqbal Malik, Biswajit Sarkar, Muhammad Waqas Iqbal, Mehran Ullah, Irfanullah Khan, Muhammad Babar Ramzan
Summary: This paper focuses on coordination in a two-member supply chain with a flexible production system under buyer's service level constraint and stochastic demand. Multiple inspection policy and discrete investment function are used to improve cost-sharing scenario. The study develops three SC models and the results show that the centralized cooperative model based on Nash bargaining significantly improves the overall profit of the SC.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Editorial Material
Environmental Sciences
Irfan Ali, Biswajit Sarkar, Syed Mithun Ali, Armin Fuegenschuh
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2023)
Article
Business
Han Lim, Kathleen B. Aviso, Biswajit Sarkar
Summary: This study aims to develop an optimal strategy for retailers in an agricultural supply chain, considering online, offline, and buy-online-pick-up-in-store channels. The study focuses on traceability technologies, services, advertisements, and holding costs to maximize retailer profits. The results show that the proposed multi-modal omnichannel policy can increase the expected profits by investing in advertising, services, product traceability, and product-quality keeping.
ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS
(2023)
Article
Business
Biswajit Sarkar, Rekha Guchhait
Summary: Competition in the supply chain business is challenging, with environmental protection being an adjacent issue. Supply chain players follow carbon policies to reduce emissions while maximizing profits, but information asymmetry among players affects supply chain profit. This study develops a green supply chain management with reduced information asymmetry through technology support, and finds that a non-coordination policy is more profitable than a coordination policy.
ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS
(2023)
Article
Automation & Control Systems
Chiranjibe Jana, Momcilo Dobrodolac, Vladimir Simic, Madhumangal Pal, Biswajit Sarkar, Zeljko Stevie
Summary: This paper addresses and solves the critical problem of selecting the most sustainable strategy for urban parcel delivery. It proposes an assessment framework and introduces a new evaluation method, finding that the united consolidation center is the most sustainable strategy.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Mathematics
Sandipa Bhattacharya, Mitali Sarkar, Biswajit Sarkar, Lakshmi Thangavelu
Summary: This research focuses on the unsustainable and unstable demand and consumption of electrical energy, exploring a mixed-integer non-linear programming model of an energy supply chain that combines the roles of a manufacturer and retailer to achieve reliable energy generation alternatives from both technical and economic perspectives. The study emphasizes the manufacturer's efforts and the importance of government subsidies, confirms the validity of the model through experimental evaluation, and demonstrates the economic growth potential and significance of sustainable development.
Article
Mathematics
Taniya Mukherjee, Isha Sangal, Biswajit Sarkar, Qais Almaamari, Tamer M. Alkadash
Summary: The present consumer behavior is driven by fast fashion, resulting in increased greenhouse gas emissions from the fashion industry. In this study, efforts are made to minimize the cost and carbon emissions in managing returned articles in the primary and secondary markets. Reverse cross-docking is implemented for managing returns, and green technology investment is addressed to reduce emissions. The results show that despite a slight increase in total cost, green technology investment leads to a significant reduction in carbon emissions. Additionally, reverse cross-docking is found to be a better option for cost minimization compared to traditional warehousing.
Article
Environmental Sciences
Ashish Kumar Mondal, Sarla Pareek, Biswajit Sarkar
Summary: The remanufacturing industry provides the opportunity to rework defective products and make them useful again. This study investigates a flexible production system to reduce the overuse of machines for repetitive tasks. A two-stage production system is considered, where common parts are produced and remanufactured in Stage 1, and product-specific production and remanufacturing processes are completed in Stage 2. The study aims to optimize the cycle time and production rate, and results show that the two-stage system with a shared-production process is cost-efficient and reduces the cycle time.
AIMS ENVIRONMENTAL SCIENCE
(2023)
