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The use of microelectromechanical systems (MEMS) in electronics, automotive, consumer and medical sector is increasing rapidly. It is expected that by 2024 the Global MEMS and sensor market will reach the value of 93 billion dollars. MEMS inertial measurement sensors (accelerometer and gyroscopes) are used in low end consumer electronics such as smartphones to high end products such as drones used in military applications. MEMS IMU (Inertial Measurement Unit) are often deployed in dynamic environment such as in machining process for condition monitoring, vehicles for identifying driving behaviors, wearable technology for fall detection and many others. Consequently, Gaussian noise is always present in the output signal of such sensors. Denoising the output signal is critical for feature extraction and data analysis. Recently hybrid approaches for noise removal have gained much research attention. The aim of this paper is to present a hybrid noise removal algorithm for MEMS IMU sensors. In this technique, the signal to noise ratio has been improved and remove glitches by minimizing the hybrid noise from the original output signal of the MEMS IMU sensor.

Gimballed sensor system is a precision electromechanical assembly designed primarily to isolate the optical system from disturbances induced by the operating environment. This paper gives an insight to the design and development of gimballed sensor system for Line of Sight (LOS) stabilization of an electro-optical tracking and pointing system. Initially kinematic equations are formulated to establish a relationship between LOS angle and applied torque. This relationship is used to obtain nested loop transfer function model. First, the parameters of the proposed assembly are determined through experimentation & rigorous analysis process, and then conventional control design methodology is adopted for controller configuration design for current and rate loop. The frequency response analysis of the designed LOS stabilization model with conventional controller is done in simulation and the obtained results are verified experimentally against angular disturbances in real time scenario. Further, Based on prior qualitative information about system dynamics and linguistic performance criteria, a fuzzy logic controller of mamdani type with simplified rule set is developed with an objective to improve the disturbance attenuation and command response performance of designed system irrespective of angular disturbances due to platform vibrations, model uncertainties and mass imbalance in gimbal assembly. Both the Fuzzy logic simulation model and conventional model are tested based on critical performance characteristics such as stability of the loop, responsiveness of the loop and insensitivity to disturbances. Finally, the comparative analysis suggests that, although both the control configuration satisfies the required accuracy, Fuzzy logic control certainly improvised the performance of the gimballed sensor system and hence can be very effective for more precise pointing, tracking and stabilization application.

Imaging techniques such as X-ray, computerized tomography scan and magnetic resonance imaging are useful in the correct diagnosis of a disease or deformity in the organ. Two-dimensional imaging techniques such as X-ray give a clear picture of simple bone deformity but fail in visualizing multiple fractures in a bone. Moreover, these lack in providing a multi-angle view of a bone. Three-dimensional techniques such as computerized tomography scan and magnetic resonance imaging present a correct orientation of fracture geometry. Computerized tomography scan is a collection of multiple slices of an image. These slices provide a fair idea about a fracture but fail in the measurement of correct dimensions of a fractured fragment and to observe its geometry. It also exposes a patient with carcinogenic radiations. Magnetic resonance imaging induces a strong magnetic field. So, it becomes ineffective for organs containing metallic implants. The high cost of three-dimensional imaging techniques makes them inaccessible for economic weaker section of society. The limitations of two- and three-dimensional imaging techniques motivate researchers to propose an innovative machine learning model ‘CT slices to $3$-D convertor’ that accepts multiple slices of an image and yields a multi-dimensional view at all possible angles from 0 degree to 360 degree for an input image.

The aim of this paper is to analyze and evaluate the sensitivity and non-linearity of graphene piezoresistive MEMS force sensor by optimizing its geometrical parameters. In this work, important fac...

Since the last decade, there is a significant change in the procedure of medical diagnosis and treatment. Specifically, when internal tissues, organs such as heart, lungs, brain, kidneys and bones are the target regions, a doctor recommends ‘computerized tomography’ scan and/or magnetic resonance imaging to get a clear picture of the damaged portion of an organ or a bone. This is important for correct examination of the medical deformities such as bone fracture, arthritis, and brain tumor. It ensures prescription of the best possible treatment. But ‘computerized tomography’ scan exposes a patient to high ionizing radiation. These rays make a person more prone to cancer. Magnetic resonance imaging requires a strong magnetic field. Thus, it becomes impractical for patients with implants in their body. Moreover, the high cost makes the above-stated techniques unaffordable for low economy class of society. The above-mentioned challenges of ‘computerized tomography’ scan and magnetic resonance imaging motivate researchers to focus on developing a technique for conversion of 2-dimensional view of medical images into their corresponding multiple views. In this manuscript, the authors design and develop a deep learning model that makes an effective use of conditional generative adversarial network, an extension of generative adversarial network for the transformation of 2-dimensional views of human bone into the corresponding multiple views at different angles. The model will prove useful for both doctors and patients.

The study aimed to assess the hand-arm vibration (HAV), noise exposure, and shift in hearing threshold (SHT) due to the prolonged use of hand tools used in three different handicraft occupations. D...

Purpose This paper aims to propose a dynamically balanced mechanism for cleaning unit used in agricultural thresher machine using a dynamically equivalent system of point masses. Design/methodology/approach The cleaning unit works on crank-rocker Grashof mechanism. This mechanism can be balanced by optimizing the inertial properties of each link. These properties are defined by the dynamic equivalent system of point masses. Parameters of these point masses define the shaking forces and moments. Hence, the multi-objective optimization problem with minimization of shaking forces and shaking moments is formulated by considering the point mass parameters as the design variables. The formulated optimization problem is solved using a posteriori approach-based algorithm i.e. the non-dominated sorting Jaya algorithm (NSJAYA) and a priori approach-based algorithms i.e. Jaya algorithm and genetic algorithm (GA) under suitable design constraints. Findings The mass, center of mass and inertias of each link are calculated using optimum design variables. These optimum parameters improve the dynamic performance of the cleaning unit. The optimal Pareto set for the balancing problem is measured and outlined in this paper. The designer can choose any solution from the set and balance any real planar mechanism. Originality/value The efficiency of the proposed approach is tested through the existing cleaning mechanism of the thresher machine. It is found that the NSJAYA is computationally more efficient than the GA and Jaya algorithm. ADAMS software is used for the simulation of the mechanism.

This paper deals with the optimum two-plane balancing of the threshing drum using discrete parameters such as masses and corresponding angular locations on balance planes. To improve the dynamic pe...

Purpose The purpose of this paper is to propose the dynamically balanced mechanism for cleaning unit used in the agricultural thresher machine using the system of point masses. Design/methodology/approach The cleaning unit works on crank-rocker Grashof mechanism. To balance the mechanism, the shaking forces and shaking moments are minimized by optimizing the mass distribution of links using the dynamically equivalent system of point masses. The point mass parameters are taken as the design variables. Then, the optimization problem is solved using Jaya algorithm and genetic algorithm (GA) under suitable design constraints. Findings The mass, center of mass and inertias of each link are calculated using optimum design variables. These optimum parameters improve the dynamic performance of the cleaning unit. Originality/value The proposed methodology is tested through the standard four-bar mechanism taken from literature and also applied to the existing cleaning mechanism of the thresher machine. It is observed that the Jaya algorithm is computationally more efficient than the GA. The dynamic analysis of the proposed mechanism is simulated using ADAMS software.

This study describes the shape synthesis of a metallic flywheel using a non-dominated sorting Jaya algorithm. Generally, the flywheel is used to store the kinetic energy in the machines. Kinetic energy is an essential parameter to measure flywheel performance and can be improved by the optimal shape of the flywheel. In order to the optimal shape of the flywheel, the multi-objective problem with the maximization of the kinetic energy and minimization of von Mises stresses is formulated under appropriate design constraints using the cubic B-spline curve. A flowchart is proposed to solve the two-point boundary value differential equation for the calculation of von Mises stress at each point between the inner and outer radii of the flywheel. The design variables are represented by the control points of the cubic B-spline curve. A posteriori approach-based algorithm as non-dominated sorting Jaya algorithm (NSJaya) is used to solve the formulated optimization problem. This algorithm is based on the concepts of crowding distance and non-dominated sorting approach and gives the optimal Pareto set. The proposed method is applied to the flywheel of the agricultural thresher. The performance of the proposed algorithm is compared with that of non-dominated sorting genetic algorithm (NSGA-II) using hyper-volume performance metric. It is found that the NSJaya algorithm gives better results compared to NSGA-II and a posteriori approach-based algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), and Jaya. The optimal Pareto set for the optimal shape of the flywheel is calculated and outlined in this paper. The designer can choose any solution from the Pareto set for the optimal shape of the flywheel. ANSYS parameter design language (APDL) software is used for the validation of the von Mises stresses in the optimized shapes of the flywheel.

Mixed-variable optimization problems consist of the continuous, integer, and discrete variables generally used in various engineering optimization problems. These variables increase the computational cost and complexity of optimization problems due to the handling of variables. Moreover, there are few optimization algorithms that give a globally optimal solution for non-differential and non-convex objective functions. Initially, the Jaya algorithm has been developed for continuous variable optimization problems. In this paper, the Jaya algorithm is further extended for solving mixed-variable optimization problems. In the proposed algorithm, continuous variables remain in the continuous domain while continuous domains of discrete and integer variables are converted into discrete and integer domains applying bound constraint of the middle point of corresponding two consecutive values of discrete and integer variables. The effectiveness of the proposed algorithm is evaluated through examples of mixed-variable optimization problems taken from previous research works, and optimum solutions are validated with other mixed-variable optimization algorithms. The proposed algorithm is also applied to two-plane balancing of the unbalanced rigid threshing rotor, using the number of balance masses on plane 1 and plane 2. It is found that the proposed algorithm is computationally more efficient and easier to use than other mixed optimization techniques.

Purpose: The assistive knee exoskeleton device is used for supporting the surrounding ligaments, tendons, and muscles of the injured knee joint. Various knee exoskeletons have been discussed; howev...

While extracting land cover from remote sensing images, each pixel in the image is allocated to one of the possible class. In reality different land covers within a pixel can be found due to continuum of variation in landscape and intrinsic mixed nature of most classes. Mixed pixels may not be appropriately processed by traditional image classifiers, which assume that pixels are pure. The existence of mixed pixels led to the development of several approaches for soft (often termed fuzzy in the remote sensing literature) classification in which each pixel is allocated to all classes in varying proportions. However, while the proportions of each land cover within each pixel may be predicted, the spatial location of each land cover within each pixel is not. Thus, it is important to develop and implement a classifier that can work as soft classifiers for landslide identification. This work is an attempt to document and identify landslide areas by five spectral indices using temporal multi-spectral images from IRS-P6 LISS-IV images. To improve the spectral properties of spectral indices for specific class identification (in this case landslide) a Class Based Sensor Independent (CBSI) technique proposed. The result indicates that CBSI based Transformed Normalized Difference Vegetation Index (TNDVI) temporal indices data gives better results for landslide identification with minimum entropy and membership range.

This paper proposes a novel hybrid teaching–learning particle swarm optimization (HTLPSO) algorithm, which merges two established nature-inspired algorithms, namely, optimization based on teaching–learning (TLBO) and particle swarm optimization (PSO). The HTLPSO merges the best half of population obtained after the teacher phase in TLBO with the best half of the population obtained after PSO. The population so obtained is used subsequently in learner phase of TLBO. To validate the proposed algorithm, five constrained benchmark functions are considered to prove its robustness and efficiency. The proposed algorithm is applied to synthesize four-bar linkage for prescribed path. It is found that the HTLPSO performs better than other single nature-inspired algorithms for path synthesis problem in mechanism theory. Hence, HTLPSO may prove to be an important tool for mechanism design to follow the prescribed path.

Technological advances in prosthetics have attracted the curiosity of researchers in monitoring design and developments of the sockets to sustain maximum pressure without any soft tissue damage, skin breakdown, and painful sores. Numerous studies have been reported in the area of pressure measurement at the limb/socket interface, though, the relation between amputee's physiological parameters and the pressure developed at the limb/socket interface is still not studied. Therefore, the purpose of this work is to investigate the effects of patient-specific physiological parameters viz. height, weight, and stump length on the pressure development at the transtibial prosthetic limb/socket interface. Initially, the pressure values at the limb/socket interface were clinically measured during stance and walking conditions for different patients using strain gauges placed at critical locations of the stump. The measured maximum pressure data related to patient's physiological parameters was used to develop an artificial neural network (ANN) model. The effects of physiological parameters on the pressure development at the limb/socket interface were examined using the ANN model. The analyzed results indicated that the weight and stump length significantly affects the maximum pressure values. The outcomes of this work could be an important platform for the design and development of patient-specific prosthetic socket which can endure the maximum pressure conditions at stance and ambulation conditions.

The octahedron seven point mass model of equimomental point masses and optimization technique “teaching–learning-based optimization” is presented to minimize constraint forces and moments at joints of an industrial manipulator. The octahedron point mass model configuration presented offers positive values for equimomental point masses to facilitate link shape formation. Equations are derived to compute point masses and their locations for the rigid links of an industrial manipulator. The flow chart of the teaching–learning-based optimization applicable in solving the manipulators problem is presented and used. The constraint moments at heavily loaded joints are reduced significantly. Moreover, the maximum values of driving torques are also reduced at joints. It is observed that teaching–learning-based optimization gives better results with less computational effort vis-à-vis genetic algorithm for the manipulator optimization problem formulated. The teaching–learning-based optimization algorithm introduced first time for manipulator balancing as optimization solver.

This paper proposes the synthesis of a human knee exoskeleton using the reduced number of necessary and sufficient constraints. The proposed human knee exoskeleton consists of a defect-free crank-rocker mechanism capable of accurately moving its coupler point along the prescribed trajectory. For synthesizing the crank-rocker mechanism based on proposed reduced number of constraints, an optimization problem is formulated to synthesize the mechanism. An algorithm based on teaching-learning-based-optimization (TLBO) is presented to solve this highly nonlinear optimization problem. The optimization minimizes the error between generated and prescribed trajectory and simultaneously avoids any defect in the synthesized mechanism. The penalty method is used to manage all the constraints. Besides a realistic nontrivial example of human knee flexion/extension, a straight line trajectory is also considered to demonstrate the effectiveness of the refinement scheme in the optimal syntheses of planar crank-rocker linkage free from all defects. The optimization problem is solved using well-established nature-inspired algorithms such as genetic algorithm (GA), particle swarm algorithm (PSO), and teaching-learning-based-optimization (TLBO) algorithm. It is found that TLBO is computationally more efficient than other algorithms used here. Additionally, the proposed human knee exoskeleton model is experimentally validated for one gait cycle.

The set of measured data points acquired from the Coordinate Measuring Machine (CMM) need to be processed and analyzed for evaluating the form errors inside the manufactured components. This paper presents a modified algorithm of particle swarm optimization (MPSO) for assessing the form error from the set of coordinate measured data points. In the classical algorithm of the particle swarm optimization (PSO), the value of the candidate solution is updated from its existing value without actually comparing the value obtained in the consecutive iterations for fitness. This behaviour attributes to a lack of exploitation ability in the defined search space. The proposed algorithm generates new swarm position and fitness solution for the objective function through an improved and modified search equation based on a proposed heuristic step. In this step, the swarm searches around the best solution of the previous iteration for improving the swarm exploitation capability. The particle swarm uses greedy selection procedure to choose the best candidate solution. A non-linear minimum zone objective function is formulated mathematically for different types of form errors and then optimized using proposed MPSO. Five benchmark functions are used to prove the effectiveness of the modified algorithm, which is verified by comparing its solution and convergence with those obtained from the established algorithms namely PSO and genetic algorithm (GA). Finally, the result of the proposed algorithm for form error evaluation is compared with previous work and other established nature-inspired algorithms. The results demonstrate that the proposed MPSO algorithm is more efficient and accurate than the other conventional heuristic optimization algorithms. Furthermore, it is well suited for form error evaluation using CMM acquired data.

The pattern of changing hydro-geochemical characteristics of water in Himalayan rivers is primarily controlled by sediment load from natural sources in higher altitudes and anthropogenic sources such as the burning of fossil fuels for domestic use, vehicular emissions, and wind transported industrial pollutants in the downstream region. The assessment of water quality is critical for the comparison of natural and anthropogenic sources in the downstream areas due to the dependence of the population on the glacial meltwater for freshwater supply. In the present study, we investigate the physical and ionic characteristics of glacial meltwater from Naradu Glacier catchment concerning the dominant weathering process. The freshwater samples were collected during the ablation period of 2016 and 2017 from specified locations. The physical parameters (pH, electrical conductivity, and temperature) were measured in the field while the analyses for concentrations of major cations (Ca2+, Mg2+, K+, Na+) and major anions (Cl−, SO42−, HCO3−, NO3−) were done in the laboratory. The anions (HCO3− > SO42− > Cl− > NO3−) and cations (Ca2+ > Mg2+ > Na+ > K+) concentrations were observed to have similar trends for both of the ablation period. The statistical analysis shows the predominance of geological weathering processes in the catchment as the controlling factor for the variation in concentration of different ionic species. The catchment was found to be rich in rocks with carbonate mineral making the Ca2+ and HCO3− the most dominant ions in the glacial meltwater.

An optimum design of an industrial robot can be achieved from different point of views. For example, a robot can be conceived from the standpoint achieving maximum workspace or minimum weight, etc. In this paper, the objective is to arrive at a robot design that will require optimum driving torques/forces at its joints to perform tasks within its workspace. Such a design will automatically save energy. Note that these torques/forces at the joints are highly dependent on the mass and the inertia properties of the robot’s links. Therefore, these quantities were minimized by determining the optimum masses and optimum mass centers and finding out the corresponding inertia properties of the moving links. Such an approach was briefly introduced earlier by the authors with the help of a simple two-link planar arm. In this paper, the concept is generalized and demonstrated with the help of a complex robot, a 6-degrees-of-freedom PUMA robot. To achieve the design for optimum driving torques/forces at the joints, the concept of equimomental system of point masses was introduced, which helped to obtain the optimum locations of the mass centers of each link quite conveniently. However, to compute the driving torques/forces recursively for such equivalent point mass systems, the decoupled natural orthogonal complement matrices for point masses (DeNOC-P) was derived. It has led to a simplified algorithm for obtaining driving torques/forces. The proposed algorithm for optimization is illustrated with the help of a PUMA robot.

Computer-aided tools help in shortening and eradicating numerous repetitive tasks that reduces the gap between digital model and actual product. Use of these tools assists in realizing free-form objects such as custom fit products as described by a stringent interaction with the human body. Development of such a model presents a challenging situation for reverse engineering (RE) which is not analogous with the requirement for generating simple geometric models. Hence, an alternating way of producing more accurate three-dimensional models is proposed. For creating accurate 3D models, point clouds are processed through filtering, segmentation, mesh smoothing and surface generation. These processes help in converting the initial unorganized point data into a 3D digital model and simultaneously influence the quality of model. This study provides an optimum balance for the best accuracy obtainable with maximum allowable deviation to lessen computer handling and processing time. A realistic non trivial case study of free-form prosthetic socket is considered. The accuracy obtained for the developed model is acceptable for the use in medical applications and FEM analysis.

A two-stage optimization method for optimal dynamic design of planar mechanisms is presented in this paper. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of mechanism links using the equimomental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e. cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using evolutionary optimization algorithm – “Teaching-learning-based optimization (TLBO) algorithm”. The computational performance of TLBO algorithm is compared with another evolutionary optimization algorithm, i.e. genetic algorithm.

This paper presents a Neural-fuzzy model structure to improve the disturbance attenuation performance of a gimballed Line of Sight (LOS) stabilization system. Initially, a Fuzzy Logic Controller (FLC) based on prior qualitative information about system dynamics and linguistic performance criteria is developed. Next, proposed Neural-fuzzy model architecture is constructed, which overcome the difficulties and limitations of each isolated methodology. The Neural-fuzzy architecture is developed based on input-output data-sets available from FLC. Fuzzy curve approach is used to determine significant inputs, number of rules, initialization of connecting layers weights, and hence the model structure. Both the controller configurations are tested based on critical performance characteristics such as stability of the loop, responsiveness of the loop and insensitivity to disturbances. Finally, the comparative analysis suggests that the proposed Neural-fuzzy controller completely outperforms the FLC configuration and hence, can be very effective for more precise pointing applications.

This study is aimed for the analysis of different designs for sensing low magnitude forces which lies in the micro-Newton range and suitable for biomimetic microbotics. For this, a flexible and high sensitive Micro Electro Mechanical System (MEMS) based Force sensor using piezoresistive sensing mechanism has been analyzed. Design analysis is carried out for sensitivity enhancement on microcantilever by incorporating various combinations of stress concentrated regions (SCR) and their respective arrays. The materials under consideration for sensor are polysilicon piezoresistors and Polydimethylsiloxane (PDMS) microcantilever. For design analysis, the designing and simulation work is assessed using Finite Element Analysis approach in COMSOL Multiphysics 5.3a software. The results revealed that the electrical sensitivity of 1.62 mV/[Formula: see text]N within (0–100) [Formula: see text]N operating range is achieved for microcantilever with rectangular SCR with square SCR array. This operating range has many applications in microbotic field such as sensing tactile movements. Hence, MEMS Force sensor for low magnitude forces has been designed with high sensitivity and flexibility.

Several emerging IOT applications may require ultra-low power image-acquisition techniques, at the cost of relaxed constraints on image quality. Event-driven imaging, based on address-event-representation (AER) proposed earlier, ensures event-driven motion detection and conditional image acquisition. However it relies on delta modulation of pixel data upon event detection, which may lead to error accumulation for grey-scale reconstruction. In this work we propose event-driven on-sensor halftoning scheme based on cellular neural network (CNN), which can achieve compressed image acquisition, reducing the data to one bit per active pixel, while avoiding error accumulation over multiple frames. The proposed scheme can achieve reduction in power dissipation related to image quantization, communication and storage. Event-driven current-mode discrete-time CNN (DT-CNN) circuit is proposed for integration on CMOS imager pixel, which is optimally duty cycled to achieve ultra-low power for the halftoning operation. The impact of design parameters and process variations on the final image quality is assessed through inverse halftoning. Clubbed with event-driven acquisition, the proposed on-sensor halftoning can achieve large reduction in power dissipation and data volume, reduction in total volume, as compared to frame based imaging, as well as event driven grey-scale imaging.

Background/Objective Human walking involves the coordination of brain, nerves, and muscles. A disturbance in their coordination may result in gait disorder. The gait disorder may be treated through manually assisted gait training or with the aid of assistive devices/robotic devices. These robotic devices involve mechanisms which are synthesized using complex conventional procedures. Therefore, in this study, a new gait-based synthesis procedure is proposed, which simplifies the mechanism synthesis and helps to develop a mechanism which can be used in rehabilitation devices, bipeds, etc. Methods This article presents a novel procedure for the synthesis of 4-bar linkage using the natural gait trajectories. As opposed to the conventional synthesis procedures, in this procedure, a global reference frame is considered, which allows the use of hip trajectory while moving. Moreover, this method is divided into two stages, and five precision points are considered on the hip trajectory in each stage. In the first stage, the 4-bar linkage is designed, thereafter, the configurations of the linkage for the remaining precision points are determined in the second stage. The proposed synthesis procedure reduces the complexity involved in the synthesis and helps in the simplification of the problem formulation. A two-stage optimization problem is formulated for minimizing the error between the generated and desired hip trajectories. Two nature-inspired algorithms are used for solving the optimization problem. The obtained best results are presented, and the designed linkage is simulated in MATLAB. Results The best design of the linkage is obtained using particle swarm optimization. The trajectories generated by the designed linkage using the proposed methodology can accurately track the desired path, which indicates that designed linkage can achieve all the orientations required during walking. The positions of a whole lower limb at all the desired precision points are demonstrated by stick diagram for one gait. Conclusion The proposed methodology has reduced the complexity of synthesis procedures and used optimization techniques to obtain a feasible design of the mechanism. The stick diagram of the designed mechanism obtained using the proposed method indicates that the designed mechanism can walk smoothly. Hence, the designed mechanism can be used in the rehabilitation devices. Furthermore, a conceptual design of an exoskeleton knee is also presented. The Translational Potential of this Article Many hospitals and individuals have used the immobile and portable rehabilitation devices. These devices involve mechanisms, and the design of mechanism plays a vital role in the functioning of these devices; therefore, we have developed a new synthesis procedure for the design of the mechanism. Besides synthesis procedure, a mechanism is developed that can be used in the rehabilitation devices, bipeds, exoskeletons, etc., to benefit the society.

In this paper an ANFIS-PD+I (AFSPD+I) based hybrid force/position controller has been proposed which works effectively with unspecified robot dynamics in the presence of external disturbances. A constraint is put to limit the movement of manipulator in XY Cartesian coordinates. The validity of the proposed controller has been tested using a 6-degree of freedom PUMA robot manipulator. The performance comparison have been done with the fuzzy proportional derivative plus integral, fuzzy proportional integral derivative and conventional proportional integral derivative controllers subjected to the same data set with proposed controller. The projected AFSPD+I controller adhered to the desired path closer and smoother than the other mentioned controllers.

Background: Walking is a complex process that involves rhythmic movement of lower limb along with the coordination of brain, nerves and muscles. If the coordination is disturbed, gait may be effected or disordered. Therefore, it should be treated effectively and efficiently using assistive devices/exoskeletons. The exoskeletons and assistive devices may be embedded with the linkage and other mechanisms to imitate the behavior of human lower limb. However, these mechanisms are synthesized using the complex conventional procedures. Thus, a new gait-inspired algorithm is proposed in this study for synthesizing a four-bar mechanism for exoskeletons.Methods: This paper presents a design of four-bar linkage for lower limb exoskeleton to support walking. A new gait-inspired algorithm to synthesize four-bar linkage is also proposed which uses two phases of gait, namely, the swing phase and the stance phase, for lower limb exoskeleton. The trajectory is derived for each phase of the gait and is combined with the optimization techniques. The trajectory passes through 10 precision points in each phase giving a total of 20 precision points for one gait cycle. The optimization is performed in two stages. The first stage deals with the minimization of error between the desired and the generated foot trajectories; whereas, the second stage deals with the minimization of error between the desired and generated hip trajectories of the linkage. Besides the gait-inspired four-bar linkage synthesis, a hybrid teaching-learning-particle-swarm-optimization (HTLPSO) technique is also used to solve the problem.Results: A well-established genetic algorithm (GA) and a new hybrid (HTLPSO) algorithm are used to compare the results of the tracking error of the linkage. It is found that the HTLPSO optimization algorithm performs better in comparison to GA for the problem considered here. Finally, a solid model of the proposed design for lower limb exoskeleton is presented. Moreover, the obtained linkage tracks all the prescribed points accurately and the simulation of designed linkage has been demonstrated using stick diagram for one gait cycle.Conclusion: The proposed method has simplified the synthesis procedure to a great extent, and a feasible design is obtained using the optimization algorithm. The mechanism obtained using the proposed method can walk smoothly which is validated through stick diagram. The proposed mechanism can be used for exoskeleton, assistive devices, bipeds etc. Moreover, the proposed method may be extended to six- and eight-bar mechanisms.

This paper presents comparative analysis of different controller configuration for speed control of separately excited DC motor. The main aim of this paper is to obtain optimize speed characteristics of DC motor drive by minimizing transient response specification such as rise time, settling time and overshoot. The speed control of DC motor is done using PID, Fuzzy and ANFIS controller Configuration. PID controller tuning parameters are obtained using Ziegler Nicholas (ZN) and Modified Ziegler Nicholas (MZN) method. This PID configuration is used as a reference to develop Fuzzy and Anfis structure. In this study, transfer function based model of DC motor is developed with defined parameters which is then integrated with different controller configuration. Finally, the developed system is tested for number of simulation runs and comparative analysis shows that ANFIS provide superior features including easy implementation, good computational efficiency, and stable convergence characteristic and this has validated the robustness of the ANFIS scheme.

The objective of this work is to identify optimum pressure distribution of the prosthetic socket under specific load using finite element analysis (FEA). In addition, this study includes the topology optimisation of the socket using Altair's OptiStruct software. The socket needs to be flexible, but strong, to permit normal gait movement, but not twist/bend under pressure. Plaster of Paris (PoP) sockets of different clinical cases and below knee (BK) amputees having different stump geometries have been considered in this paper. The CAD model is developed by using point cloud data and meshing approach used for creating a volume mesh. The quantification of location, intensity and distribution of stress-strain on the socket leads to improved socket design. The proposed method redesigns the socket to improve patient comfort using FEA along with reverse engineering techniques. Further, the patients would feel comfortable with lightweight due to customised prosthetic sockets. The results of the study are in sync with the available literature.

Computer-aided tools help in shortening and eradicating numerous repetitive tasks that reduce the gap between digital model and the actual product. Use of these tools assist in realizing free-form objects such as custom fit products as described by an stringent interaction with the human body. Development of such model presents a difficult situation for reverse engineering (RE), which are not analogous with the requirement for generating simple geometric models. Hence, an alternating way of producing more accurate three-dimensional models is proposed. For creating accurate 3D models, point clouds are processed through filtering technique, segmentation, mesh smoothing and surface generation. These processes help in converting the initial unorganized point data into a 3D digital model and simultaneously influence the quality of the model. This study provides an optimum balance for the best accuracy obtainable with maximum allowable deviation to lesser computer handling and processing time. In this paper, a realistic nontrivial case study of the free-form prosthetic socket is considered. The accuracy obtained for the developed model is acceptable for the use in medical applications and FEM analysis.

The manufacturing of limb prosthesis socket that is comfortable for the amputee depends greatly on prosthetic practitioner’s knowledge of socket biomechanics and skill. It involves multistage manual corrections depending upon the clinical condition of the patient’s residual limb which may be affected by shrinkage or possible damage of plaster of paris (PoP) mold. The current work describes a novel process simplified through digitization, it integrates conventional PoP processes, reverse engineering (RE), and additive manufacturing (AM) technologies to design and develop a socket. The stereolithography (STL) file generated from the scan data was modeled on a fused deposition modeling (FDM) based AM. Its fitment was assessed with the help of INSPECTPLUS and GEOMAGIC reverse engineering tools. This approach takes the guess work out of prosthetic practitioner’s job, ensures better fitment, and shortens the total fabrication time leading to improved patient satisfaction. The proposed method is a part of the ongoing research and it will offer maximum comfort on demand to the patients through digitization.

Electromagnetic forming is a high-velocity, unconventional forming process, in which a high magnetic field is used to form a metal workpiece. Light weight metals such as aluminium and magnesium and their alloys are generally formed through this type of forming process. Increasing the temperature would lead to a decrease in the flow stress of a material. Thus, a metal can be deformed easily at elevated operating temperatures for the case of conventional forming. In this paper, high-velocity electromagnetic forming analysis of aluminium alloy AA5182 has been carried out in a commercially available FEM package, LS Dyna®. The deformation behaviour, in the case of electromagnetic forming, has been studied for various elevated temperatures in order to determine the feasibility of the process at high temperatures.