Advanced Control Technologies Research Articles

Classification of NOx Emission in Marine Engines Utilizing kNN-Based Machine Learning Algorithms

Marine diesel engines are crucial for powering large vessels in the maritime sector and are known for their efficiency across various industries. However, increasing environmental concerns and stringent regulations targeting air pollutants such as nitrogen oxides (NOx) and particulate matter (PM) have heightened the need for advanced emission control technologies. Addressing this challenge, the study focuses on developing a reliable method to predict NOx emission levels in marine engines, reducing reliance on resource-intensive experimental testing. Leveraging machine learning techniques, particularly k-nearest neighbors (kNN)-based algorithms, the research classifies NOx emissions in marine engines operating under the Reactivity-Controlled Compression Ignition (RCCI) strategy. Comparative performance analysis reveals that the FPFS-kNN algorithm achieves the highest accuracy (90.00%) alongside strong precision (84.23%), recall (82.37%), and F1 score (82.47%). These findings underscore the potential of machine learning in emission prediction and highlight directions for future exploration in this domain.

Advanced integration of IoT and AI algorithms for comprehensive smart meter data analysis in smart grids

Abstract Smart grids utilize advanced communication, information, and control technologies to build a more friendly power supply system. However, the development of technology leads to the increasing complexity of smart meter (SM) data in the power grid, and analyzing SM data becomes difficult. Therefore, in order to realize the effective analysis and forecasting of users’ electricity consumption behavior, an SM data analysis technique integrating the Internet of Things and artificial intelligence is proposed, which contains three major techniques: meter reading systems, load clustering, and load forecasting, and at last the technique is validated. Finally, the technology is validated. The experimental results showed that the average value of the Davis-Balding index for the proposed method combining recursive graphs and convolutional autoencoders was 1.87, which was significantly lower than the average value of 2.35 for other methods. The average value of the Dunn index was 0.086, which was higher than the 0.065 for the comparison method. In the load forecasting model, the model that employs multi-task learning and a gated cycle unit demonstrates superior performance across all comparison schemes, with the lowest average absolute percentage error of 12.90%. This is significantly lower than the comparison model’s 15.35%, which highlights the enhanced efficacy of the proposed model. The study realizes the effective analysis and prediction of consumers’ electricity consumption behavior and provides new ideas and solutions for the optimization and management of smart grids.

Solar Energy Applications in Protected Agriculture: A Technical and Bibliometric Review of Greenhouse Systems and Solar Technologies

This study addresses solar energy applications in protected agriculture, focusing on greenhouses and related technologies. A bibliometric and technical analysis is developed, covering research published between 1976 and 2024, to identify the main trends and challenges in the use of solar energy in controlled environments. The methodology was based on the PRISMA approach, using the Scopus database to retrieve relevant documents. From an initial total of 221 documents, 216 were selected after a filtering and debugging process, ensuring the relevance of the final set. In the analytical phase, the results showed a moderate growth of 3.68% in the annual publication rate, highlighting the impact of research on solar energy’s application to air conditioning and energy efficiency in greenhouses. Most of the studies reviewed feature hybrid systems that combine solar energy with other resources, and we highlight both advances in climate control through artificial intelligence and the implementation of photovoltaic and thermal technologies to improve the energy efficiency of agricultural systems. The results also underline the importance of tomato cultivation in the selected studies, reflecting its global economic impact. The conclusions highlight the need for the further integration of energy storage and desalination technologies, especially in arid regions with high solar irradiation, to ensure the sustainability of greenhouses. It is proposed that future research should address the wider implementation of hybrid systems and advanced climate control technologies, optimizing both the use of energy resources and the performance of crops under cover. In addition, it is recommended that international collaboration be strengthened to address technical and climatic challenges in protected agriculture and to expand the adoption of innovative solutions in different geographical contexts.

Optimizing shutdown and startup procedures in oil facilities: A strategic review of industry best practices

Shutdown and startup procedures in oil facilities are critical processes that significantly impact operational efficiency, safety, and environmental compliance. This strategic review examines industry best practices for optimizing these procedures to minimize downtime and enhance productivity. Effective shutdown and startup operations are essential not only for maintaining equipment integrity but also for ensuring the safety of personnel and compliance with regulatory standards. The complexities of oil facility operations necessitate a thorough understanding of the interdependencies between various systems and processes during these phases. This review identifies key factors that contribute to successful shutdown and startup procedures. First, comprehensive planning and preparation are vital. Establishing a detailed shutdown/startup plan that outlines specific tasks, timelines, and responsibilities helps mitigate risks associated with unplanned events. This includes conducting risk assessments and ensuring that all personnel are adequately trained to execute their roles effectively. Second, the implementation of advanced monitoring and control technologies is crucial. Utilizing automation and real-time data analytics allows for precise control over processes during shutdowns and startups, enabling quicker responses to anomalies. This technological integration can significantly reduce the time required for these operations while enhancing safety measures. Third, collaboration and communication among teams are essential components of successful operations. Encouraging a culture of open communication fosters teamwork and ensures that all stakeholders are aligned throughout the shutdown and startup phases. Regular debriefings and feedback sessions post-operations also play a vital role in continuous improvement. In conclusion, optimizing shutdown and startup procedures in oil facilities is paramount for enhancing operational efficiency and safety. By adopting industry best practices, including thorough planning, leveraging technology, and promoting effective communication, organizations can achieve significant improvements in their operational performance. This review serves as a resource for industry stakeholders aiming to refine their shutdown and startup strategies to achieve operational excellence. Keywords: Shutdown Procedures, Startup Procedures, Oil Facilities, Operational Efficiency, Safety, Environmental Compliance, Risk Assessment, Automation, Real-Time Data Analytics, Industry Best Practices.

Review of PID Control in Industrial Areas for Tobacco Production, Self-driving Car Technology and Robotic Arm Robots

Abstract. PID control is widely employed across diverse industries such as tobacco production, autonomous car technology, and mechanical arm robotics. This shows that PID control has a substantial developmental potential, so I choose the PID control as the topic. Since few people summarize its different applications in different industries, this study has the motivation to comprehensively summarize the applications of PID. This research provides an in-depth overview and analysis of PID control's varied applications in tobacco production, autonomous car technology, and mechanical arm robotics. It focuses on addressing practical challenges and exploring optimization strategies encountered in these fields. This article is summarized using the methods of the review. PID plays a crucial role in enhancing stability, precision, and response speed in these applications, thereby improving overall control system dynamic response performance. This study consolidated existing literature to offer insights into PID's effectiveness across these industrial sectors, shedding light on its impact and potential for further advancements in control technology.

Biofuel blends and nano-additives: a sustainable approach to diesel engine performance and emissions improvement

Abstract The utilization of compression ignition (CI) diesel engines has seen a substantial increase in recent years owing to their numerous advantages. However, the widespread adoption of these engines has also significantly contributed to environmental pollution issues, with diesel engines being recognized as major global contributors to exhaust emissions-related pollution. To address this issue, comprehensive research has been carried out on both emissions from diesel exhaust pollutants and advanced after-treatment technologies for emission control. This study aims to evaluate the efficiency and emissions of diesel fuel mixed with various ratios of biofuel derived from Karanja seeds (B10, B15, and B20). Among the different blends examined, B20 demonstrated superior performance in terms of brake thermal efficiency (BTE) and brake-specific fuel consumption (BSFC), along with lower levels of hydrocarbon (HC) and carbon dioxide (CO2) emissions compared to pure diesel. Further, the impact of nanoadditives, specifically titanium dioxide (TiO2), at different concentrations (80 ppm, 100 ppm, and 120 ppm), on B20 blends was evaluated. The findings indicated that B20 blended with 100 ppm of TiO2 exhibited superior performance in terms of BTE, BSFC, and lower emissions of HC, CO2, nitrogen oxides (NOx), and carbon monoxide (CO). From the results, the BTE increases from 1% to 33%, illustrating enhanced thermal efficiency under similar conditions. The average BSFC across all loads and speeds in the table is approximately 0.89 kg kW−1h−1, while the average BTE stands at approximately 23.1%.

RESEARCH

As buildings become increasingly integrated with advanced control technologies, cybersecurity concerns have risen significantly. This is particularly true for networked lighting systems, as cybersecurity has become more important due to their growing integration with IP networks and other building IT and operational technology (OT) systems. Historically, electricians have focused on physical and electrical installations, occasionally handling system commissioning. However, the advent of networked control systems in modern buildings requires electricians to acquire a new skill set. These systems, often deployed with default configurations, can be vulnerable to unauthorized access and cyberattacks, posing significant security risks to the entire building.

Numerical analysis of stress distribution due to upper protective layer mining and its impact on gas extraction

Pressure-relief gas extraction through the floor directional long boreholes is an advanced and effective gas control technology for the upper protective layer of contiguous coal seams. This study systematically analyzed the effects of mining activities on stress distribution in the underlying strata and developed an analytical equation to calculate the permeability distribution of the protected layer under mining-induced conditions. The results indicate that the effective extraction radius of directional long boreholes increased by 186% as the mining distance of the upper protective layer extended from 50 to 150 m. Furthermore, increasing the borehole diameter from 89 to 153 mm led to a 14.8% improvement in gas extraction efficiency, while raising the negative pressure from 15 to 35 kPa resulted in a 19.6% increase in the effective extraction radius. These findings provide valuable guidance for optimizing borehole design parameters and gas extraction efficiency, ensuring safer and more effective gas control in coal mining operations.

Integrated Mechanical and Electronic Design and Comfort Optimization in Smart Furniture

Smart furniture, as an important component of modern home environments, integrates advanced mechanical design and electronic control technologies, enhancing the quality of life for users through automatic sensing and adjustment. With the development of technology, the functionality of smart furniture has continuously expanded, and comfort has become a central focus in its design. This paper explores the integrated mechanical and electronic design in smart furniture, examining its structural design, electronic system integration, and the application of human-machine interaction technology in comfort optimization. The study indicates that the high integration of mechanical and electronic systems not only improves the functionality of the furniture but also optimizes the user experience through technologies such as smart adjustments and personalized control. By using comfort evaluation standards and optimization models, combined with innovative applications of material selection and environmental sensing technologies, smart furniture can adaptively adjust according to different user needs and environmental conditions, thereby achieving optimal comfort. This paper provides a theoretical basis for the design and optimization of smart furniture and points out the direction for future development.

Feasibility and design of nonlinear negative‐stiffness isolating approach for solid‐rocket‐motor‐type structures

AbstractSolid rocket motor (SRM)‐type structures are popular due to their reliability, considering that service safety during transportation can be improved by applying advanced vibration control technologies. In this study, a negative‐stiffness‐enhanced isolation system (NSeIS) with appropriately designed linear and nonlinear properties was developed to vertically isolate SRMs subjected to transportation‐ and deployment‐induced vibrations. The NSeIS design, based on the combination of a negative‐stiffness device and vertical isolator, involved a clear mechanical model, physical realization, and mechanical properties. Parametric analyses were performed on a typical SRM controlled with a linear and nonlinear NSeIS and a conventional isolation system. Subsequently, a feasible parameter domain and design recommendations were deduced. Finally, design cases for the SRM for time‐domain verification were considered. The results revealed that the NSeIS offers a flexible and enhanced isolating effect through the parallel arrangement of the negative‐stiffness device and conventional isolators. For the motor‐type structure, NSeIS ensures marked enhancements in performance and multiple levels of mitigation effects. Thus, compared with a conventional isolator with the same damping, NSeIS achieves a more substantial negative‐stiffness effect for a large displacement response range owing to its nonlinear property. NSeIS can isolate more vibration‐induced energy, thereby suppressing the interface Mises stress, which is essential for SRM‐type structures.

Online characterization of primary and secondary emissions of particulate matter and acidic molecules from a modern fleet of city buses

Abstract. The potential impact of transitioning from conventional fossil fuel to a non-fossil-fuel vehicle fleet was investigated by measuring primary emissions via extractive sampling of bus plumes and assessing secondary mass formation using the Gothenburg Potential Aerosol Mass (Go:PAM) reactor from 76 in-use transit buses. Online chemical characterization of gaseous and particulate emissions from these buses was conducted using chemical ionization mass spectrometry (CIMS) with acetate as the reagent ion, coupled with the Filter Inlet for Gases and AEROsols (FIGAERO). Acetate reagent ion chemistry selectively ionizes acidic compounds, including organic and inorganic acids, as well as nitrated and sulfated organics. A significant reduction (48 %–98 %) in fresh particle emissions was observed in buses utilizing compressed natural gas (CNG), biodiesels like rapeseed methyl ester (RME) and hydrotreated vegetable oil (HVO), and hybrid-electric HVO (HVOHEV) compared to diesel (DSL). However, secondary particle formation from photooxidation of emissions was substantial across all the fuel types. The median ratio of particle mass emission factors of aged to fresh emissions increased in the following order: DSL buses at 4.0, HVO buses at 6.7, HVOHEV buses at 10.5, RME buses at 10.8, and CNG buses at 84. Of the compounds that can be identified by CIMS, fresh gaseous emissions from all Euro V/EEV (Enhanced Environmentally friendly Vehicle) buses, regardless of fuel type, were dominated by nitrogen-containing compounds such as nitrous acid (HONO), nitric acid (HNO3), and isocyanic acid (HNCO), alongside small monoacids (C1−C3). Notably, the emission of nitrogen-containing compounds was lower in Euro VI buses equipped with more advanced emission control technologies. Secondary gaseous organic acids correlated strongly with gaseous HNO3 signals (R2=0.85–0.99) in Go:PAM, but their moderate to weak correlations with post-photooxidation secondary particle mass suggest that they are not reliable tracers of secondary organic aerosol formation from bus exhaust. Our study highlights that non-regulated compounds and secondary pollutant formation, not currently addressed in legislation, are crucial considerations in the evaluation of environmental impacts of future fuel and engine technology shifts.

B-195 Accelerating Molecular Diagnostics: Development of a novel Rapid, Integrated PCR System for Acute Respiratory Infections Detection

Abstract Background The COVID-19 pandemic and acute respiratory infections have underscored the necessity for high-throughput and timely molecular diagnostics. Existing molecular diagnostic methods are labor-intensive, a challenge particularly evident in large-scale testing. This study aims to streamline the nucleic acid testing process by integrating extraction and detection in PCR testing, thereby optimizing efficiency. Methods We developed 'EXP-160R', an integrated PCR system capable of rapid thermal cycling. This innovation employs advanced temperature control technology to markedly reduce heating, cooling, and annealing-extension times. The PCR reagent-kit (Zybio Inc.) was optimized to complement the instrument's capabilities, aiming for pathogen nucleic acid detection in acute respiratory infections within 25 minutes. The precision of in-tube temperature during rapid amplification was validated by using temperature-sensitive molecular probes in system development stage. Performance evaluation used the WHO International Standard for SARS-CoV-2 RNA to assess sensitivity and detection limits. We also analyzed 500 clinical samples from multiple Chinese hospitals, including 295 COVID-19 positives and 205 negatives, comparing the EXP-160R system's performance with an NMPA-approved PCR kit. Results The innovative system significantly improved PCR cycle times, enabling detection of 16 samples in 22 minutes and a throughput of 2400 tests per day, without compromising sensitivity or specificity. Validation confirmed a detection limit of 200 copies/mL, and the system achieved a 100% detection rate for medium and high viral load samples, with a coefficient of variation (CV) for Ct values ≤ 5%. Clinical trial comparisons with clinical standard diagnostics revealed a sensitivity of 98.05%, specificity of 100%, accuracy of 99.2%, and a Kappa coefficient of 0.984. When compared to the established PCR kit, our system showed comparable efficacy, with a sensitivity of 98.50%, specificity of 98.67%, accuracy of 98.6%, and a Kappa of 0.971. Conclusions The rapid PCR system represents a significant advancement in molecular diagnostics, offering rapid, high-throughput, and accurate detection of SARS-CoV-2. This system is particularly beneficial in urgent testing scenarios, such as airports and fever clinics. It addresses current pandemic needs and sets a new benchmark for future respiratory and infectious disease diagnostics, enhancing both efficiency and user experience.

Multidisciplinary Optimization of Aircraft Aerodynamics for Distributed Propulsion Configurations

The combination of different aerodynamic configurations and propulsion systems, namely, aero-propulsion, affects flight performance differently. These effects are closely related to multidisciplinary collaborative aspects (aerodynamic configuration, propulsion, energy, control systems, etc.) and determine the overall energy consumption of an aircraft. The potential benefits of distributed propulsion (DP) involve propulsive efficiency, energy-saving, and emissions reduction. In particular, wake filling is maximized when the trailing edge of a blended wing body (BWB) is fully covered by propulsion systems that employ boundary layer ingestion (BLI). Nonetheless, the thrust–drag imbalance that frequently arises at the trailing edge, excessive energy consumption, and flow distortions during propulsion remain unsolved challenges. These after-effects imply the complexity of DP systems in multidisciplinary optimization (MDO). To coordinate the different functions of the aero-propulsive configuration, the application of MDO is essential for intellectualized modulate layout, thrust manipulation, and energy efficiency. This paper presents the research challenges of ultra-high-dimensional optimization objectives and design variables in the current literature in aerodynamic configuration integrated DP. The benefits and defects of various coupled conditions and feasible proposals have been listed. Contemporary advanced energy systems, propulsion control, and influential technologies that are energy-saving are discussed. Based on the proposed technical benchmarks and the algorithm of MDO, the propulsive configuration that might affect energy efficiency is summarized. Moreover, suggestions are drawn for forthcoming exploitation and studies.

A Review of Model Predictive Control for the Municipal Solid Waste Incineration Process

Municipal solid waste incineration (MSWI) is essential for tackling urban environmental challenges and facilitating renewable energy recycling. The MSWI process has characteristics of multiple variables, strong coupling, and complex nonlinearity, requiring advanced process control (APC) technology. Although there have been several reviews on the modeling and control of the MSWI process, there is a lack of focus on model predictive control (MPC), a widely used APC technology. This article aims to comprehensively review MPC strategies in the MSWI process. First, it describes MSWI process technology in detail, examining control issues and objectives to highlight the complexity and challenges in controller design while providing an overview of MPC methods and their benefits. Second, it reviews incinerator modeling for control, including traditional modeling techniques and machine learning technologies such as fuzzy neural networks. Third, it reviews the controllers used for MSWI process, emphasizing the advantages of MPC over existing control methods. Fourth, it discusses the current status of MPC design and online updates, covering the need for an accurate dynamic predictive model and objective function and the online updates components such as predictive modeling, rolling optimization, and feedback correction. Finally, the study concludes with a summary of the findings.

CRISPR/Cas9-Based Genome Editing of Fall Armyworm (Spodoptera frugiperda): Progress and Prospects.

The fall armyworm (Spodoptera frugiperda) poses a substantial threat to many important crops worldwide, emphasizing the need to develop and implement advanced technologies for effective pest control. CRISPR/Cas9, derived from the bacterial adaptive immune system, is a prominent tool used for genome editing in living organisms. Due to its high specificity and adaptability, the CRISPR/Cas9 system has been used in various functional gene studies through gene knockout and applied in research to engineer phenotypes that may cause economical losses. The practical application of CRISPR/Cas9 in diverse insect orders has also provided opportunities for developing strategies for genetic pest control, such as gene drive and the precision-guided sterile insect technique (pgSIT). In this review, a comprehensive overview of the recent progress in the application of the CRISPR/Cas9 system for functional gene studies in S. frugiperda is presented. We outline the fundamental principles of applying CRISPR/Cas9 in S. frugiperda through embryonic microinjection and highlight the application of CRISPR/Cas9 in the study of genes associated with diverse biological aspects, including body color, insecticide resistance, olfactory behavior, sex determination, development, and RNAi. The ability of CRISPR/Cas9 technology to induce sterility, disrupt developmental stages, and influence mating behaviors illustrates its comprehensive roles in pest management strategies. Furthermore, this review addresses the limitations of the CRISPR/Cas9 system in studying gene function in S. frugiperda and explores its future potential as a promising tool for controlling this insect pest.

Preface: 6th International Conference on Automatic Control and Mechatronic Engineering (ACME 2024)

2024 6th International Conference on Automatic Control and Mechatronic Engineering (ACME 2024) is to facilitate an exchange of information on best practices for advanced automation, control technology, vehicle engineering, electronic engineering, electrical engineering, mechanical engineering, and mechatronic engineering, addressing the problems and opportunities of a sustainable future. This conference provides a forum for engineers and scientists in academia, industry, and government to address the most innovative research and development including technical challenges and economic issues, and to present and discuss their ideas, results, work in progress and experience in these aspects. ACME 2024 was held during July 13-14, 2024, in Sapporo, Japan. The development of science occurs by utilizing collaboration with other branches of science such as technology, mechanical engineering, and mathematics. The distinctive feature of collaboration that has become an important value. We thank all participants for ACME 2024 who have contributed their research. I hope, with this kind of collaboration, we can jointly improve the development quality in this era. Organizing Committees of ACME Sapporo, Japan

Water neutrality: Concept, challenges, policies, and recommendations

Agriculture, urbanisation, and industrial growth have significantly increased water demand, leading to water pollution, necessitating the protection of rivers, wetlands, and ecosystems. Hence, a strategy is needed that is aligned with Sustainable Development Goal (SDG) 6, which includes ensuring safe and affordable drinking water (SDG 6.1), implementing integrated water resources management (SDG 6.5), and protecting and restoring water-related ecosystems (SDG 6.6). This review article introduces the concept of water neutrality (WN), a planning approach for new urban developments aimed at minimising impacts on water security. The peer-reviewed articles and governmental reports published between 2014 and 2024 provide an overview of the current water situation. It also explores the potential benefits of WN, evaluates existing policies and case studies, and offers actionable recommendations. The study reveals that implementing water-related policies often faces challenges, such as political commitment, insufficient funding, and weak monitoring systems, particularly in developing countries. In India, water policies primarily focus on irrigation, drinking water supply, and pollution control. However, these policies struggle due to weak enforcement and conflicting stakeholder interests. The study recommends significant policy reforms and the adoption of new approaches to achieve WN, which promote integrated water resource management, strengthen governance, pricing mechanisms, advanced pollution control technologies, climate-resilient infrastructure, and public awareness, all while aligning with SDG 6. Innovative solutions, such as smart irrigation systems and water recycling programs, offer promising paths to address water scarcity. Additionally, international collaborations can further support these goals. Integrating WN into SDG 6 has the potential to significantly enhance global water security and sustainability.

Comprehensive Study of Load Characteristics of O-type Rotor Car Dumper Based on Measurements

The car dumper, an essential apparatus for unloading bulk materials, is increasingly critical across various sectors such as electricity generation, metallurgy, and operations at port terminals. This significance stems from its continuous operational capacity, which significantly boosts the efficiency of bulk material handling and optimizes the overall processes at industrial sites. This research paper delves into the power quality problems associated with car dumper applications, particularly focusing on the harmonic disturbances caused by inverters used within these systems. Such disturbances can degrade the quality of power within the industrial grid, potentially leading to inefficiencies and safety hazards. To address these issues, the paper proposes the use of parallel active power filters (APF). These filters are renowned for their efficiency in controlling and mitigating harmonic disruptions in electrical systems. The implementation of APFs has shown promising potential to stabilize power quality by filtering unwanted harmonic frequencies and allowing for a smoother power flow. Through detailed measurements conducted on an O-type rotor quad car dumper, the study systematically analyzes the operational characteristics of the dumper, thereby forming a comprehensive database. This database aids in the optimization of electrical control strategies and operational methodologies for car dumpers.The primary objectives of this research are to enhance the operational efficiency of car dumpers, minimize their energy consumption, and improve overall safety measures. By integrating advanced harmonic control technologies such as APF, this study not only addresses the immediate issues of power quality but also contributes to the broader goal of sustainable and efficient industrial practices. The findings are expected to influence future designs and operations of car dumpers, making them more energy-efficient and less prone to electrical disturbances, thereby ensuring a safer working environment in industries dependent on heavy machinery for bulk material handling.

Current Status of Yam Diseases and Advances of Their Control Strategies

Yam (Dioscorea spp.) is an important tuber crop consumed globally. However, stable yam production faces challenges from a variety of diseases caused by fungi, nematodes, viruses, and bacteria. Prominent diseases such as anthracnose, leaf spot, yam wilt, dry rot, and crazy root syndrome, currently pose serious threats to yam yields. These diseases not only result in quality degradation but also cause great economic losses. This review summarizes the damages, symptoms, causal agents, and epidemic factors of major yam diseases. It also outlines a comprehensive disease control strategy that includes the use of resistant varieties, proper crop rotation, sanitation measures, and the application of agrochemicals and biocontrol agents. Additionally, this review addresses future perspectives on risk factors and knowledge gaps, aiming to serve as a reference for in-depth research into advanced disease monitoring and control technologies for yams.

Machine learning & conventional approaches to process control & optimization: Industrial applications & perspectives

Technologies based on Artificial Intelligence (AI) and Machine Learning (ML) concepts are advancing at a rapid pace. The new paradigms are challenging the status-quo of mature automation and control technologies in industry. Autonomous operation is a frequently stated goal of AI evangelists and technology providers. This white paper gives an overview of the current state of art of advanced process control and optimization technologies. It also provides a brief summary of the AI and ML-based approaches that address the closed-loop control and optimization space. Some results from industrial implementations are shared for both conventional and AI/ML-based approaches. Experience from four industrial applications is shared, covering rigorous model-based, machine learning and hybrid approaches to real-time optimization and control problems. The applications range from unit-based control & optimization to refinery & network wide optimization. A set of high-level requirements that need to be satisfied regardless of the underlying technology for closed-loop autonomous operations is reviewed. The article concludes with some future directions and perspectives highlighting areas where the emerging technologies may have significant impact in industry.