Umer Hameed Shah received the BE and MS degrees in Mechanical Engineering from the National University of Sciences and Technology (NUST), Pakistan, in 2005 and 2012, respectively, and the PhD degree in Mechanical Engineering from the School of Mechanical Engineering, Pusan National University (PNU), South Korea, in 2018. He has held academic positions at several renowned institutions including the Lecturer position at NUST and postdoctoral positions at PNU, Texas A&M University at Qatar, and Khalifa University, United Arab Emirates (UAE). Currently, he is serving as an Assistant Professor at the Department of Mechanical Engineering, College of Engineering and Information Technology, Ajman University, UAE. He has been working in the broad research are of Dynamics and Control of Underactuated Systems that include hybrid ODE-PDE systems; cranes; vehicle suspension systems; underwater vehicle-manipulator systems; marine risers; compliant manipulators; and tactile sensors.
In this paper, the residual vibration control problem of a nuclear power plant’s fuel-transport system is discussed. The purpose of the system is to transport fuel rods to the target position within the minimum time. But according to observations, the rods oscillate at the end of the maneuver, causing an undesirable delay in the operation and affecting the system’s performance in terms both of productivity and of safety. In the present study, a mathematical model of the system was developed to simulate the under-water sway response of the rod while keeping in view the effects of the hydrodynamic forces imposed by the surrounding water. Experiments were performed to validate the model’s correctness. Further, simulation results were used to design the input shaping control that generates shaped velocity commands for transport of the fuel rods to the target position with the minimum residual vibration. It was observed that due to the under-water maneuvering, the fuel-handling system behaves as a highly damped process and that the generated shaped velocity commands fail to effect the desired suppression of the residual vibration. Therefore, keeping in view the highly damped nature of the system, a modified shaped command was generated that transported the fuel rods to the target position with the minimum residual vibration.
In this paper, residual sway control of objects that are moved underwater is investigated. The fuel transfer system in a nuclear power plant transfers the nuclear fuel rods underwater. The research on the dynamics of the loads transferred in different mediums (water and air) and their control methods have not been fully developed yet. The attenuation characteristics of the fuel transfer system have been studied to minimize its residual vibration by considering the effects of hydrodynamic forces acting on the fuel rod. First, a mathematical model is derived for the underwater fuel transfer system, and then experiments have been conducted to study the dynamic behavior of the rod while it travels underwater. Lastly, the residual vibration at the end point is minimized using the input shaping technique.
This paper addresses a residual vibration control problem of the refueling machine (RM) that transports fuel rods in water to their desired locations in the nuclear reactor. A hybrid lumped-mass and distributed-parameter model of the RM is considered for investigation of the transverse vibrations (caused by trolley movement) of a fuel rod in water. Simulations and experiments reveal that the hydrodynamic force causes a large deflection of the rod in water as compared with in air, which must be suppressed to avoid damage to the rod's fissile material. A new command-shaping method for suppression of the flexible rod's residual vibrations in water is developed, which considers both a similitude law relating the maximum endpoint deflection of the rod in water to the maximum trolley velocity and a constraint on the rod's maximum endpoint deflection during its transport. The simulation and experimental results show that the proposed underwater-command-shaping method can effectively suppress the vibrations of the flexible rod operating in water.
This paper addresses a simultaneous control of the positions of the bridge and trolley and the vibrations of the load of a nuclear refueling machine (RM) that transports nuclear fuel rods to given locations in the nuclear reactor. Hamilton’s principle is used to develop the equations of motion of the RM. The lateral and transverse vibrations of the fuel rods during their transportation in water are analyzed. In deriving the control law, the nonlinear hydrodynamic forces acting on the rod are considered. Then, a boundary control scheme is developed, which suppresses the lateral and transverse vibrations simultaneously in the course of the transportation of the fuel rod to the desired locations. Furthermore, Lyapunov function-based stability analyses are performed to prove the uniform ultimate boundedness of the closed loop system as well as the simultaneous control of the positions of the bridge and trolley under the influence of nonlinear hydrodynamic forces. Finally, experimental and simulation results are provided to demonstrate the effectiveness of the proposed control scheme.
This paper reviews the dynamics and vibration control techniques for marine riser systems. The riser pipes are modeled as Euler-Bernoulli beams that vibrate under the effects of ocean loads and the movements of the surface vessel, resulting in hybrid ODE-PDE equations. Chronological development of such hybrid models is first discussed, and their approximated ODE models for simulation are examined. Theoretical and experimental techniques for instability and fatigue analyses on the riser systems are also summarized. To increase the fatigue life against ocean currents, passive vibration suppression devices (e.g., strakes and spoilers) were mounted on the surface of the riser. Whereas to tackle the instability problem caused by sea waves, active control techniques utilizing the movements of the vessel were employed. In Conclusions, as future riser technologies, seven research issues are identified.
This chapter discusses the mathematical modeling of gantry crane systems, considering the subsystems of a crane to be rigid bodies. Such a formulation does not reflect the deflections within the individual parts of the crane but only considers their rigid body movements and results in a lumped mass model (LMM). Both the overhead and container cranes , shown in Figs. 1.1 and 1.3, respectively, lie within the category of gantry cranes . In developing the LMMs of gantry cranes , three different approaches for modeling the hoisting mechanism are usually followed: (i) single-rope hoisting mechanism , (ii) multi-rope hoisting mechanism , and (iii) double-pendulum system . The first approach, which considers a single-rope hoisting mechanism , represents the dynamics of a simple overhead crane considering the hook and the payload as a single-lumped mass.
discussed in Chap. 1, rotary cranes comprise tower cranes and boom cranes . In this chapter, we will discuss the dynamics of both the tower and boom crane systems. The operation of a tower crane consists of a slew motion of the jib , a translational motion of the trolley along the length of the jib , and a hoisting motion of the payload . The operations of a boom crane include slewing and luffing movements of the boom together with a hoisting motion of the payload (Ito et al. 1978).
In the previous chapters, we have discussed the crane systems with a fixed base, which are used at construction sites (e.g., tower cranes ), manufacturing/power plants (e.g., overhead cranes ), ship-building factories (e.g., gantry cranes ), and seaports (e.g., container cranes ), for handling heavy loads.
This chapter discusses modeling of crane systems as distributed parameter systems .
This paper reviews the existing vision-based tactile sensor (VBTS) designs reported in the literature. Although some reviews on VBTSs already exist in the literature. We believe it is necessary to review existing VBTS designs to formulate a guideline for developing such systems considering recent developments in the manufacturing and imaging technologies. Therefore, the main emphasis of this paper is to investigate current manufacturing trends and component selection criteria for developing a complete VBTS system. Further, the motivation behind this review is to identify the shortcomings in the current VBTS development technology and to furnish viable solutions to overcome such challenges. First, three different modalities of VBTSs are discussed: i) Waveguide-type designs, ii) marker-tracking based designs, and ii) reflective membrane designs. Next, a detailed discussion on various design aspects, like manufacturing, selection, and arrangements of the various sensor components, of the VBTSs is included. Then, a discussion on the validation/testing of various VBTSs is presented. Finally, based on the review, several challenges related to the development of VBTS are presented and the future research directions to overcome such challenges are recommended. This will serve the research community in determining the future research directions in the area of VBTS development.
This paper presents an innovative design of a hybrid compliant-rigid underwater manipulator that is capable of performing intervention operations underwater with high safety and precision by instantly shifting it’s joint-compliance. To analyze the responses of the said system, a mathematical model of the system is developed, which is used to simulate the system’s responses for different loading conditions. A PD control law is developed to maintain the position of the link at a desired value and to suppress its vibrations under the influence of hydrodynamic forces and environmental disturbances. Simulations are performed to analyze the safety and precision performance of the proposed manipulator system for compliant and rigid joint configurations.
This work presents the design, prototyping, and experimental evaluation of a parallel gripper with an optical mirroring mechanism based on the Periscope principle to enable vision-based sensing. The mechanism incorporates an optic system of three mirrors and a convex lens to transfer the grasping activity from the fingertip to a stationary camera placed at the gripper base. The mechanism arrangement allows isolating the camera from the grasping workspace to ensure its safety. The gripper prototype is equipped with a neuromorphic event-based camera that observes the reflected images from the optical mirroring mechanism to detect high-speed phenomena, such as object slippage. Experimental evaluation is carried out to assess the grasping and sensing capabilities of the gripper in a slip detection task. The results indicate that the event-based camera can detect slip moments across a different set of objects that represent surface, line, and point contact cases at a speed of 500 (i.e., 2 kHz) through a feature-based slip detection algorithm, highlighting the success of the proposed mechanism in providing a clear transmission of the grasping activity to the camera and enabling the sensorization of the gripper.
Rapid industrialization is consuming too much energy, and non-renewable energy resources are currently supplying the world’s majority of energy requirements. As a result, the global energy mix is being pushed towards renewable and sustainable energy sources by the world’s future energy plan and climate change. Thus, hydrogen has been suggested as a potential energy source for sustainable development. Currently, the production of hydrogen from fossil fuels is dominant in the world and its utilization is increasing daily. As discussed in the paper, a large amount of hydrogen is used in rocket engines, oil refining, ammonia production, and many other processes. This paper also analyzes the environmental impacts of hydrogen utilization in various applications such as iron and steel production, rocket engines, ammonia production, and hydrogenation. It is predicted that all of our fossil fuels will run out soon if we continue to consume them at our current pace of consumption. Hydrogen is only ecologically friendly when it is produced from renewable energy. Therefore, a transition towards hydrogen production from renewable energy resources such as solar, geothermal, and wind is necessary. However, many things need to be achieved before we can transition from a fossil-fuel-driven economy to one based on renewable energy.
In this paper, an adaptive fuzzy control design problem is investigated for an underwater vehicle manipulator system (UVMS) based on a fuzzy performance observer (FPOB) and fuzzy disturbance observer (FDO). The UVMS is considered as a nonlinear system comprising model uncertainties, external disturbances and dead-zone band input nonlinearities. To mitigate the combined effects of the dead-zone and the hysteresis, a novel pre-deadzone compensator is proposed. Then, fuzzy logic systems (FLSs) with online adaptations are utilized to evaluate the unknown components of the inertia matrix, the Coriolis matrix and the damping matrix. In addition, a fuzzy performance observer is constructed whose errors are used to estimate the external disturbances. Further, an H∞ fuzzy control technique is developed to reduce the errors in estimating the external disturbance. Then, the stability and tracking performance of the closed-loop system are analyzed using the Lyapunov stability theory. It is shown that all signals of the closed-loop system are uniformly ultimately bounded. Finally, simulations are performed to demonstrate the effectiveness of the proposed control scheme in addressing the tracking control problem of the UVMS in presence of the dead-zone band and disturbances.
Due to the depletion of fossil fuels, cost-effective and efficient alternate energy resources are a major topic of research nowadays. Solar energy is one of the renewable energy sources which is under research. The main emphasis is on developing new technologies for harnessing the sun’s energy efficiently. Solar photovoltaic (PV) cells are one such technology that works on the principle of the photovoltaic effect, with the electric output generated by it being directly influenced by the amount of light reaching the surface of the cell. Identification of those parameters, which act as an obstacle between light and the solar cell surface and decrease the efficiency of the cell drastically, is necessary. This research study focuses on the environmental parameters (dust and humidity) that directly influence PV cell performance. Here, experiments were conducted by using different types of dusts (sand, soil, ash) of varying quantities and then finding their effect on PV cell output. The results clearly indicate an adverse effect of quantity of dust on performance of the solar PV cell. Moreover, the relative humidity effect on the PV cell performance was also checked, which shows significant change in efficiency for high relative humidity.
Non-destructive and reliable radiation-based gauges have been routinely used in industry to determine the thickness of metal layers. When the material’s composition is understood in advance, only then can the standard radiation thickness meter be relied upon. Errors in thickness measurements are to be expected in settings where the actual composition of the material may deviate significantly from the nominal composition, such as rolled metal manufacturers. In this research, an X-ray-based system is proposed to determine the thickness of an aluminum sheet regardless of its alloy type. In the presented detection system, an X-ray tube with a voltage of 150 kV and two sodium iodide detectors, a transmission detector and a backscattering detector, were used. Between the X-ray tube and the transmission detector, an aluminum plate with different thicknesses, ranging from 2 to 45 mm, and with four alloys named 1050, 3050, 5052, and 6061 were simulated. The MCNP code was used as a very powerful platform in the implementation of radiation-based systems in this research to simulate the detection structure and the spectra recorded using the detectors. From the spectra recorded using two detectors, three features of the total count of both detectors and the maximum value of the transmission detector were extracted. These characteristics were applied to the inputs of an RBF neural network to obtain the relationship between the inputs and the thickness of the aluminum plate. The trained neural network was able to determine the thickness of the aluminum with an MRE of 2.11%. Although the presented methodology is used to determine the thickness of the aluminum plate independent of the type of alloy, it can be used to determine the thickness of other metals as well.
In this work, an improved Q learning control algorithm base on an extended state observer (ESO) is designed for an underwater vehicle manipulator system (UVMS). The UVMS is modeled as a nonlinear system with model uncertainties and external disturbances. In this paper, extended state observer (ESO) is constructed to evaluate the model uncertainties and external disturbances. In addition, an augmented system is constructed based on UVMS and reference signal. Furthermore, an improved Q learning control method is proposed to solve online the augmented algebraic Riccati equation (ARE) in the absence of the knowledge of the augmented system parameters. Finally, extensive numerical simulation results show that the effectiveness of the proposed optimal tracking control method for UVMS.
This paper addresses the problem of trajectory tracking control for the underwater vehicle manipulator system (UVMS) with parameter uncertainty and external disturbances. An adaptive linear active disturbance rejection control (ALADRC) scheme is proposed by combining ADRC and model-free adaptive control. Firstly, the UVMS dynamics model is discretized and converted into an equivalent dynamic linearization data model. Secondly, a parameter estimation law and an adaptive extended state observer are designed to estimate the pseudo-partial derivative matrix and the total disturbance in the data model respectively. Then, an adaptive LADRC law is designed to compensate the total disturbance to realize the trajectory tracking control. The proposed ALADRC is a typical data-driven solution, which only requires input-output data to achieve effective performance. Furthermore, the stability analysis of the designed control system is given. Finally, the effectiveness of the proposed control scheme is verified by numerical simulations.
Mobile robots are increasingly employed in today’s environment. Perceiving the environment to perform a task plays a major role in the robots. The service robots are wisely employed in the fully (or) partially known user’s environment. The exploration and exploitation of the unknown environment is a tedious task. This paper introduces a novel Trimmed Q-learning algorithm to predict interesting scenes via efficient memorability-oriented robotic behavioral scene activity training. The training process involves three stages: online learning and short-term and long-term learning modules. It is helpful for autonomous exploration and making wiser decisions about the environment. A simplified three-stage learning framework is introduced to train and predict interesting scenes using memorability. A proficient visual memory schema (VMS) is designed to tune the learning parameters. A role-based profile arrangement is made to explore the unknown environment for a long-term learning process. The online and short-term learning frameworks are designed using a novel Trimmed Q-learning algorithm. The underestimated bias in robotic actions must be minimized by introducing a refined set of practical candidate actions. Finally, the recalling ability of each learning module is estimated to predict the interesting scenes. Experiments conducted on public datasets, SubT, and SUN databases demonstrate the proposed technique’s efficacy. The proposed framework has yielded better memorability scores in short-term and online learning at 72.84% and in long-term learning at 68.63%.
This research introduces a robust control design for multibody robot systems, incorporating sliding mode control (SMC) for robustness against uncertainties and disturbances. SMC achieves this through directing system states toward a predefined sliding surface for finite-time stability. However, the challenge arises in selecting controller parameters, specifically the switching gain, as it depends on the upper bounds of perturbations, including nonlinearities, uncertainties, and disturbances, impacting the system. Consequently, gain selection becomes challenging when system dynamics are unknown. To address this issue, an extended state observer (ESO) is integrated with SMC, resulting in SMCESO, which treats system dynamics and disturbances as perturbations and estimates them to compensate for their effects on the system response, ensuring robust performance. To further enhance system performance, deep deterministic policy gradient (DDPG) is employed to fine-tune SMCESO, utilizing both actual and estimated states as input states for the DDPG agent and reward selection. This training process enhances both tracking and estimation performance. Furthermore, the proposed method is compared with the optimal-PID, SMC, and H∞ in the presence of external disturbances and parameter variation. MATLAB/Simulink simulations confirm that overall, the SMCESO provides robust performance, especially with parameter variations, where other controllers struggle to converge the tracking error to zero.
In this paper, the dynamics of a new type of container crane, in which eight ropes connect the trolley and spreader in a triangle-trapezoid shape, is developed. The triangle-trapezoid cable configuration for connecting the spreader with the trolley is introduced to reflect the dynamic aspects of the multi-rope reeving system. A super-twisting sliding mode control for the developed model is designed for accurate trolley position control and vibration suppression of the load. Due to its robustness property against external disturbance, satisfactory control performance is achieved. Finally, experimental results to validate the developed model and simulation results to verify the control algorithm are also provided in this study.
To achieve the requirements of lightweight, low energy consumption, and low inertia of an underwater vehicle manipulator system, a cable-driven manipulator is installed on the underwater vehicle to form a cable-driven flexible-joint-based underwater vehicle manipulator system (CDFJ–UVMS). The CDFJ–UVMS is a complex nonlinear system subject to model uncertainties, complex marine environment disturbances, and actuator dead-zone nonlinearity. To design track controllers, the CDFJ–UVMS dynamics is divided into two parts: known and unknown. Subsequently, a radial basis function neural network is adopted to approximate the unknown nonlinearity. A neural network performance observer is constructed, whose estimation error is then used to design a novel neural disturbance observer (NDO) to estimate the total disturbance. Finally, an adaptive neural network control method is proposed for the CDFJ–UVMS based on the NDO, neural network compensator, and neural performance observer. The stability of the closed-loop system is analyzed using the Lyapunov method. The proposed control algorithm is applied to a CDFJ–UVMS with two cable-driven joints and compared with other control methods to show the effectiveness of the proposed control algorithm.
Measuring the volume fraction of different types of fluids with two or three phases is so vital. Among all available methods, two of them, capacitance-based and gamma-ray attenuation, are so popular and widely used. Moreover, nowadays, AI which stands for Artificial Intelligence can be seen almost in all areas, and the measuring section is no exception. In this paper, the main goal is to predict the volume fraction of a three-phase homogeneous fluid which contains water, oil, and gas materials. To opt for an optimised method, a combination of capacitance-based sensors, gamma-ray attenuation sensor and Artificial Neural Networks (ANN) is utilised. To train the proposed metering system which is a MLP type, two inputs are considered. For the first input, the concave sensor is simulated in COMSOL Multiphysics software and different combinations of three phases (different volume fractions) are applied. Then through theoretical investigations of gamma-ray sensor, Barium-133 which radiates 0.356 MeV is used. This way, the second required input is generated. Finally, to implement a new and accurate metering system, a number of networks with different characteristics are run in the MATLAB software. The best structure had a Mean Absolute Error (MAE) equal to 0.33, 3.68 and 3.75 for the water, gas and oil phases, respectively. The accuracy of the presented metering system is illustrated by the received outcomes. The novelty of this study is proposing a new combined method that can measure a three-phase homogeneous fluid’s volume fractions containing water, gas and oil, precisely.
Top speed of an aircraft is limited by the stiffness and damping of a structure which are contributing to aeroelastic response such as divergence and flutter, respectively. This study explores stiffness tailoring of Carbon Fiber Reinforced Polymer (CFRP) spars using a proposed bi-level framework. Frequency-based aeroelastic approaches are fast but less accurate for highly flexible structures, while time-based methods utilizing Fluid-Structure Interaction offer high accuracy but at a significant computational cost. This work addresses the computational challenge by proposing a bi-level framework for efficient and accurate aeroelastic analysis. This framework employs a two-step process: Initially, a frequency-based approach in MSC NASTRAN provides an initial prediction of critical velocities. However, this method can be over-conservative for flexible structures due to limitations in capturing non-linear aerodynamics such as wake, viscous effects and induced drag. Subsequently, the framework utilizes ANSYS for more detailed analysis beyond the earlier predicted velocities. Essentially, this bi-level approach can reduce the computational cost upto 60% compared to a full-time-based analysis depending upon flight envelope, while maintaining an acceptable error margin of within 5%. Furthermore, this work investigates the impact of parametric optimization of stacking sequence on the CFRP spar. While maximizing shear modulus increases flutter speed, it comes at the expense of decreased divergence speed highlighting the importance of design trade-offs for improved aeroelastic performance. In conclusion, results of the aeroelastic tailoring showed that mass of the wing is reduced by 17.7% compared to baseline whereas divergence and flutter speed is increased by 10 and 22.8%, respectively.