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This article presents a novel proportional-integral approximation-free control (PIAFC) for nonlinear robotic systems with unknown Coriolis and gravity dynamics. One key merit is to transform the original motion tracking problem into an alternative system stabilization problem by introducing prescribed performance functions (PPFs) and the associated error transformation. Another idea is to develop a proportional-integral error compensation mechanism and incorporate it into the approximation-free control synthesis, such that the tracking error converges to zero in the steady-state. In this framework, only the inertia matrix is required and the computationally demanding function approximators are avoided, while the unknown Coriolis and gravity dynamics can be effectively handled. Moreover, the transient tracking error can be retained within a preset boundary. Stability analysis of the closed-loop control system is carried out in terms of the Lyapunov theorem. Finally, extensive comparative simulations and experimental results on a realistic SCARA robotic test-rig illustrate the superiority of the suggested method over several other methods. [ABSTRACT FROM AUTHOR]

Fault-tolerant control policies that automatically restart programable logic controller-based automated production system during fault recovery can increase system availability. This article provides a proof of concept that such policies can be synthesized with deep reinforcement learning. The authors specifically focus on systems with multiple end-effectors that are actuated in only one or two axes, commonly used for assembly and logistics tasks. Due to the large number of actuators in multi-end-effector systems and the limited possibilities to track workpieces in a single coordinate system, these systems are especially challenging to learn. This article demonstrates that a hierarchical multi-agent deep reinforcement learning approach together with a separate coordinate prediction module per agent can overcome these challenges. The evaluation of the suggested approach on the simulation of a small laboratory demonstrator shows that it is capable of restarting the system and completing open tasks as part of fault recovery. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economic Research & Business Administration is the property of Al-Farabi Kazakh National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In India, we get some news like a child has struck up in a bore well, and it takes more than 16 to 24 hours save a child. Borewell accidents are common because of uncovered openings of bore well at farms and home surroundings. In some cases, it is too difficult to save the child from the bore well. Dragging the child out from the narrow hole of bore well is not easy. It is difficult to protect children who fall into a bore well by using exhausting methods, because a child who falls into a bore hole has no gaps between the walls of the bore well, so he is stuck there. That's why he's so screwed up but all the extinguishing methods were designed such that the robotic could hold it up or send a balloon down the pillow to support it. But what they have forgotten is that there is no gap in the support balloons or robotic arm to catch the child. In this study paper, we analyze the problems associated with the bore well rescue operations. We also present details of various existing robot systems available in use. Along with this, we discuss how robotics and automation could be a possible solution for this entire problem. In this context, we discuss the features of such a robotic system and also give suggestions on various humankind robotic systems that can be designed and implemented. [ABSTRACT FROM AUTHOR]

Modular and reconfigurable manipulators have gained popularity especially in the service sector, where the use of customized configurations has increased. Adaptable modular designs have come into advances in achieving required configuration of a robotic manipulator. As reported in literature, various designs of the modules mainly with conventional configurations are presented and a few are reported with unconventional adjustments. To cater the non-repetitive applications, this paper presents an optimal architectural design for unconventional parameters for customized reconfigurability. This lighter and easier-to-connect version is also applicable to n-DoF and unconventional robotic parameters. Architecture Prominent Sectioning (APS) strategy is proposed which assumes an architecture as a set of point masses and optimally relocate components with respect to the minimization of the joint torques. Modules are considered to be 3D printable using poly-lactic acid (PLA), a thermoplastic material, and thus light in weight. The new modular architecture design is validated through the assemblage of conventional/unconventional configurations using two types of modules namely Heavy (H) and Light (L). Along with that, worst torque analyses for the different configurations have been done in order to provide a strategy for assembly combinations. A comparative study is presented based upon the payload-to-weight ratio, involving other reported architectures. [ABSTRACT FROM AUTHOR]

Harmonic drives are widely used devices in robotic and space applications. As for any device transmitting motion, its mechanical efficiency is one of the main concerns for the designer. In this paper, it is proposed a new model to estimate this significant feature. The proposed approach makes use of the kinematic correspondence between the harmonic drive and an epicyclic gear train. Although the authors introduced simple approximations to describe the complex tribological phenomena during harmonic drive teeth meshing, the numerical results match the trend of experimental evidence. In particular, assuming the harmonic drive working at the rated torque, the plots of the mechanical efficiency versus different parameters such as temperature and angular speed have been simulated. [ABSTRACT FROM AUTHOR]

Most existing robust adaptive control designs for robotic systems only address the issue of modelling uncertainties and external disturbances. In this paper, we present a control method exhibits several salient features, such as robustness against modelling uncertainties, adaptation to unknown system parameters, tolerance to actuation failures, and obedience to motion constraints. It also ensures prescribed performance bounded (PPB) for any initial conditions, removing the shortcoming of the current PPB method. The proposed control scheme consists of two units: supervisory control and prescribed performance bounded (PPB) control. The role of the former is to drive the tracking error from any initial condition within the domain of interest to a residual set, so that the PPB control can be activated to ensure pre-given performance specifications. A soft connector is introduced to maintain continuous control action during the switching. Theoretical analysis and simulation verification confirm the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

In this work, the trajectory tracking control scheme is the framework of optimal control and robust integral of the sign of the error (RISE); sliding mode control technique for an uncertain/disturbed nonlinear robot manipulator without holonomic constraint force is presented. The sliding variable combining with RISE enables to deal with external disturbance and reduced the order of closed systems. The adaptive reinforcement learning technique is proposed by tuning simultaneously the actor–critic network to approximate the control policy and the cost function, respectively. The convergence of weight as well as tracking control problem was determined by theoretical analysis. Finally, the numerical example is investigated to validate the effectiveness of proposed control scheme. [ABSTRACT FROM AUTHOR]

This article presents a state-of-the-art survey on the robotic systems, sensors, actuators, and collaborative strategies for physical human–robot collaboration (pHRC). This article starts with an overview of some robotic systems with cutting-edge technologies (sensors and actuators) suitable for pHRC operations and the intelligent assist devices employed in pHRC. Sensors being among the essential components to establish communication between a human and a robotic system are surveyed. The sensor supplies the signal needed to drive the robotic actuators. The survey reveals that the design of new generation collaborative robots and other intelligent robotic systems has paved the way for sophisticated learning techniques and control algorithms to be deployed in pHRC. Furthermore, it revealed the relevant components needed to be considered for effective pHRC to be accomplished. Finally, a discussion of the major advances is made, some research directions, and future challenges are presented. [ABSTRACT FROM AUTHOR]

The analysis of robotic systems (e.g. landers and rovers) involved in sampling operations on planetary bodies is crucial to ensure mission success, since those operations generate forces that could affect the stability of the robotic system. This paper presents MISTRAL (MultIdisciplinary deSign Tool for Robotic sAmpLing), a novel tool conceived for trade space exploration during early conceptual and preliminary design phases, where a rapid and broad evaluation is required for a very high number of configurations and boundary conditions. The tool rapidly determines the preliminary design envelope of a sampling apparatus to guarantee the stability condition of the whole robotic system. The tool implements a three-dimensional analytical model capable to reproduce several scenarios, being able to accept various input parameters, including the physical and geometrical characteristics of the robotic system, the properties related to the environment and the characteristics related to the sampling system. This feature can be exploited to infer multidisciplinary high-level requirements concerning several other elements of the investigated system, such as robotic arms and footpads. The presented research focuses on the application of MISTRAL to landers. The structure of the tool and the analysis model are presented. Results from the application of the tool to real mission data from NASA's Phoenix Mars lander are included. Moreover, the tool was adopted for the definition of the high-level requirements of the lander for a potential future mission to the surface of Saturn's moon Enceladus, currently under investigation at NASA Jet Propulsion Laboratory. This case study was included to demonstrate the tool's capabilities. MISTRAL represents a comprehensive, versatile, and powerful tool providing guidelines for cognizant decisions in the early and most crucial stages of the design of robotic systems involved in sampling operations on planetary bodies. [ABSTRACT FROM AUTHOR]

BACKGROUND: Human-robot interaction (HRI) is becoming a current research field for providing granular real-time applications and services through physical observation. Robotic systems are designed to handle the roles of humans and assist them through intrinsic sensing and commutative interactions. These systems handle inputs from multiple sources, process them, and deliver reliable responses to the users without delay. Input analysis and processing is the prime concern for the robotic systems to understand and resolve the queries of the users. OBJECTIVES: In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection. RESULTS: The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs. CONCLUSION: The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses. [ABSTRACT FROM AUTHOR]

Type annotations connect variables to domain-specific types. They enable the power of type checking and can detect faults early. In practice, type annotations have a reputation of being burdensome to developers. We lack, however, an empirical understanding of how and why they are burdensome. Hence, we seek to measure the baseline accuracy and speed for developers making type annotations to previously unseen code. We also study the impact of one or more type suggestions. We conduct an empirical study of 97 developers using 20 randomly selected code artifacts from the robotics domain containing physical unit types. We find that subjects select the correct physical type with just 51% accuracy, and a single correct annotation takes about 2 minutes on average. Showing subjects a single suggestion has a strong and significant impact on accuracy both when correct and incorrect, while showing three suggestions retains the significant benefits without the negative effects. We also find that suggestions do not come with a time penalty. We require subjects to explain their annotation choices, and we qualitatively analyze their explanations. We find that identifier names and reasoning about code operations are the primary clues for selecting a type. We also examine two state-of-the-art automated type annotation systems and find opportunities for their improvement. [ABSTRACT FROM AUTHOR]

Robotic systems are believed to be the elements of conceptual inflexion in the conduct of future military conflicts. The progress made by the military industry in the field of robotics science and engineering, coupled with the practical results obtained in theatres of operations, have led us to the hypothesis of a paradigm shift regarding the role that autonomous systems will have not only in designing military operations but also in approaching the ethics of military action.

Bu çalışmada çok katlı bina, köprü vb. yapıların anlık sağlık durumlarının takibinde kullanılmak amacıyla uzaktan algılama ve temassız ölçüm tekniklerine dayalı, programlanabilir robotik bir tarayıcı sistem geliştirilmesi amaçlanmaktadır. Önerilen sistem, ölçüm tekniği olarak lazer Doppler interferometri kullanılacağı için test edilen yapılar üzerine herhangi bir sensör yerleştirilmesine ihtiyaç duyulmadan her türlü yapıya kolaylıkla uygulanabilir. Yüksek hassasiyet ve çözünürlükte ölçüm alınabilmesi amacıyla, yüksek örnekleme frekansına sahip bir lazer Doppler titreşimölçer, yatay ve düşey eksenlerde bağımsız hareket edebilen motorize bir platform üzerine yerleştirilmiştir. Platforma eklenen kameralı görüntüleme sistemleri, geliştirilen kontrol algoritmaları ve arayüz yardımıyla, kullanıcının test ve ölçümler ile ilgili çeşitli parametreleri kişisel bilgisayarı üzerinden kontrol edebileceği bütünleşik bir yapı oluşturulmuştur. Geliştirilen tarayıcı sistem laboratuvarda kurulan küçük ölçekli çok katlı bina modelleri üzerinde test edilerek yapıların dinamik özelliklerinin yüksek doğruluk ve çözünürlükte çıkarılabildiği gösterilmiştir. Önerilen sistem birden fazla yapının düzenli bir şekilde taranmasına imkan sağlayacak şekilde programlanabilmektedir. Elde edilen titreşim verisinin analizi sonucunda yapının doğal frekanslarının, sönümleme oranlarının ve mod şekillerinin hızlı ve etkin bir şekilde hesaplanabildiği görülmüştür.

The article presents the main results of the analysis of the agriculture automation level in Russia and in the world. The results of the research of the foreign market, structures and compositions of foreign-made unmanned mobile energy vehicles are presented. The main direction of development of foreign companies is the creation of new models of navigation and orientation equipment for agricultural machinery aimed to the implementation of autonomous moving and mission equipment control. Technics automatization is possible due to refitting of already existing samples with specialized attachments. According to this analysis, foreign agricultural machinery is far ahead of domestic manufacturers for the production of crew-unmanned facilities of mechanization for the agricultural sector, and the material intensity of the existing agricultural production in Russia is 3-4 times higher than that of foreign countries. The need for this kind of analysis is explained by the result of a comparison labor productivity: this index in Russia's agriculture is by 2.4 times lower than European one and 3.5 times lower than that of the USA. The Russian agriculture development retard can be eliminate through the use of modern achievements in the field of robotic systems for special purposes. The authors proved the possibility of double use of technologies because of similarity of schemes and structure of robotic systems for the solution of specialized tasks of both directions. The unmanned mobile energy vehicles can be used at sequential and parallel autonomous driving.

Nowadays, simulators are being used more and more during the development of robotic systems due to the efficiency of the development and testing processes of such applications. Undoubtedly, these simulators save time, resources and costs, as well as enable ease of demonstrations of the system. Specifically, tools like the open source Robotic Operating System (ROS) and Gazebo have gained popularity in building models of robotic systems. ROS is extensively used in robotics due to the pros of hardware abstraction and code reuse. The Gazebo platform is used for visualisation because of its high compatibility with ROS. In this paper, ROS and Gazebo have been integrated to build an interface for the visualisation of the Katana Arm manipulator. [ABSTRACT FROM AUTHOR]

Control of the force exerted on an object is important for boosting system performance in robotics manipulators. Any undesired applied force may leave remarkable effects on the system, with the potential to damage the object. In addition, measuring external force is another challenge associated with such cases. Proposing an appropriate force estimation algorithm is a solution to overcome this deficiency. In this research, a control strategy is proposed to control the external force applied on the n-dof robotics. To eliminate force measurement in the controller, a force estimation strategy based on a disturbance observer is employed. Subsequently, a sliding-mode based control is implemented to cope with the force estimation error. The closed-loop stability of the system in the presence of estimated force is analytically considered. The proposed algorithm was implemented on piezoelectric actuators as the experimental setup. The experimental results confirm that by employing the proposed control scheme, precise force control is achievable. The force estimation algorithm can also suitably estimate external force. [ABSTRACT FROM AUTHOR]

This paper considers a general approach to fault diagnosis using a generalized Hamiltonian system representation. It can be considered that, in general, nonlinear systems still represent a problem in fault diagnosis because there are results only for a specific class of them. Therefore, fault diagnosis remains a challenging research area despite the maturity of some of the available results. In this work, a type of nonlinear system that admits a generalized Hamiltonian representation is considered; in practice, there are many systems that have this kind of representation. Thereupon, an approach for fault detection and isolation based on the Hamiltonian representation is proposed. First, following the classic approach, the original system is decoupled in different subsystems so that each subsystem is sensitive to one particular fault. Then, taking advantage of the structure, a simple way to design the residuals is presented. Finally, the proposed scheme is validated at the two-degree of freedom (DOF) helicopter of Quanser®, where the presence of faults in sensors and actuators were considered. The results show the efficacy of the proposed scheme. [ABSTRACT FROM AUTHOR]

The industrial zones are increasingly invaded by groups of mobile robots that are the most capable to perform complex tasks by collaborating and cooperating together. The operation of a mobile robot within a dynamic and high-risk environment with strong interaction between robot-robot and human-robot is of a certain complexity of control and safety. Such type of systems requires a safety and hazard investigation to verify if it is able to operate under certain operating conditions, while still ensuring the control and collaboration between mobile robots and human. This paper presents an approach that combines aspects of System-Theoretic Process Analysis (STPA) and Bowtie for safety assessment purposes. The approach we propose is used for a case related to multi-robot systems considering the coordinating, cooperating and collaborating aspects. At first, a risk identification study is done using STPA to extract a set of risk scenarios related to different types of hierarchical coordination architectures in addition to their factors. Afterward, an evaluation of the obtained scenarios is performed by the Bowtie method. The aim of our study is to better compare different control approaches of a multi-agent system. The combination offers detailed hazard identification. It further provides a classification of risks which helps to improve STPA outcomes thus facilitate decision-making over the suitable approach. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we study the effects of mechanical compliance on safety in physical human-robot interaction (pHRI). More specifically, we compare the effect of joint compliance and link compliance on the impact force assuming a contact occurred between a robot and a human head. We first establish pHRI system models that are composed of robot dynamics, an impact contact model, and head dynamics. These models are validated by Simscape simulation. By comparing impact results with a robotic arm made of a compliant link (CL) and compliant joint (CJ), we conclude that the CL design produces a smaller maximum impact force given the same lateral stiffness as well as other physical and geometric parameters. Furthermore, we compare the variable stiffness joint (VSJ) with the variable stiffness link (VSL) for various actuation parameters and design parameters. While decreasing stiffness of CJs cannot effectively reduce the maximum impact force, CL design is more effective in reducing impact force by varying the link stiffness. We conclude that the CL design potentially outperforms the CJ design in addressing safety in pHRI and can be used as a promising alternative solution to address the safety constraints in pHRI. [ABSTRACT FROM AUTHOR]

In this paper, we propose an alternative, simple, yet efficient estimation method to handle unknown dynamics and external disturbances for motion control of robotic systems. An unknown system dynamics estimator (USDE) is first proposed by introducing filter operations and simple algebraic calculations, where the external disturbances and unknown Coriolis/gravity dynamics can be estimated simultaneously. In the specific case where only the external disturbance is unknown, a further modified unknown disturbance estimator (MUDE) is introduced. These proposed USDE and MUDE can be easily implemented and their parameter tuning is straightforward compared with the nonlinear disturbance observer that requires calculation of the inverse of the inertia matrix. The acceleration signal of robotic joints is not used in the design of estimators. Moreover, we also show that the proposed estimators can be incorporated into the design of composite controllers to achieve satisfactory motion tracking response. The closed-loop control system stability and convergence of both the tracking error and estimation error are all guaranteed. Finally, the effectiveness of the two proposed methods is validated by using simulations and experiments based on a SCARA robot test-rig. [ABSTRACT FROM AUTHOR]

Non‐linear model predictive control requires the use of efficient solutions and strategies for its implementation in fast/real‐time systems. A popular approach for this is the real‐time iteration scheme, which uses a shifting strategy, namely the initial value embedding, that shifts the solution from one sampling time to the next. However, this strategy together with other efficient strategies such as move blocking, present a recursive feasibility problem. This study proposes a novel modified shifting strategy which preserve both recursive feasibility and stability properties, as well as achieves a significant reduction in the computational burden associated with the optimisation. The proposed approach is validated through a simulation of an inverted pendulum where it clearly outperforms other standard solutions in terms of performance and recursive feasibility properties. Additionally, the approach was tested on two computing platforms: a laptop with an i7 processor and a Beaglebone Blue Linux‐based computer for robotic systems, where computational gains compared to existing approaches are shown to be as high as 100 times faster. [ABSTRACT FROM AUTHOR]

This paper introduces the equations of motion of modular 2D snake robots moving in vertical plane employing Series Elastic Actuators (SEAs). The kinematics of such 2D modular snake robot is presented in an efficient matrix form and Euler-Lagrange equations are constructed to model the robot. Moreover, using a spring-damper contact model, external contact forces, necessary for modeling pedal wave motion (undulation in the vertical plane) are taken into account, which unlike existing methods can be used to model the effect of multiple contact points. Using such a contact model, pedal wave motion of the robot is simulated and the torque signal measured by the elastic element from the simulation and experimentation are used to show the validity of the model. Moreover, pedal wave locomotion of such robot on uneven terrain is also modeled and an adaptive controller based on torque feedback in gait parameter's space with optimized control gain is proposed. The simulation and experimentation results showed the efficacy of the proposed controller as the robot successfully climbed over a stair-type obstacle without any prior knowledge about its location with at least 24.8% higher speed compared with non-adaptive motion. [ABSTRACT FROM AUTHOR]

Robotic systems generally employ resource description framework (RDF) to express heterogeneous data coming from different sensors. With the access of more terminals, the RDF volume in robotic systems is becoming larger and larger, posing new significant challenges to the storage and retrieval of RDF data. This paper proposes a star-based partitioning and index algorithm for RDF data of robotic systems. First, we construct a two-hop star structure by MapReduce and HDFS, and get a coarsened weighted graph. Next, a balance partitioning algorithm is used to divide the weighted graph. After partitioning, a compressed and linked S-tree index is proposed to improve the query efficiency. Experiments are executed on benchmark and real data sets to evaluate the studied partitioning and index methods. Results show that our partitioning method has a lower replication ratio, and a better load balancing performance, so our method is efficient for star query and competitive in complex query.

This paper surveys the methods used for visual servoing of robotic systems, where the main focus is on mobile robot systems. The three main areas of research include the Direct Visual Servoing, stereo vision systems, and artificial intelligence in visual servoing. The standard methods such as Image-Based Visual Servoing (IBVS) and Position-Based Visual Servoing (PBVS) are analyzed and compared with the new method named Direct Visual Servoing (DVS). DVS methods have better accuracy, compared to IBVS and PBVS, but have limited convergence area. Because of their high accuracy, DVS methods are suitable for integration into hybrid systems. Furthermore, the use of the stereo systems for visual servoing is comprehensively analyzed. The main contribution of the stereo system is the accurate depth estimation, which is critical for many visual servoing tasks. The use of artificial intelligence (AI) in visual servoing purposes has also gained popularity over the years. AI techniques give visual servoing controllers the ability to learn by using predefined examples or empirical knowledge. The learning ability is crucial for the implementation of robotic systems in a real-world dynamic manufacturing environment. Also, we analyzed the use of visual odometry in combination with a visual servoing controller for creating more robust and reliable positioning system.

It is a great challenge to find an optimal one-wafer cyclic schedule for a single-arm multicluster tool that is widely adopted in semiconductor fabrication. Aiming to tackle this significant problem, an optimal scheduling strategy is determined first for each individual tool under the condition that the bottleneck individual tool is transport-bound. Then, by developing a Petri net model with robot waiting being explicitly described to reveal the properties of the entire system, this paper shows that to schedule such a tool optimally is to allocate the robot waiting time properly. Then, this paper presents the necessary and sufficient conditions for the existence of an optimal one-wafer cyclic schedule. Thereafter, an efficient algorithm is developed to check the given conditions and find such a schedule efficiently if existing. Finally, two industrial examples are used to verify that the proposed method is applicable and effective.

Technological breakthroughs in recent years have led to a revolution in fields such as Machine Vision and Search and Rescue Robotics (SAR), thanks to the application and development of new and improved neural networks to vision models together with modern optical sensors that incorporate thermal cameras, capable of capturing data in post-disaster environments (PDE) with rustic conditions (low luminosity, suspended particles, obstructive materials). Due to the high risk posed by PDE because of the potential collapse of structures, electrical hazards, gas leakage, etc., primary intervention tasks such as victim identification are carried out by robotic teams, provided with specific sensors such as thermal, RGB cameras, and laser. The application of Convolutional Neural Networks (CNN) to computer vision is a breakthrough for detection algorithms. Conventional methods for victim identification in these environments use RGB image processing or trained dogs, but detection with RGB images is inefficient in the absence of light or presence of debris; on the other hand, developments with thermal images are limited to the field of surveillance. This paper’s main contribution focuses on implementing a novel automatic method based on thermal image processing and CNN for victim identification in PDE, using a Robotic System that uses a quadruped robot for data capture and transmission to the central station. The robot’s automatic data processing and control have been carried out through Robot Operating System (ROS). Several tests have been carried out in different environments to validate the proposed method, recreating PDE with varying conditions of light, from which the datasets have been generated for the training of three neural network models (Fast R-CNN, SSD, and YOLO). The method’s efficiency has been tested against another method based on CNN and RGB images for the same task showing greater effectiveness in PDE main results show that the proposed method has an efficiency greater than 90%.

The presence of faults in dynamic systems causes the potential loss of some of the control objectives. For that reason, a fault-tolerant controller is required to ensure a proper operation, as well as to reduce the risk of accidents. The present work proposes a passive fault-tolerant controller that is based on robust techniques, which are utilized to adjust a proportional-derivative scheme through a linear matrix inequality. In addition, a nonlinear term is included to improve the accuracy of the control task. The proposed methodology is implemented in the control of a two degrees of a freedom robotic helicopter in a simulation environment, where abrupt faults in the actuators are considered. Finally, the proposed scheme is also tested experimentally in the Quanser® 2-DOF Helicopter, highlighting the effectiveness of the proposed controller.

Harmonic reducers are generally supported by flexible bearings. The elastic deformation of the flexible bearing enables the harmonic reducer to satisfy high reduction ratio performance. By considering the flexible outer ring and noncircular inner ring of the flexible bearing, a universal static analysis model was developed to calculate the ball load distribution of flexible bearings in harmonic reducers. The validity of the proposed model was proved by studying two types of flexible bearings mounted on an elliptical cam and a four-force action-type cam, respectively. Several results validate the use of the model to assess the ball load distribution instead of a more time-consuming finite element method. Influences of design parameters in the flexible bearing on the load distribution were investigated, which makes reference for the optimal design of the flexible bearing. [ABSTRACT FROM AUTHOR]

In this paper, we design an adaptive neural network (NN) controller of uncertain ${n}$ -joint robotic systems with time-varying state constraints. By proposing a nonlinear mapping, the robotic systems are transformed into the multiple-input, multiple-output systems. Compared with constant constraints, the time-varying state constraints are more general in the real systems. To overcome the design challenge, the time-varying barrier Lyapunov function is introduced to ensure that the states of the robotic systems are bounded within the predetermined time-varying range. The NN approximations are employed to approximate the uncertain parametric and unknown functions in the robotic systems. Based on the Lyapunov analysis, it can be proved that all signals of robotic systems are bounded; the tracking errors of system output converge on a small neighborhood of zero and the time-varying state constraints are never violated. Finally, a simulation example is performed to demonstrate the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

In this work, an adaptive controller is designed by an adaptive network called fuzzy rules emulated network (FREN) for a class of nonlinear discrete-time systems when the mathematical model is completely neglected. The characteristic curve between the plant's input and output is drawn by results of the experimental setup. The design parameters are determined by the characteristic curve and utilized to design the controller. The network structure of FREN controller is established by the set of human knowledge-based IF-THEN rules according to the relation between the plant's input and output. The theoretical result is provided to guarantee the convergence of tracking error of the learning algorithm. Furthermore, experimental systems with the LED current control and the robotic system are constructed to validate the performance of the proposed controller. [ABSTRACT FROM AUTHOR]

Featured Application: A novel robot capable of performing maintenance and inspection tasks is designed to substitute humans to complete dangerous work in the railway bridges. A novel robot capable of performing maintenance and inspection tasks for railway bridges is proposed in this paper. Termed CMBOT (climbing manipulator robot), the robot is a combination of a five-degrees-of-freedom (5-Dof) biped climbing robot with two electromagnetic feet and a redundant manipulator with 7-Dof. This capability offers important advantages for performing maintenance and inspection tasks for railway bridges. Several fundamental issues of the CMBOT, such as robotic system development and motion planning algorithms, are addressed in this paper. A series of simulations and prototype experiments were conducted to validate the proposed robotic systems and motion planning algorithm. The results of the experiments show the reliability of the robotic systems and the efficiency of the motion planning algorithm. [ABSTRACT FROM AUTHOR]

Robotic handling systems are increasingly applied in distribution centers. They require little space, provide flexibility in managing varying demand requirements, and are able to work 24/7. This makes them particularly fit for e-commerce operations. This paper reviews new categories of automated and robotic handling systems, such as shuttle-based storage and retrieval systems, shuttle-based compact storage systems, and robotic mobile fulfillment systems. For each system, we categorize the literature in three groups: system analysis, design optimization, and operations planning and control. Our focus is to identify the research issue and operations research modeling methodology adopted to analyze the problem. We find that many new robotic systems and applications have hardly been studied in academic literature, despite their increasing use in practice. Because of unique system features (such as autonomous control, flexible layout, networked and dynamic operation), new models and methods are needed to address the design and operational control challenges for such systems, in particular, for the integration of subsystems. Integrated robotic warehouse systems will form the next category of warehouses. All vital warehouse design, planning, and control logic, such as methods to design layout, storage and order-picking system selection, storage slotting, order batching, picker routing, and picker to order assignment, will have to be revisited for new robotized warehouses. [ABSTRACT FROM AUTHOR]

Copyright of Dokuz Eylul University Muhendislik Faculty of Engineering Journal of Science & Engineering / Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi is the property of Dokuz Eylul Universitesi Muhendislik Fakultesi Fen ve Muhendislik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The continuous finite-time stabilization of a broad class of lower-triangular nonlinear systems using output feedback is studied in this paper. The nonlinearities are only assumed to be Hölder continuous. A constructive, continuous, finite-time, output-feedback stabilizer design is proposed based on a finite-time observer. Rigorous finite-time stability analysis is carried out for the closed-loop observer-controller system. The proposed design method is applied to a single-link robotic manipulator coupled to a dc motor. [ABSTRACT FROM AUTHOR]