This paper presents a parametric study of an eddy current (EC) sensor that measures the magnetic flux density (MFD) for detecting lack-of-fusion defects commonly found in metal additive manufacturing (Metal-AM). In this study, the EC-sensing system is simulated using a two-stage method that decomposes the EC-based detection of a defective conductor into two subproblems; the first analytically solves for the EC assuming no defects, and the second solves for the EC perturbation in the focused regions near the defects using a distributed current source method. Based on the proposed EC model, the effects of geometrical parameters on the sensitivity of an EC-sensing system were analyzed and verified by comparing with finite-element analysis (FEA). The study leads to the identification of two key parameters that significantly affect the sensitivity and accuracy of an EC sensor for detecting small defects, which are the locations and axes of the MFD sensors relative to the coil. The ECD distributions are simulated for two EC-sensor design scenarios: fixed at specified locations, and scanning over the entire specimen. Both DCS-based and FEA results match excellently well when images are at a fixed senor location. When scanning, DCS-based images are much smoother and require significantly less time to scan as compared to FEA that requires remeshing between steps and exhibits significant numerical noise, demonstrating the accuracy and efficiency of the proposed numerical model.

In this paper, a novel snake like robot design is presented and analyzed. The structure described desires to obtain a robot that is most like a snake found in nature. This is achieved with the combination of both rigid and soft link structures by implementing a 3D printed rigid link and a soft cast silicone skin. The proposed structure serves to have a few mechanical improvements while maintaining the positives of previous designs. The implementation of the silicone skin presents the opportunity to use synthetic scales and directional friction. The design modifications of this novel design are analyzed on the fronts of the kinematics and minimizing power loss. Minimization of power loss is done through a numerical minimization of three separate parameters with the smallest positive power loss being used. This results in the minimal power loss per unit distance. This research found that the novel structure presented can be effectively described and modeled, such that they could be applied to a constructed model.

Regulating the melt-pool size to a constant reference value during the build process is a challenging task in Laser Powder Bed Fusion additive manufacturing (LPBF-AM). This paper considers adjusting laser power to achieve a constant melt-pool volume during laser processing of a multi-track build under LPBF-AM. First, a Gaussian Process Regression (GPR) is applied to model the variation of the melt-pool volume along the deposition distance, with physics-informed input features. Then a constrained finite-horizon optimal control problem is formulated, with a quadratic cost function defined to minimize the difference between the melt-pool volume and a reference value. A projected gradient descent algorithm is applied to compute the sequence of laser power in the proposed optimal control problem. The GPR modeling of melt-pool dynamics is trained and tested using simulated data sets generated from a commercial finite-element based AM software, and the same commercial AM software is used to evaluate the control performance. Simulation results demonstrate the effectiveness of the proposed GPR modeling and optimal control in regulating melt-pool volume for building multi-track parts with LPBF-AM.

Electrohydrodynamic jet printing (e-jet printing) is a nascent additive manufacturing process most notable for extremely high resolution printing and having a vast portfolio of printable materials. These capabilities make e-jet printing promising for applications such as custom electronics and biotechnology fabrication. However, reliably fulfilling e-jet printing’s potential for high resolution requires delicate control of the volume deposited by each jet. Such control is made difficult by a lack of models that both capture the dynamics of volume deposition and are compatible with the control schemes relevant to e-jet printing. This work delivers such a model. Specifically, this work introduces a definition of “droplet volume” as a dynamically evolving variable rather than a static variable, and uses this definition along with analysis of high speed microscope videos to develop a hybrid dynamical system model of droplet volume evolution. This model is validated with experimental data, which involves the contribution of a novel technique for extracting consistent droplet volume measurements from videos.

This paper presents a machine-learning based predictive modeling approach on how process input parameters affect melt-pool volumes for a Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) process. A physics-informed approach is adopted to define input features for the machine-learning models, and a two-level architecture is defined for the model training and validation. Specifically, a so-called initial (pre-deposition) temperature at the deposition point is identified as one key variable in characterizing thermal history for predicting melt-pool sizes. At the lower-level of the two-level modeling architecture, a hybrid model consisting of an analytical computation and a Gaussian process is developed to predict the pre-deposition temperature using process input parameters. Then at the higher-level of the modeling architecture, eight machine learning algorithms (including machine-learning based regression models and a two-layer neural network) are evaluated in predicting melt-pool volumes using the pre-deposition temperature and process parameters. For this proof-of-concept study, simulation data generated from the Autodesk Netfabb Local Simulation are used for model training and validation. The study shows that the proposed two-level machine learning model achieves high prediction performance and its prediction accuracy improves significantly compared to the one-level machine learning without using pre-deposition temperature as an input feature.

Control of part geometry to achieve desired geometric accuracy is critical for fabrication of complex components via laser-based additive manufacturing (AM) processes. Especially for Laser Powder Bed Fusion (LPBF) AM, which uses laser heat source with a much smaller focus diameter and builds parts with much finer resolution, the requirement on geometric accuracy poses additional challenges. For example, simulating a LPBF process using finite-element analysis (FEA) requires significantly higher computation power and time compared to simulating other AM processes such as the direct energy deposition (DED) processes, which makes FEA models difficult to use for real-time control and/or optimization. This paper aims to develop an analytical, control-oriented model on the dynamics of melt-pool volume in building a multi-track part using LPBF. The derivation of the melt-pool dynamics starts from a lumped-parameter-based governing equation on the energy balance of the molton puddle, combined with characterization of thermal history and temperature contributions from past tracks. Based on this analytical model on melt-pool volume, a nonlinear inverse-dynamics controller is designed to adjust laser power such that the melt-pool volume is regulated to a constant set point during the build process of a multi-track part. The performance of the control is evaluated by FEA using Autodesk’s Netfabb Local Simulation. This proof-of-concept study lays the initial foundation for developing more advanced control-oriented models for melt-pool geometry in LPBF and future work includes experimental evaluation of the proposed modeling and control design.

This paper describes a modular 2-DOF serial robotic system and accompanying experiments that have been developed to instruct robotics students in the fundamentals of dynamic force control. In prior work, we used this same robot to showcase and compare the performance of a variety of textbook techniques for dynamic motion control (i.e. fast/accurate trajectory tracking using dynamic model-based and robust control techniques). In this paper we now add a low-cost 3D-printed 2-DOF force sensor to this modular robot and demonstrate a variety of force control techniques for use when the robot is in physical contact with the environment. These include stiffness control, impedance control, admittance control, and hybrid position/force control. Each of these various force control schemes can be first simulated and then experimentally implemented using a MATLAB/Simulink real-time interface. The two-degrees of freedom are just enough to demonstrate how the manipulator Jacobian can be used to implement directional impedances in operational space, and to demonstrate how hybrid control can implement position and force control in different axes. This paper will describe the 2-DOF robot system including the custom force sensor, illustrate the various force control methods that can be implemented, and demonstrate sample results from these experiments.

This paper introduces a new quasi-steady in-ground effect model for rotorcraft unmanned aerial vehicles to predict the aerodynamic behavior when the vehicle’s rotors approach ground plane. The model assumes that the compression of the outflow due to the presence of ground plane induces a change in the induced velocity that can drastically affect the thrust and power output. The new empirical model describes the change in thrust as a function of the distance to an obstacle for a rotor in hover condition. Using blade element theory and the method of image, the model parameters are described in terms of the rotor pitch angle and solidity. Experiments with off-the-shelf, fixed-pitch propellers and 3D-printed variable pitch propellers are carried out to validate the model. Experimental results suggest good agreement with 9.5% root-mean-square error (RMSE) and 97% p-value of statistic significance.

Stroke-induced disability interferes with survivors’ participation and engagement in activities of daily living. With increasing costs of healthcare and lack of trained medical personnel, frequent supervised physical therapy is not adequately available to the majority of patients. Consumer-grade gaming controllers are emerging as a viable means to facilitate physical therapy to patients’ homes conveniently and affordably. However, their non-universal design is not always favorable to people with disability, who often experience considerable difficulty with adapting their hand posture to fit commercial designs targeted at healthy people. In attempts to complete their prescribed exercise tasks, these patients often employ compensatory strategies that may impede their recovery and increase their risk of injury. In order to improve the outcomes and safety of telerehabilitation without compromising its affordability, the possibility of mitigating motor compensation with consumer-grade gaming controllers through 3D-printed retrofit extensions is explored. A retrofit handle is designed for the Novint Falcon, a haptic device that mediates fine motor rehabilitation to allow for physiological grasp and promote wrist motion. Its impact on motor performance and compensation patterns is tested, providing preliminary evidence for the potential of this approach.

Direct energy deposition (DED) is a metal additive process that has applications in high-value part repair and fabrication of functionally-graded parts. However, the process is sensitive to commanded inputs and process conditions, such as powder flow and heat conduction from the melt pool, which change throughout the course of a build and often lead to geometric inaccuracies in the final part. Thus, there is a need for in-process sensing and feedback control to improve robustness to process conditions and achieve the desired part geometry. Previously, a repetitive process, quadratic-optimal height controller was implemented on thin-wall builds, where height measurements and control updates were performed in between layers. In that work, the desired layer thickness remained constant from layer to layer. Here, the repetitive process framework is extended to account for height references that change with layer number, as will be the case for producing more complex part geometries. Using this extended model, a model predictive controller is derived and simulated on a part build with iteration-varying references.

This study presents the design and multi-physics finite element analysis of a novel hydraulically amplified dielectric elastomer actuator (HADEA). The design was optimized for additive manufacturing and consists of a hyper-elastic silicone toroidal shell enclosing a dielectric liquid filled chamber and a pair of elastic annular electrodes partially covering the opposing actuator surfaces. Application of voltage on electrodes leads the central region of the HADEA to be compressed due to the induced Maxwell stress. Consequently, the peripheral region of the HADEA is axially expanded by the pressurized dielectric liquid. The finite element modeling and analysis that couples the structural, electrostatic, and fluid-structure interaction effects in the model is presented. We investigated the effect of two geometric parameters, the electrode size relative to the actuator diameter and the height of the actuator, on the actuation stroke of HADEAs. Numerical results showed actuation strains up to 63.1% while maintaining the electrodes’ voltage in instrument range. The proposed design shows promising potential for the application of HADEAs in bio-mechanical systems, soft robots, and co-robots capable of human interaction.

This paper presents a novel wind turbine blade with an actively adaptable twist angle. A weighted-least square technique is proposed to design and control the blade in its application. Controlling the twist distribution provides new capabilities that may not be achievable with blade pitch or rotor torque control. An adaptive twist angle can reduce fatigue loads and improve the efficiency of wind energy conversion. Our previous work established the theoretical blade twist distribution that maximizes wind capture during partial load operation. The twist distribution changes continuously as a function of wind speed. In practice, it is a challenge to design and control the blade to adapt to this range of transformation. Accordingly, a blade concept and engineering design method are proposed to achieve this task. The blade is constructed from additively manufactured sections that are assumed to have tunable stiffness. The sections are mounted on a centralized spar that provides stiffness. The sections are actuated at each end and have two zones of stiffness. A mathematical framework prescribes (1) length of each blade section and (2) the relative stiffness between a pair of compliant shells. Establishing the section length effectively sets the points of actuation, while the relative stiffness establishes a nonlinear twist. These design selections determine the twist distribution. The method employing weighted-least squares is employed to optimize these selections. The approach biases the shape design and control towards the theoretical twist distribution at a range of designated wind speed. This enables a customized solution that maximizes the wind capture based on the wind conditions at a given installation site.

Additive manufacturing (AM) uses computer-aided design to construct parts layer by layer. Relative to traditional manufacturing processes, AM provides a time-efficient and cost-effective way to produce low-volume, customized parts with complex geometries. This work presents an improved Cross-Coupled iterative learning control (CCILC) scheme to overcome current limitations in contour following for complex, free-form curves in AM. The approach involves modifying the definition of the error vector used in the individual axis iterative learning controllers and defining time varying weightings based on the curvature of the reference trajectory to couple tracking and contour errors. In this paper, the design for the improved CCILC system is presented, and the performance of this system is compared to the performance of existing ILC control schemes via simulations. In comparison to the current control methods, the simulation results demonstrate significant performance improvements for contour tracking of a reference trajectory with high levels of curvature.

Modulating the closed-loop transmission of energy in a wide frequency band without sacrificing overall system performance is a fundamental issue in a wide range of applications from precision control, active noise cancellation, to energy guiding. This paper introduces a loop-shaping approach to create such wideband closed-loop behaviors, with a particular focus on systems with nonminimum-phase zeros. Pioneering an integration of the interpolation theory with a model-based parameterization of the closed loop, the work proposes a filter design that matches the inverse plant dynamics locally and creates a framework to shape energy transmission with user defined performance metrics in the frequency domain. Application to laser-based powder bed fusion additive manufacturing validates the feasibility to compensate wide-band vibrations and to flexibly control system performance at other frequencies.

The swashplate of a model helicopter consists of stationary and rotating plates separated by ball bearings. This mechanism enables the swashplate to tilt in all directions and move vertically as one unit. The lower stationary plate is mounted on the main rotor mast and connected to the cyclic and collective controls by a series of pushrods. There are similar pushrods known as pitch links connected to the upper rotating plate. These pitch links are connected to the pitch horns and control the pitch of individual blades. In this study, the pitch links of the model helicopter are replaced by a semi compliant mechanism. This mechanism is directly connected to the pitch horns to control the pitch of the individual blades. The actuation of the bars can be achieved by using high torque stepper or servo motors. These precise low and high amplitude outputs are specifically required for the cyclic and collective controls of the helicopter swashplate. The compliant swashplate mechanism can be fabricated as a single piece using an injection molding technique or by 3D printing. The mechanism is modeled by two similar vector loops in two different planes. The mathematical model of the plate motion and the forces on the mechanism links are developed and simulated using MATLAB and Simulink, and initial results are discussed in this paper. This mechanism would be applied to the helicopter directional control where the plate in the pitch-roll mechanism would serve as the swash plate of the helicopter.

This paper presents the development of a piezo-based three-degree-of-freedom (3-DOF), tripedal microrobotic platform that allows for unlimited travel with sub-micron precision over a planar surface. Compliant mechanical amplifiers are incorporated with each piezoelectric stack actuator to improve both the stroke and load-bearing capability of the platform. A forward kinematic model of the stage based on its tripedal leg architecture is derived for each stick-slip step cycle and inverted for feedforward control of the platform. A prototype is constructed using low-cost 3D-printing techniques. Experimental results demonstrate actuator stroke of 29.4 μm on average with a dominant resonance of approximately 860 Hz. Results demonstrate the stage tracks a 3 mm by 3 mm square trajectory in open loop. Feedback control through visual servoing is then simulated on a model that includes flexure dynamics, observed surface interactions, and camera sampling times, reducing the root-mean-square (RMS) tracking error by 90%. This control scheme is then implemented experimentally, resulting in 99% RMS position error reduction relative to when only feedforward control is used.

Take home lab equipment and hands-on learning tools are still in demand for control theory and vibrations courses. The existing equipment are extremely expensive and require wide lab space. The aim of this research is to build vibratory mechanical system that is compact, modular and small scale so that each student can work on their setup and take it home if necessary. For this purpose, in this study, a semi-compliant mechanism is designed to be utilized in systems control and vibrations courses which would enhance the understanding of students by using experimental demonstration of the theoretical systems. The superiorities of the design over commercially available equipment are their low cost and simplicity. A parallel arm mechanism consisting of several flexible links that can be attached at different points on the slider is designed, finite element analysis (FEA) is performed in Solidworks, and the flexible beams are 3D printed using polyactic acid (PLA) and Polyethylene terephthalate glycol-modified (PETG) filaments. Different configurations of the mechanism are explored by changing the number of flexible beams attached to the slider. The mathematical model of the proposed mechanism can be represented by a single mass and multiple springs in parallel. Since mass is a known property, the equivalent stiffness can be experimentally found from the frequency analysis of free response. For this purpose, a PCB model tri-axial accelerometer is attached to the slider and the equations of motion are derived from the analysis of frequency characteristics of the complaint dual arm mechanism for each configuration. System properties including the equivalent friction are obtained from the acceleration vs time data using logarithmic decrement. The forced response is studied by attaching a load to the mass through a pulley system. The load deflection curve is obtained experimentally from LabVIEW. Since the system parameters are obtained from the free response, Matlab Simulink model outputs for the same initial displacement and force input are verified with the experimental data.

Control of deposition geometry is critical for repair and fabrication of complex components through directed energy deposition (DED). However, current limited sensing technology is often one of the bottlenecks that make it difficult to implement a real-time, measurement-feedback control of build geometry. Hence, this paper proposes to implement the control trajectories from a model-based, simulated-output feedback controller (where the controller uses simulated rather than measured outputs for feedback) as a feed-forward controller in a real DED process. We illustrate the effectiveness of such feed-forward implementation of a model-based, simulated-output feedback controller in the height control of a L-shaped structure via varying laser power in a DED process. Experimental validation shows that by applying the proposed feed-forward controller for laser power, the resulting build has (30%–50%) increased accuracy in achieving the target build height than applying laser with constant power or experience-based, hatch-dependent laser power. Results in this paper indicate that applying a simulated-output feedback controller could be a practical alternative for the control of DED (or other additive manufacturing processes) before the sensing technologies are matured enough to support real-time, measurement-feedback controller.

3D printing is a diverse field, in particular for biological or bioengineering applications. As a result, research teams working in this area are often multidisciplinary. A (bio) 3D printer in this research environment should balance performance with ease of use in order to enable system adjustments and operation for all machine users from a wide range of disciplines. This work presents results in the development of an easy-to-use fabrication system capable of producing rectilinear bone scaffolds. Common motion control problems, which are barriers to ease of use, are addressed and implemented in a way that researchers outside of the controls field could easily understand. A dynamic model of a 3-stage position system for bone scaffold fabrication is presented. Further, control design for a feedforward plus feedback controller and a user-friendly ILC feedforward compensator is outlined. The ability of the (bio) 3D printer to print bone scaffolds and the effectiveness of the control architecture is demonstrated.

Recent advances in flexible and wireless sensors, soft materials, and additive manufacturing, have stimulated demands for developing intelligent systems that can achieve multidisciplinary objectives (e.g., mechanical strength, thermal conductivity, state and input estimation, controllability, and others). Existing studies often decouple these objectives through sub-system level design, e.g., topology and material design for mechanical and thermal properties, and filter and sensor/actuator design for observability and controllability, assuming that the sub-systems have minimal influences to each others. To investigate the validity of this assumption, we take a unique angle at studying how the topology of the system influences both structural performance (e.g., compliance under static loads) and input observability (e.g., the error in estimating the loads). We reveal a tradeoff between these two objectives and derive the Pareto frontier with respect to the topology. This preliminary result suggests the necessity of a multiobjective formulation for designing intelligent structures, when significant tradeoffs among system objectives exist.