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Trained deep reinforcement learning (DRL) based controllers can effectively control dynamic systems where classical controllers can be ineffective and difficult to tune. However, the lack of closed‐loop stability guarantees of systems controlled by trained DRL agents hinders their adoption in practical applications. This research study investigates the closed‐loop stability of dynamic systems controlled by trained DRL agents using Lyapunov analysis based on a linear‐quadratic polynomial approximation of the trained agent. In addition, this work develops an understanding of the system's stability margin to determine operational boundaries and critical thresholds of the system's physical parameters for effective operation. The proposed analysis is verified on a DRL‐controlled system for several simulated and experimental scenarios. The DRL agent is trained using a detailed dynamic model of a non‐linear system and then tested on the corresponding real‐world hardware platform without any fine‐tuning. Experiments are conducted on a wide range of system states and physical parameters and the results have confirmed the validity of the proposed stability analysis (https://youtu.be/QlpeD5sTlPU). [ABSTRACT FROM AUTHOR]

Abstract Trained deep reinforcement learning (DRL) based controllers can effectively control dynamic systems where classical controllers can be ineffective and difficult to tune. However, the lack of closed‐loop stability guarantees of systems controlled by trained DRL agents hinders their adoption in practical applications. This research study investigates the closed‐loop stability of dynamic systems controlled by trained DRL agents using Lyapunov analysis based on a linear‐quadratic polynomial approximation of the trained agent. In addition, this work develops an understanding of the system's stability margin to determine operational boundaries and critical thresholds of the system's physical parameters for effective operation. The proposed analysis is verified on a DRL‐controlled system for several simulated and experimental scenarios. The DRL agent is trained using a detailed dynamic model of a non‐linear system and then tested on the corresponding real‐world hardware platform without any fine‐tuning. Experiments are conducted on a wide range of system states and physical parameters and the results have confirmed the validity of the proposed stability analysis (https://youtu.be/QlpeD5sTlPU).

This essay is a pedagogical parable. It tells a poignant story of transformative learning in community and immersed in place. Sometimes we struggle to achieve new learning and insight. It requires patience, discipline, and determination. And then, somewhat miraculously, when both internal and external conditions are just right, a fog can lift that allows us to see through new eyes. Something of profound beauty emerges, which as it turns out, much to our wonderment, has in fact been there all along. This is "Crane Time". [ABSTRACT FROM AUTHOR]

Urbanization, industrialization, and intensification of agriculture have led to considerable heavy metal pollution across the globe, harming our ecosystems. Concentrations of arsenic (As), cadmium (Cd), copper (Cu), and lead (Pb) have been analysed in 249 eggshells collected between 2006 and 2021 from 83 female Common Cranes (Grus grus) nesting within north-eastern Germany. Information on the presence of trace elements in cranes from Europe and their potential adverse effects on the reproduction are largely missing. Only Cu and Pb were found to be present in eggshell samples. Levels of both metals did not exceed concentrations considered potentially toxic in birds and unhatched eggs did not contain higher metal concentrations compared to eggshell residues from hatched eggs. Statistical analysis revealed that trace element concentrations decreased significantly over the course of the study period. The ban of leaded gasoline in the early twenty-first century and strict limitations of heavy metal-based biocontrol products are likely responsible for this decrease over the years. However, as Cu levels gradually increase with increasing proportions of agricultural areas within the cranes' home ranges, we suggest that considerable amounts of Cu originating from agricultural practises are still being released into the environment. We found no increase in metal concentrations in eggshells with increasing female age, suggesting that heavy metals do not accumulate in the circulatory systems of the adults over time. This study is the first to assess heavy metal contamination in Common Cranes and indicates the suitability of crane's eggshells as bioindicator for monitoring environmental pollution. [ABSTRACT FROM AUTHOR]

Effective control of the tower crane system (TCS) is crucial for the safe and quick transport of goods from one point to another in industries and construction sites. However, the existing literature either depends on the dynamic model of the system, which is prone to errors and assumptions, or requires the feedback of the states to be controlled, which can be costly and or complex. In particular, the TCS has many states and is highly nonlinear. Thus, a non‐model‐based control approach that depends on minimal feedback sensors is needed. The primary contribution of this work is that the potential hybrid configurations of the input shaping control (ISC) and fuzzy logic control (FLC) were proposed and investigated. The study provides the best hybrid configuration of the ISC and FLC (non‐model‐based controllers) for optimal positioning and anti‐swing control of the TCS. Three configurations of the ISC + FLC, namely shaper as reference input (SARI), shaper as input to the FLC (SAI2F), and shaper as input to the plant (SAI2P) were investigated to assess the optimal hybrid configuration of the ISC + FLC. The results demonstrated that the hybrid ISC + FLC scheme had improved the response of ISC by at least 150% and enhanced the oscillation reduction of FLC by 72%. Finally, these analyses showed that the ISC + FLC could achieve reasonable control of the tower crane by only considering the output of one state (position). This makes the control scheme cheaper and reduces the complexity and computational time compared to other full‐state feedback controllers. [ABSTRACT FROM AUTHOR]

Industrial building structure planning complies with standards and regulations, such as Procedures for Earthquake Resistance Planning, Minimum Loads for Building Design, and Specifications for Structural Steel Buildings. Vertical and lateral loads are fundamental to the structure's load flow process. Industrial buildings handle roof, wind, earthquakes, crane, and wall loads. Structural design must consider these elements, including the choice of lateral force-resisting systems such as X-bracing. In determining building loads, including earthquake and wind loads, various parameters such as wind speed, exposure category, and other factors must be considered by standard requirements such as SNI 1727-2020 and SNI 1726:2019. Selection of site class, wind direction, topographic, and ground surface elevation factors are essential in determining wind loads. This research method focuses on supporting structures consisting of purlins and girts in the context of industrial buildings. Purlins, made from hot or cold rolled steel, generally use C and Z profiles. Girts, made from cold or hot rolled steel, have profile variations such as C, Z, or hollow square sections. The girt structure design process determines dimensions, rod sag, internal requirements, and sag rod capacity. [ABSTRACT FROM AUTHOR]

A reliable assessment of the population size of threatened species is crucial for making informed decisions about their conservation and management. However, there is a lack of comprehensive knowledge on the population of the eastern Black Crowned Crane (Balearica pavonina ceciliae), which is globally recognized as a threatened taxon experiencing a declining population trend. Here, we investigated the density, abundance and factors that influence flock size in the wetlands of the Gambella region in Ethiopia. We used line transects to collect data during dry and wet seasons. Population density and abundance were estimated using DISTANCE software, whereas factors influencing crane flock size were evaluated using a generalized linear model. We found that crane density ranged from 444 to 965 birds per sq km in the dry season and from 62 to 105 individuals per sq km in the wet season. We estimated that the population size within the designated survey areas as 7634 during the dry season and 866 during the wet season. Furthermore, for the broader survey region that encompasses permanent wetlands, the estimated population ranged from 9138 to 19,849 individuals in the dry season and from 1272 to 2166 individuals in the wet season. We found that grazing intensity and proximity to woodlands and rivers had significant positive impacts on crane flock size, whereas an increase in wetland water depth and grass height remarkably reduced flock size. As a result, wetland habitat degradation-related problems are not currently a threat to cranes in this region, but are likely to increase in the future due to large-scale agricultural expansion. The crane population size we estimated in Gambella is high, three to four times higher than the estimate from the entirety of Ethiopia. Our research underscores the global significance of Gambella wetlands as an important habitat for cranes. However, to obtain an accurate population estimate in this region, it is imperative to include seasonal wetlands, savannah grasslands, farmlands and the extended wetlands of South Sudan, which are hydrologically connected to the wetlands of Gambella region. To achieve this, comprehensive surveys and estimations should incorporate various techniques, such as aerial surveys, satellite telemetry, and high-resolution satellite imagery.

The objective of microgrid operation is to supply the energy demanded by the loads at minimum cost. To achieve this goal, new tools are being proposed in the literature, such as the use of optimal schedulers in the field of multi-vector management systems. An optimal scheduler provides the hourly schedule of the flexible loads that exist in a microgrid to maximize the use of local renewable resources. This work aims to investigate the application in the context of five optimization algorithms in terms of energy and computation costs and to demonstrate how optimal schedulers can contribute significantly to reducing energy operating costs in new and real microgrid scenarios. The analysis of the algorithms is carried out through an experimental process on the existing installations at Port of Borg (Norway), which contains photovoltaic production and different types of flexible assets, such as cranes, electric vehicle charging stations, and electrical storage. Real data gathered at the port's premises is used to assess the energy cost reduction when the optimal scheduler is part of the energy management system, and the computations are performed in real time to apply the proposed schedule to the pilot. The results show how the use of optimal schedulers can reduce operation costs up to 17.2%, augmenting local energy production utilization, and that using two OS algorithms in cascade can also reduce the computation time.

Offsite construction methods have shown many advantages over traditional construction techniques, especially related to efficiency and productivity during the construction phase. Nevertheless, offsite construction generally involves oversizing the internal structure of the modules due to the internal stresses produced during transport and lifting operations, producing an increase in material usage, direct cost, and carbon footprint. In developing countries, the direct cost of social housing is the most important factor determining the feasibility of construction. For this reason, oversizing the internal structure of the modules can play an important role in the adoption of a modern construction technique such as offsite construction systems. In order to solve this issue, a temporary reusable stiffener structure is proposed to allow an economical offsite construction system using a lightweight steel framing structure used in traditional methods. The reusable structure was designed using a finite element method, and the direct cost and carbon footprint of the structure were evaluated. The results show that the proposed construction strategy allows for a low cost and reduced environmental impact due to a lower usage of materials in the modules and the possibility of a circular economy approach to the reusable structure. [ABSTRACT FROM AUTHOR]

The first summary of the past distribution (8000 to 1000 BP) of the common crane in Bulgaria is presented. It is based on the bone remains collected from 14 prehistoric and later archaeological sites. All bone remains were found in the vast lowlands and plains (mostly up to 200 m a.s.l.), often close to large rivers and lakes, which were also the species' breeding habitats until its extinction in the 1950s as a breeding species in Bulgaria. [ABSTRACT FROM AUTHOR]

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This research introduces a novel approach to optimizing control policies for waste cranes operating at waste-to-energy plants. Although previous methods forced people to define evaluation functions for automation, such design works in actual environments can often be challenging due to limited sensors and design difficulties. This paper aims to establish a methodology that achieves automation by having people respond to interactive pairwise comparison queries, which is relatively simple compared to design work. On the other hand, considering such automation, it becomes imperative to address the increased sample cost associated with slow crane operation and the complexities of decision-making due to waste inhomogeneity. Our proposed Preferential Bayesian Policy Optimization (PBPO) optimizes control policies with a small number of queries using Preference-based Bayesian optimization (PbBO) and mitigates the difficulty of decision-making by providing human evaluators who have an option to skip queries. We also incorporate a query synthesis mechanism to enhance query efficiency that generates a new preference relation from the skipped queries. PBPO’s effectiveness was validated with a scattering task employed in previous studies. Experimental results with simulated evaluators show the effectiveness of the PBPO and query synthesis. Furthermore, results with actual human evaluators indicate that our proposed method performs as well as the Bayesian optimization (BO) method, which requires an evaluation function.

In the crane industry, the sizing of hoisting machinery is based on several factors, including the weight of the load being lifted, the frequency of the duty cycles, the speed at which the lifting is done, and the method of rope reeving. Industrial cranes, such as those used in the Paper, Automotive, Steel, and Power industries, often utilize hoists with a true vertical lift rope reeving method that employs both left-handed and right-handed ropes. The rope drum is a key component that plays a crucial role in determining the size of the hoisting gear. International design standards, such as FEM, EN, and CMAA, govern the dimensioning of the rope drum. These design standards not only confirm the strength of the drum tube but also provide guidance on the maximum permissible fleet angle for ropes leaving the drum. This paper presents the development of an active rope guide that aims to create zero-degree drum angles, thus activating the area of use that is typically forbidden by crane standards. To test this concept, a prototype was built. [ABSTRACT FROM AUTHOR]

To solve the problems of inaccurate quality inspection and poor safety maintenance of traditional overhead cranes, this study has developed a prediction system for overhead cranes based on digital twin technology. First, interworking of the data flow between the control port of the overhead crane and the digital twin system is realized. Then, finite element technology is exploited to calculate the stress of the crane bridge, thereby performing stress rendering of the digital twin system. Next, the life of bridge cranes is predicted by the stress and strain of their main girders. Finally, synchronous overhead-crane communication combines the virtual twin system and the actual control system of the crane. The study results provide a reference for developing crane software based on digital twins. [ABSTRACT FROM AUTHOR]

The Sacramento–San Joaquin Delta is an important region for bird conservation in California, particularly as part of a large, productive estuary on the Pacific Flyway. The Delta currently provides habitat to an abundant, diverse community of birds, but it is likely only a small fraction of what the Delta’s bird community once was. Meeting the goal of restoring a healthy Delta ecosystem is legislatively required to include providing habitat for birds among the conservation goals and strategies in the Delta Plan, yet birds and their habitat needs are often not addressed in science syntheses, conservation planning, and large-scale restoration initiatives in the Delta. In this essay, we provide an avian perspective on the Delta, synthesizing recent scientific work to describe factors that contribute to the Delta’s current importance for birds, and the conservation needs of the diverse array of bird species that call the Delta home. We also evaluate the potential for the Delta to become even more important for birds in the future, incorporating climate change effects, species range shifts, and changes to the composition and configuration of the Delta’s landscape. Finally, recognizing the uncertainties about the Delta’s future landscape and the complexity of this social-ecological system, we provide recommendations—aimed at a higher- level policy and planning audience—for integrating bird conservation with other goals in the Delta. To improve ecosystem integrity, conserve biodiversity, and provide benefits to local communities of people, we urge a focus on creating a more resilient Delta and employing a diversified portfolio of conservation strategies, both old and new.

Tower cranes with slender jib transporting bulky loads are commonly applied in the construction site. Human-operated commands induce vibrations of the cantilever jib, swing, and twisting of the suspended load. Coupled oscillations among jib deflection, load swing and load twisting exhibit complex dynamic behavior. Furthermore, coupled-system frequencies significantly differ from uncoupled frequencies of the jib and pendulum. Unfortunately, little attention has been directed at the coupled-oscillation dynamics and control of jib deflection, load swing, and load twisting. A dynamic model of a tower crane slewing a slender jib and moving a distributed-mass load is derived. The fully coupled effects among jib deflection, load swing, and load twisting are described in the model. Then, an equation for predicting coupled-system frequencies is presented from the analytical model. Meanwhile, a hybrid piecewise smoother is proposed to filter out coupled oscillations among jib deflection, load swing and load twisting. Many experiments validate the utility of frequency-estimation equation and verify the success of the smoother. [ABSTRACT FROM AUTHOR]

Understanding the behavior of crane species is highly important for conservation and management activities. Unfortunately, cranes are facing deleterious threats due to human intervention, i.e., habitat loss and degradation, trapping and illegal hunting. This research's primary goals were to assess the relative quantity of cranes, the prevalence of gastrointestinal parasites, and their endangerment at three separate study sites; River Indus (S1), River Kurram (S2) and Zara Dagger (S3). From 2019 to 2022, four years straight, the line transects surveys approach was used during the migratory season (November to March). In total, 1874 crane bird individuals, comprising 822 common cranes and 1052 demoiselle cranes were observed. The results about habitat preference indicated that demoiselle crane - Grus virgo and common crane Grus grus frequently utilized the River Indus (S1 = 20.238%) and River Kurram (S2 = 22.512%) especially grassland while in Zara Daggar (S3) they heavily utilized the semi-sandy habitat (39.114%). The results of crane diversity analysis revealed that demoiselle crane - G. grus and common crane - G. virgo diversity indices varied among three distinct habitats. In Indus River the higher diversity index was determined for common crane (H' = 0.3524 and D = 1.252) and species richness and uniform distribution for demoiselle crane. In Kurram river, the prevalent diversity index (H' = 0.2363 and D = 1.136), species richness (R = 0.1879 and Mn = 0.1397) and species evenness (E1 = 0.3323 and E2 = 0.2092) was ascertained for common crane than demoiselle crane. Likewise, in Zara Daggar, the higher diversity indices were determined for common crane than demoiselle crane. Three parasite species, i.e., Ascaridia sp. (21.127%), Fasciolopsis sp. (18.309%) and Echinochasmus sp. (15.845%) were especially abundant in faeces of cranes. On the contrarily, the Syngamus trachea (0.352%) was the lowest parasite in the faeces of cranes. The highest parasite relative abundance was detected in Zara Daggar (S3; 120 parasites; 42.253%) and the lowest one in River Indus (S1; 28.169%). This demonstrated that both crane species were inflected by different parasite species. Additionally, people's perspectives suggested that habitat loss and degradation, illegal hunting, and poaching are the main sources of harmful risks to crane species. [ABSTRACT FROM AUTHOR]

This article constructs two adaptive control laws to achieve deformation reduction and attitude tracking for a rotary variable-length crane arm with system parameter uncertainties and asymmetric input–output constraints. Two auxiliary systems are given to deal with the input constraints, an asymmetric-logarithm-barrier Lyapunov function is established for achieving the asymmetric output constrains, and five adaptive laws are constructed to handle system parameter uncertainties. Besides, the control design is based on a partial differential equation model, and the S-curve acceleration and deceleration method is used for regulating the arm extension speed. Both the system stability and uniform ultimate boundedness of the controlled crane arm are analyzed. Simulation results validate the effectiveness of our established control laws. [ABSTRACT FROM AUTHOR]

This article addresses the stabilization control issue for the postcapture tethered system by tethered space robot (TSR). Due to the physical characteristics of space tether by nature, there exists no control inputs on the in-plane/out-of-plane channels of the tether; therefore, the postcapture tethered system is a typical multiinput and multioutput underactuated system. In this article, we propose an energy-based controller for the underactuated system subject to input saturation and the nonnegativity constraint of the tether tension. First, we give the dynamic model of the postcapture tethered system, with consideration of the three attitude angles of the postcapture combination, the in-plane/out-of-plane angles, and the tether length. Second, we list the analysis process of the system’s equilibrium points. Third, we give the detailed controller design process, and verify the stability of the system by invoking the Lyapunov techniques and the extended Barbalat’s lemma. Finally, numerical simulations and comparison results with the hierarchical sliding mode controller are conducted to validate the performance improvement of the developed control strategy. [ABSTRACT FROM AUTHOR]

The berth allocation problem (BAP) is an NP-hard problem in maritime traffic scheduling that significantly influences the operational efficiency of the container terminal. This paper formulates the BAP as a permutation-based combinatorial optimization problem and proposes an improved ant colony system (ACS) algorithm to solve it. The proposed ACS has three main contributions. First, an adaptive heuristic information (AHI) mechanism is proposed to help ACS handle the discrete and real-time difficulties of BAP. Second, to relieve the computational burden, a divide-and-conquer strategy based on variable-range receding horizon control (vRHC) is designed to divide the complete BAP into a set of sub-BAPs. Third, a partial solution memory (PSM) mechanism is proposed to accelerate the ACS convergence process in each receding horizon (i.e., each sub-BAP). The proposed algorithm is termed as adaptive ACS (AACS) with vRHC strategy and PSM mechanism. The performance of the AACS is comprehensively tested on a set of test cases with different scales. Experimental results show that the effectiveness and robustness of AACS are generally better than the compared state-of-the-art algorithms, including the well-performing adaptive evolutionary algorithm and ant colony optimization algorithm. Moreover, comprehensive investigations are conducted to evaluate the influences of the AHI mechanism, the vRHC strategy, and the PSM mechanism on the performance of the AACS algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a combined planning and optimization method that enables a dual-arm robot to lift up and flip heavy plates using crane pulley blocks. The problem is motivated by the low payload of modern collaborative robots. Instead of directly manipulating heavy plates that collaborative robots cannot afford, the paper develops a planner for collaborative robots to operate crane pulley blocks. The planner assumes a target plate is pre-attached to the crane hook. It optimizes dual-arm action sequences and plans the robot’s dual-arm motion that pulls the rope of the crane pulley blocks to lift up the plate. The crane pulley blocks reduce the payload that each robotic arm needs to bear. When the plate is lifted up to a satisfying pose, the planner plans a sliding-pushing motion for one of the robot arms to tumble over the plate while considering force and moment constraints. The article presents the technical details of the planner and several experiments and analysis carried out using a dual-arm robot made by two Universal Robots UR3 arms. The influence of various parameters and optimization goals are investigated and compared in depth. The results show that the proposed planner is flexible and efficient. This paper is motivated by a cleaning process in a factory that produces sewage press machines. The pressboard of sewage press machines could be as heavy as 1000 kg. Human workers need to flip and clean both sides of the board before installing them to the main axis of a sewage machine. Their solution is using a gantry crane. They attach the board to the crane hook using bearing belts, activate the crane to lift up the board. When the board is raised to a satisfying pose, the workers turn the board over by pushing it. Motivated by human workers’ actions, we developed the planner presented in this paper. We assumed crane pulley blocks in the experiments and analysis, but in practice, they may be replaced with electronic ones to improve effort and efficiency. Using the electronic ones will be a sub-problem since there is no need for pulling ropes. The proposed method is expected to help a company’s technicians better judge if they need a heavy payload manipulator or keep their current crane equipment while employing several intelligent collaborative robots to operate them. As a result, it may help to accelerate the upgrade of manufacturing sites while reducing reforming budgets. Note to Practitioners—This paper is motivated by a cleaning process in a factory that produces sewage press machines. The pressboard of sewage press machines could be as heavy as 1000 kg. Human workers need to flip and clean both sides of the board before installing them to the main axis of a sewage machine. Their solution is using a gantry crane. They attach the board to the crane hook using bearing belts, activate the crane to lift up the board. When the board is raised to a satisfying pose, the workers turn the board over by pushing it. Motivated by human workers’ actions, we developed the planner presented in this paper. We assumed crane pulley blocks in the experiments and analysis, but in practice, they may be replaced with electronic ones to improve effort and efficiency. Using the electronic ones will be a sub-problem since there is no need for pulling ropes. The proposed method is expected to help a company’s technicians better judge if they need a heavy payload manipulator or keep their current crane equipment while employing several intelligent collaborative robots to operate them. As a result, it may help to accelerate the upgrade of manufacturing sites while reducing reforming budgets. [ABSTRACT FROM AUTHOR]

In this article, we design a novel saturated proportional-derivative (PD) with sliding-mode control (SMC) method or saturated PD-SMC in short for 4-DOF tower crane systems under uncertain dynamics, external disturbances, as well as saturated control input constraints. The designed control method is model free, which can achieve accurate positioning and rapid swing suppression and elimination using only jib/trolly position/velocity and payload swing feedback with limited control inputs. Different from the existing control methods, the designed control method takes the advantages of simple structure and being easily realized in practical applications of the PD control, strong robustness of the SMC method with respect to model uncertainties and external disturbances, avoiding the requirements of accurate model knowledge associated with the SMC method, as well as rapid payload swing reduction of the swing suppression control. The stability of the controlled system is ensured by rigorous Lyapunov-based analysis. To the best of our knowledge, this is the first model-free control method without any linearization operations for tower crane systems with uncertain dynamics, external disturbances, and saturated control input constraints. Several experimental results are given to validate the superior control performance and strong robustness of the designed control method. [ABSTRACT FROM AUTHOR]

This article demonstrates the realization of angle tracking and deformation suppression by developing two boundary controllers for a flexible variable-length rotary crane arm with extraneous disturbances and asymmetric input–output constraints. The dynamic model description of this kind of crane arm system is several partial differential equations integrated into few ordinary differential equations. The S-curve acceleration and deceleration scheme is utilized to adjust the elongation rate of the arm. A kind of novel observer is put forward to tackle unknown extraneous disturbances. Auxiliary systems and barrier Lyapunov functions are introduced to meet the asymmetric input–output constraints. With the help of Lyapunov’s theory, the global exponential stability and uniform boundedness are analyzed. The numerical simulations are finally provided to illuminate its availability of the designed control schemes. [ABSTRACT FROM AUTHOR]

The inspection of bridges is an essential activity to maintain the viability and safe operation of these structures. The inspection process shall be carried out by visual means using special equipment called bridge inspector. The equipment is similar in design to mobile crane installations – crane lorries, with the rotating part in the form of a boom at the end of which is the work platform for personnel and tools. The structure of the arm has the shape of a lattice girder or beams with closed section (caisson); regardless of the type of construction there is at least one telescopable section. During use, the installation is positioned on the superstructure of the bridges, supporting it by means of folding or telescopic outriggers.

Output feedback control without using velocities is an effective way of dealing with problems caused by unmeasurable velocities and noise magnification by numerical difference, which are practical issues associated with crane control. This article proposes a new adaptive dynamic output feedback control approach for double-pendulum ship-mounted cranes in the presence of unknown parameters (e.g., cargo masses). The problems caused by the unknown masses are addressed through a new adaptive gravitational compensation law. Also, the input constraints are tackled by introducing bounded functions. Specifically, to handle the complicated disturbances caused by ship motions, new state variables are constructed to transform the dynamic model. Then, Lyapunov-based stability analysis is proceeded to design the controller and the adaptive law. To the best of authors’ knowledge, this is the first control method proposed for double-pendulum ship-mounted crane systems without using velocity signals, which can simultaneously eliminate steady errors, suppress unexpected cargo swing, achieve accurate gravitational compensation, and satisfy input constraints. The closed-loop system’s state variables asymptotically converge to the equilibrium point, which is rigorously proven. A series of experiments are implemented on a hardware testbed, which further illustrate the satisfactory performance of the proposed method. [ABSTRACT FROM AUTHOR]

With large load capacity and flexible payload attitude adjustment capability, dual rotary cranes (DRCs) play crucial roles in infrastructure construction with heavy hoisting demands. However, as a kind of collaborative control systems, DRCs have complex collaborative constraints, and large-scale payloads cannot be simply regarded as mass points; moreover, due to the lack of control inputs, some state variables can only be indirectly controlled through complicated nonlinear coupling relationships, which make the controller design and corresponding analysis particularly difficult. Additionally, in practical applications of DRCs, many factors (such as boom motion overshoots, inaccurate gravity (torque) compensation, etc.) are prone to result in unexpected steady errors, large payload swing, and boom collisions, which may result in inaccurate assembly, and even lead to safety accidents. To this end, this article proposes an adaptive nonlinear proportional-integral-derivative-like collaborative control method for DRCs, which can realize accurate and efficient antiswing hoisting. To our knowledge, this is the first controller embedded with integral terms without any linearization during the controller design or stability analysis, which can effectively reduce steady errors, and keep boom motions within safety ranges by adaptive gravity (torque) compensation and elaborately designed constraint terms. Theoretically, the closed-loop stability and convergence are proven through strict mathematical analysis by using Lyapunov techniques and LaSalle’s invariance theorem. Finally, several groups of hardware experimental results are presented for effectiveness and robustness verification. [ABSTRACT FROM AUTHOR]

To solve the problem of storage space allocation for both inbound and outbound containers and twin automated stacking cranes scheduling in the automated container terminals, a new repositioning strategy is designed and a cooperative optimization model is established. The model considers the constraints of safety distance and handshake area capacity. The objective of the model is to minimize the makespan of all storage requests and the total rehandling time during the retrieval process, which is calculated according to the priority of inbound and outbound containers defined by the early retrieval and early loading rule respectively. A variable neighborhood search based hybrid genetic algorithm is designed to solve the model. Numerical experiments show that the sum of the makespan of all storage requests and the total rehandling time during the retrieval process is reduced by approximately 10% compared to the traditional repositioning strategy by optimizing the sequence of container repositioning from the handshake area to the seaside or landside designated storage space. The research is beneficial to improve the operation efficiency of automated container terminal yards. [ABSTRACT FROM AUTHOR]

Energy consumption is expected to be reduced while maintaining high productivity for container handling. This paper investigates a new energy-efficient scheduling problem of automated container terminals, in which quay cranes (QCs) and lift automated guided vehicles (AGVs) cooperate to handle inbound and outbound containers. In our scheduling problem, operation times and task sequences are both to be determined. The underlying optimization problem is mixed-integer nonlinear programming (MINLP). To deal with its computational intractability, a customized and efficient genetic algorithm (GA) is developed to solve the studied MINLP problem, and lexicographic and weighted-sum strategies are further considered. An $\epsilon $ -constraint algorithm is also developed to analyze the Pareto frontiers. Comprehensive experiments are tested on a container handling benchmark system, and the results show the effectiveness of the proposed lexicographic GA, compared to results obtained with two commonly-used metaheuristics, a commercial MINLP solver, and two state-of-the-art methods. [ABSTRACT FROM AUTHOR]

In the field of modern industrial engineering, many mechanical systems are underactuated, exhibiting strong nonlinear characteristics and high flexibility. However, the lack of control inputs brings about many difficulties for controller design and stability/convergence analysis., some unavoidable practical issues, e.g., plant uncertainties and actuator deadzones, make the control of underactuated systems even more challenging. Hence, with the aid of elaborately constructed finite-time convergent surfaces, this article provides the first solution to address the control problem for a class of multi-input-multi-output (MIMO) underactuated systems subject to plant uncertainties and actuator deadzones. Specifically, this article overcomes the main obstacle in sliding-mode surface analysis for MIMO underactuated systems, that is, by the presented analysis method, the asymptotic stability of the system equilibrium point is strictly proven based on the composite surfaces. In addition, the unknown parts of the actuated/unactuated dynamic equations and actuator deadzones can be simultaneously handled, which is important for real applications. Furthermore, we apply the proposed method to two kinds of typical underactuated systems, that is: 1) tower cranes and 2) double-pendulum cranes, and implement a series of hardware experiments to verify its effectiveness and robustness. [ABSTRACT FROM AUTHOR]

Container terminal capacity, as an important indicator of container terminal competitiveness, has become a primary concern of port managers, whereas container flows, which are supported by quay cranes, yard cranes, and automated guided vehicles, have a substantial influence on container terminal capacity. Container flows are analyzed in this article to estimate the performance of an automated container terminal considering traffic congestion, unbalanced task assignment, container batch arrival, and different berth and yard layouts. The operating system is formulated as a closed-queuing network with four stations. Theoretical analysis and the solution method are adopted to determine system capacity. The resource allocation and system design, specifically the number of vehicles, berth and yard layouts, and task assignment strategy, are optimized. Numerical experiments are conducted to provide management insights into port capacity planning, resource optimization, and layout design. Note to Practitioners—The construction of an automated container terminal (ACT) requires a sizable investment. Analyzing the performance of the container terminal with different configurations in the planning stage, which is before the construction of ports, is very important. Thus, planners can select better resource configurations. Generally, simulation is an intuitive way to estimate performance. However, formulating and running the simulation model with different configurations is time consuming. An analytic model for estimating the performance of an ACT is developed to reduce computational time in this article. [ABSTRACT FROM AUTHOR]

In this study, we propose an efficient optimization algorithm that is a hybrid of the iterated greedy and simulated annealing algorithms (hereinafter, referred to as IGSA) to solve the flexible job shop scheduling problem with crane transportation processes (CFJSP). Two objectives are simultaneously considered, namely, the minimization of the maximum completion time and the energy consumptions during machine processing and crane transportation. Different from the methods in the literature, crane lift operations have been investigated for the first time to consider the processing time and energy consumptions involved during the crane lift process. The IGSA algorithm is then developed to solve the CFJSPs considered. In the proposed IGSA algorithm, first, each solution is represented by a 2-D vector, where one vector represents the scheduling sequence and the other vector shows the assignment of machines. Subsequently, an improved construction heuristic considering the problem features is proposed, which can decrease the number of replicated insertion positions for the destruction operations. Furthermore, to balance the exploration abilities and time complexity of the proposed algorithm, a problem-specific exploration heuristic is developed. Finally, a set of randomly generated instances based on realistic industrial processes is tested. Through comprehensive computational comparisons and statistical analyses, the highly effective performance of the proposed algorithm is favorably compared against several efficient algorithms. Note to Practitioners—The flexible job shop scheduling problem (FJSP) can be extended and applied to many types of practical manufacturing processes. Many realistic production processes should consider the transportation procedures, especially for the limited crane resources and energy consumptions during the transportation operations. This study models a realistic production process as an FJSP with crane transportation, wherein two objectives, namely, the makespan and energy consumptions, are to be simultaneously minimized. This study first considers the height of the processing machines, and therefore, the crane lift operations and lift energy consumptions are investigated. A hybrid iterated greedy algorithm is proposed for solving the problem considered, and several problem-specific heuristics are embedded to balance the exploration and exploitation abilities of the proposed algorithm. In addition, the proposed algorithm can be generalized to solve other types of scheduling problems with crane transportations. [ABSTRACT FROM AUTHOR]

Underactuated dual boom crane (DBC) systems exhibit complicated nonlinearity and strong coupling due to the lack of independent actuators. Moreover, plant parameters may change in different transportation tasks and are difficult to be measured accurately, which leads to inaccurate gravity (torque) compensation and further brings positioning errors. Hence, most existing controllers based on exact model knowledge cannot ensure satisfactory control performance any longer. In order to handle the above issues, this article designs an adaptive sliding mode tracking controller for DBC systems based on the original complicated nonlinear dynamics without any linearization/simplification operations, which is the first one to effectively achieve both anti-swing and trajectory tracking control in the presence of parametric uncertainties. Not only can the state variables converge to the proposed sliding surface within finite time but also payload swing angles can be completely eliminated; consequently, the working efficiency and operation safety are further guaranteed. The corresponding stability and convergence for the equilibrium point of the closed-loop system are proven by rigorous mathematical analysis based on the Lyapunov techniques and Barbalat’s lemma. Hardware experimental results demonstrate the effectiveness and robustness of the presented controller. [ABSTRACT FROM AUTHOR]

Cultural ecosystem services (CES) are important spatial elements providing humans with recreational, esthetic, spiritual, and other benefits. Yet, because of their immaterial, subjective, qualitative, and unmeasurable nature, this means that scientists, decision-makers, and general public often find their value difficult to grasp. We enrich the CES approach with theoretical insights from humanist geography, where we frame CES as arising from perpetual interactions between humans and their environment. Places are formed through various processes, both organic and planned, which endow people with unique identities, experiences, capabilities, knowledge, and skills. We use the rural wetland area of Lake Hornborga, Sweden, with its complex history of restoration phases, to explore the profound interrelations between environmental spaces and cultural practices expressed in the everyday activities of learning, playing, creating, caring, producing, and consuming. The data was collected through qualitative methods, including interviews, observations, and a focused group interview, in order to capture these unique senses and experiences. Thefindings outline CES as key drivers behind the formation of place, rather than mere labels for inventorying benefits people receive from nature. The presence of the iconic migratory crane is especially conducive to a positive sense of place and the practice of various activities, including tourism, around the wetland. We frame the implications for planning and future research of our findings within a context of ethics. [ABSTRACT FROM AUTHOR]

We present a dynamical modeling of integrated (end-to-end) container terminal operations using finite state machine (FSM) framework where each state machine is represented by a discrete-event system (DES) formulation. The hybrid model incorporates the operations of quay cranes (QC), internal trucks (IT), and yard cranes (YC) and also the selection of storage positions in container yard (CY) and vessel bays. The QC and YC are connected by the IT in our models. As opposed to the commonly adapted modeling in container terminal operations, in which the entire information/inputs to the systems are known for a defined planning horizon, in this research we use real-time trucks, crane, and container storage operations information, which are always updated as the time evolves. The dynamical model shows that the predicted state variables closely follow the actual field data from a container terminal in Tanjung Priuk, Jakarta, Indonesia. Subsequently, using the integrated container terminal hybrid model, we proposed a model predictive algorithm (MPA) to obtain the near-optimal solution of the integrated terminal operations problem, namely the simultaneous allocation and scheduling of QC, IT, and YC, as well as selecting the storage location for the inbound and outbound containers in the CY and vessel. The numerical experiment based on the extensive Monte Carlo simulation and real dataset show that the MPA outperforms by 3-6% both of the policies currently implemented by the terminal operator and the state-of-the-art method from the current literature. [ABSTRACT FROM AUTHOR]

According to the requirements of the “Rules for industrial safety of cranes”, anti-theft devices must ensure that cranes under the influence of wind force stop at any point on the track, including at the junction of rails connected by side strips. Various types of anti-theft crane devices recommended for use have a number of disadvantages. Thus, the supply of anti-theft crane devices made in the form of lever grips interacting with the rail head with mechanisms for disengaging and converging grippers with electromechanical, electromagnetic, hydraulic or pneumatic drives complicates their design. There are also known anti-theft crane devices, in which the stopping of cranes on a rail track is carried out by a locking eccentric interacting with the surface of the rail head. The reliability of such devices is insufficient, since, due to the constant force of the spring, the adhesion force of the eccentric to the rail does not depend on the changing wind force. The paper proposes the basics of calculating the anti-theft crane device, representing the kinematic connection of two mechanisms – eccentric and thick-borne, which allows to solve a number of the above problems.

To solve the problems of inaccurate quality inspection and poor safety maintenance of traditional overhead cranes, this study has developed a prediction system for overhead cranes based on digital twin technology. First, interworking of the data flow between the control port of the overhead crane and the digital twin system is realized. Then, finite element technology is exploited to calculate the stress of the crane bridge, thereby performing stress rendering of the digital twin system. Next, the life of bridge cranes is predicted by the stress and strain of their main girders. Finally, synchronous overhead-crane communication combines the virtual twin system and the actual control system of the crane. The study results provide a reference for developing crane software based on digital twins.