Closed-loop Control Architecture Research Articles

Application of Lock-in Amplifier Technique in Signal Blind Source Separation

Abstract In the realm of signal processing, frequency error stands as a critical challenge that cannot be overlooked, particularly in scenarios characterized by noise disturbances and constantly changing environmental variables, as it significantly undermines the precision of waveform separation. Faced with a spectrum of frequency error phenomena stemming from hardware instability, such as clock drift, transmission distortion, and environmental changes, this paper proposes a waveform separation scheme centered around a core closed-loop control architecture aimed at addressing such challenges. Leveraging the high-performance STM32F407 microcontroller platform, the system harnesses the powerful algorithmic advantages of Fast Fourier Transform (FFT) to precisely locate and delineate the spectral characteristics of signals. Furthermore, we creatively integrate lock-in amplifier technology into the meticulously designed closed-loop control system, coupled with state-of-the-art zero-crossing detection algorithms for in-depth optimization. The research findings demonstrate outstanding signal-to-noise ratio performance within predefined target frequency bands for the separation device based on lock-in amplifier technology, showcasing not only remarkable resilience against interference but also the ability to accurately separate and reconstruct target signal components with high fidelity from complex and dynamic signal environments. This significantly enhances the robustness and accuracy of the entire system.

A Hybrid Method Combining Data-Driven and Model-Based Algorithms for External Force-Sensing and Haptics Control of Cable-Pulley-Driven Surgical Robotic Manipulator

Abstract The implementation of the high-precision tracking control and external force-sensing ability of a manipulator is important for achieving refined surgical robot operation. In this paper, a hybrid method based on data-driven and model-based algorithms is proposed for the manipulator of a cable-pulley-driven surgical robot. This method integrates an artificial neural network and a dynamic model rotation angle estimation, and a full closed-loop control architecture is further constructed. The algorithm compensates for the hysteresis of the joint angle and effectively improves the tracking control precision. Based on the architecture, the external force estimator (EFE) using a joint torque disturbance observer and the force interaction teleoperation control strategy using a direct force feedback framework (DFF) are implemented. In the force loading experiment, it was shown that the EFE performs well for static and dynamic force estimation, and the teleoperated haptic control experiment showed that the DFF-EFE-based system has a high position-tracking accuracy with real-time external force-sensing ability.

Dynamic Risk Assessment and Control Framework for Work Zone and Its First Implementation under Simulation Environment

The number of road maintenance operations in China is increasing. Work zones can interfere with everyday driving and bring significant safety hazards to the throughput vehicles and construction personnel. However, there is currently a lack of effective methods to conduct a dynamic risk assessment of work zones and provide control guidance when necessary. Therefore, this study proposes a dynamic risk assessment and control framework for the work zones. The framework adopts a closed-loop control and dynamic monitoring architecture. A massive amount of microscopic data on vehicles’ behavior is obtained based on advanced data collection technologies (including multicamera multiobject tracking, naturalistic driving, and microscopic traffic simulation). Traffic conflicts between single vehicle and two- or multivehicle are detected using vehicle behavior analyzing technology and the surrogate safety assessment model. A comprehensive assessment index, i.e., UTECN (unit total equivalent conflict number), is established that can consider the severity and possibility of accidents caused by conflicts based on the vehicle collision energy theory, probability theory, and risk management theory. A risk assessment standard is established based on the level of safety service. The framework is first implemented in a simulation environment, and its feasibility and effectiveness are verified by taking a work zone of Shanghai Waihuan Expressway S20 as a case study. The result shows that the framework has good practicality. Under a moderate traffic level, the risk of the work zone can be assessed within 20 minutes. It can be quickly and effectively controlled at an acceptable level after several iterations, which is of great significance for ensuring the safety of life and property of throughput vehicles and construction personnel within the work zone.

Modelling and model-based tracking control of soft twisted and coiled actuators

Soft twisted and coiled actuators (STCAs) have promising prospects for application in the field of soft-bodied robots. However, the STCA has a complex energy conversion mechanism and a rate-dependent hysteresis nonlinearity, which brings great difficulties to its modelling and control. To solve these difficulties, this paper proposes modelling and model-based tracking control methods to realize the high-precision output-force tracking control of the STCA. First, a dynamics model framework is constructed, which consists of a thermo-electric model and a thermo-mechanical model, to describe the current-to-force process of the STCA. Among which, the thermo-mechanical model is established by combining the Bouc–Wen model and the linear dynamic system in series, which can accurately describe the rate-dependent hysteresis nonlinearity of the STCA. Then, a double closed-loop control architecture with a hysteresis inverse compensation controller is proposed, which can realize the timely control of the temperature and the compensation for the rate-dependent hysteresis nonlinearity of the STCA. Next, controller parameters are adjusted in the simulation environment to reduce the risk of the damage of the STCA and to obtain a satisfactory control effect. Finally, practical experiments are conducted, and root mean square errors of all experiment results are all less than 5.01%, which verifies the effectiveness of the proposed modelling and control methods.

Elastic Response of Lifting Type Reentry Vehicles under Closed Loop Control

Present paper discusses the modeling, dynamics and closed loop aeroservoelastic analysis of a typical lifting type reentry vehicle. A linear aeroservoelastic formulation for a lifting type reentry vehicle is presented, which is based on the reduced order modeling approach, using the principle of superposition. The aeroservoelastic problem is formulated in the time domain by converting frequency domain unsteady aerodynamic loads, using pure lag-pole based rational function approximation. Second order actuator and third order sensor models are included in the closed loop control architecture, that uses full state feedback pole placement technique (for level-1 flying qualities) to arrive at control gains. The study brings out the effect of closed loop command on the elastic response of a typical lifting type reentry vehicle.

Solid-State Transformer Based on Naturally Cell Balanced Series Resonant Converter With Cascaded H-Bridge Cells Switched at Grid Frequency

This paper proposes a closed-loop control architecture for a three-stage (MV, isolated DC/DC, LV) Solid State Transformer (SST) system and a modulation technique for the MV stage that shows better performance over existing solutions in terms of control simplicity, semiconductor loss, and cost. A simple and effective closed-loop control architecture is proposed for the entire SST system using the natural cell balancing ability of the Series Resonant Dual Active Bridge (SRDAB) converters in the DC/DC stage. In order to reduce semiconductor losses and cost, Si IGBT and SiC MOSFET devices are introduced properly in the MV stage of the SST power architecture, and the proposed modulation technique switches these devices appropriately according to their merits. The proposed modulation scheme ensures more than 50% semiconductor loss reduction in the MV stage. A circulating logic is proposed to achieve equal power sharing among cells in the MV stage and associated components. Detailed dynamic modeling, closed-loop control architecture, and modulation scheme are discussed in this paper. The proposed control technique and modulation scheme are verified experimentally in a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{600}~V/100~V, \text{5}~kW$</tex-math></inline-formula> SST system.

A Novel Flight Dynamics Modeling Using Robust Support Vector Regression against Adversarial Attacks

&lt;div&gt;An accurate Unmanned Aerial System (UAS) Flight Dynamics Model (FDM) allows us to design its efficient controller in early development phases and to increase safety while reducing costs. Flight tests are normally conducted for a pre-established number of flight conditions, and then mathematical methods are used to obtain the FDM for the entire flight envelope. For our UAS-S4 Ehecatl, 216 local FDMs corresponding to different flight conditions were utilized to create its Local Linear Scheduled Flight Dynamics Model (LLS-FDM). The initial flight envelope data containing 216 local FDMs was further augmented using interpolation and extrapolation methodologies, thus increasing the number of trimmed local FDMs of up to 3,642. Relying on this augmented dataset, the Support Vector Machine (SVM) methodology was used as a benchmarking regression algorithm due to its excellent performance when training samples could not be separated linearly. The trained Support Vector Regression (SVR) predicted the FDM for the entire flight envelope. Although the SVR-FDM showed excellent performance, it remained vulnerable to adversarial attacks. Hence, we modified it using an adversarial retraining defense algorithm by transforming it into a Robust SVR-FDM. For validation studies, the quality of predicted UAS-S4 FDM was evaluated based on the Root Locus diagram. The closeness of predicted eigenvalues to the original eigenvalues confirmed the high accuracy of the UAS-S4 SVR-FDM. The SVR prediction accuracy was evaluated at 216 flight conditions, for different numbers of neighbors, and a variety of kernel functions were also considered. In addition, the regression performance was analyzed based on the step response of state variables in the closed-loop control architecture. The SVR-FDM provided the shortest rise time and settling time, but it failed when adversarial attacks were imposed on the SVR. The Robust-SVR-FDM step response properties showed that it could provide more accurate results than the LLS-FDM approach while protecting the controller from adversarial attacks.&lt;/div&gt;

Discrete Cosserat Static Model-Based Control of Soft Manipulator

In this letter, the continuous Cosserat static model is re-formulated by employing the piecewise linear strain (PLS) approach, which can obtain the analytic formula of the model to facilitate the controller design. The robust closed-loop control architecture based on the PLSCosserat static model for the soft arm around its workspace is then established. To validate the performance of the proposed model-based control scheme, the point-to-point and time-varying trajectory tracking experiments under external disturbances have been conducted on the soft manipulator actuated by cables.

Development of a morphing UAV for optimal multi-segment mission performance

AbstractThe need for innovative solutions to enable aerial platforms to fly faster, higher, and longer continues to remain a primary focus for airframe designers. This paper outlines work undertaken to apply a morphing wing warping technology onto a generic Unmanned Aerial Vehicle to deliver enhanced flight performance, efficiency and control capabilities. The prototype employs wings of novel construction which provide both near resistance-free compliance in twist as well as adequate structural stiffness to resist applied loads; all while preserving an aerodynamically smooth surface. Used in combination with developed and integrated closed-loop feedback control architecture, a real-time, non-linear, span-wise wing twist adjustment capability required for optimised flight under differing operating conditions and flight requirements, is demonstrated. Experimental results obtained from a wind tunnel test program show up to a 72% increase in lift to drag ratio under certain conditions compared to a fixed baseline providing some confidence that the combination could be used to realise a step change in flight performance.

A closed-loop control architecture of UAV and WSN for traffic surveillance on highways

Excessive speed is the leading cause of accidents on highways. The use of fixed road-side surveillance systems has proven ineffective because people take caution around only those locations. With more advanced technologies and exceptional maneuvering capabilities, Unmanned Aerial Vehicles (UAVs) is a promising candidate for real-time monitoring of vehicles on the highways. The dependency of recently proposed UAV-based architectures on terrestrial networks suffers from high deployment costs. To address this shortcoming, we propose a unique closed-loop control architecture for traffic surveillance on highways that increases the surveillance effectiveness and adapts according to varying traffic patterns. The proposed scheme is comprised of Wireless Sensor Network (WSN) and UAV, named Collaborative Highway Surveillance (CHS), that works without human intervention and enables the capture of over-speeding drivers on a highway. The WSN provides routing services to the UAV and dynamically guides UAV to the best hotspot to position itself. If any vehicle exceeds the speed limit allowed, the UAV immediately informs this event to the Mobile Base Station (MBS). However, to conserve the energy resources of the WSN, low-level speed violations are forwarded to the MBS only when the UAV gets closer to the MBS. Performance results obtained with our proposed architecture show an increase in surveillance efficiency with an improved response time compared with cooperative and stand-alone unguided UAV networks.

Integration and Testing of a High-Torque Servo-Driven Joint and Its Electronic Controller with Application in a Prototype Upper Limb Exoskeleton.

Mechatronic systems that allow motorized activation in robotic exoskeletons have evolved according to their specific applications and the characteristics of the actuation system, including parameters such as size, mechanical properties, efficiency, and power draw. Additionally, different control strategies and methods could be implemented in various electronic devices to improve the performance and usability of these devices, which is desirable in any application. This paper proposes the integration and testing of a high-torque, servo-driven joint and its electronic controller, exposing its use in a robotic exoskeleton prototype as a case study. Following a brief background review, the development and implementation of the proposal are presented, allowing the control of the servo-driven joint in terms of torque, rotational velocity, and position through a straightforward, closed-loop control architecture. Additionally, the stability and performance of the servo-driven joint were assessed with and without load. In conclusion and based on the obtained results, the servo-driven joint and its control system demonstrate consistent performance under the proposed test protocol (max values: angular velocity 97 °/s, torque 33 Nm, positioning RMSE 1.46°), enabling this approach for use in various applications related to robotic exoskeletons, including human performance enhancement, rehabilitation, or support for daily living activities.

Development of a model predictive controller for an active torsional vibration damper to suppress torsional vibrations in vehicle powertrains

The pressure of exhaust emission regulations on automotive manufacturers to reduce environmental pollution and fuel consumption of internal combustion engines (ICEs) have stimulated the works on the downsizing, downspeeding, and turbo supercharging concepts which result in boosted engine torsional vibrations. Despite significant momentum in the implementation of those concepts in modern ICEs in recent decades, similar progress has not taken place in parallel at torsional vibration isolation systems. To this end, this article centers on the development and implementation of a model predictive controller (MPC) on a novel active torsional vibration damper (ATVD) in which inertia, stiffness rate, and damping rate parameters can be varied to minimize torsional vibration transmission to the vehicle powertrain. Dynamic response of the ATVD is examined using an MPC inside a closed-loop control architecture with predicted variables. The MPC structure, state-space plant model, and physical constraint definitions are composed to be utilized in prediction models at various engine operating points. The MPC performance is evaluated in a co-simulation environment using Simcenter Amesim, NX Motion, and Matlab Simulink software, and are compared with that of the fuzzy logic controller (FLC). The simulation results clearly indicate that the MPC applied to the ATVD system has certain advantages over the FLC and is able to provide satisfactory isolation of the powertrain from engine-borne torsional vibrations while satisfying the physical constraints.

Development of a control architecture for a parallel three-axis robotic arm mechanism using CANopen communication protocol

Based upon the CANopen communication protocol and the LabVIEW graphic programing procedures, this paper develops a closed-loop control architecture for a parallel three-axis (Delta) robotic arm mechanism. The accomplishments include prototyping a parallel three-axis robotic arm mechanism, assembling servomotors with associated encoders and gearsets, coding CANopen communication scripts for servomotor controllers and a host supervision GUI, coding forward/inverse kinematics scripts to compute the required servomotor rotations and the coordinates of a movable platform or the mechanism, coding tracking error compensation scripts for effective closed-loop griper control, and coding integration scripts to command and supervise the mechanism motion on the LabVIEW-based host GUI. During the development stage, this research designed and prototyped the parallel three-axis robotic arm mechanism based upon basic Delta robot kinematics. To control the mechanism effectively and accurately, this study implemented the CANopen communication protocol, which characterizes high speed and stable transmission. The protocol applies to the CANopen communication channels among the controllers and the host supervision GUI. On the LabVIEW development platform, the coded supervision GUI performs issuing/receiving messages to the CANopen-based controllers. The controllers excite the servomotors and actuate the parallel mechanism to track prescribed trajectories in a closed-loop control fashion. Meanwhile, an electromagnet attached to the movable platform of the robotic mechanism performs satisfactory picking/placing object actions.

Smith-Predictor-Based Torque Control of a Rolling Diaphragm Hydrostatic Transmission

Rolling Diaphragm Hydrostatic Transmissions (RDHT) are high-performance low-cost solutions to delocalize heavy actuators away from the joints of robotic systems. Exploiting a low-cost pressure-based sensing technique, we propose here a Smith-predictor-based joint torque control of an RDHT-based actuation system. We also use a load-cell sensor for ground truth validation. The developed feedback controller is conveniently tuned based on an arbitrary pre-specified closed-loop natural frequency and damping ratio. This preserves the open-loop bandwidth while removing the intrinsic oscillations of the lightly damped highly transparent open-loop plant. Experimental tests validate the proposed control strategy, both in a stand-alone torque setpoint configuration and in a series of Human-Robot-Interaction tests confirming the significant advantages of the closed-loop control architecture.

Spiking neural state machine for gait frequency entrainment in a flexible modular robot

We propose a modular architecture for neuromorphic closed-loop control based on bistable relaxation oscillator modules consisting of three spiking neurons each. Like its biological prototypes, this basic component is robust to parameter variation but can be modulated by external inputs. By combining these modules, we can construct a neural state machine capable of generating the cyclic or repetitive behaviors necessary for legged locomotion. A concrete case study for the approach is provided by a modular robot constructed from flexible plastic volumetric pixels, in which we produce a forward crawling gait entrained to the natural frequency of the robot by a minimal system of twelve neurons organized into four modules.

Lithographic mask defects mitigation on a multimode interference structure

Over the last decades, the lithographic technology has greatly contributed for the confirmation of Moore's law in the semiconductor industry. Key developments in lithography such as the operational wavelength decreasing, together with a performance increase in lens and imaging technology, enabled the reduction of cost per function in integrated circuits technology. In this work, the impact of lithographic defects introduced by the manufacturing process is analyzed through simulations and two mitigation techniques are presented. These perturbations are a consequence of the limited lithographic mask resolution reflected on deviations from the geometry of the ideal device. For this purpose, the Beam Propagation and Finite Differences Time Domain methods have been used to simulate a multi-mode interference structure based on silicon nitride. The structure is affected by random perturbations and the obtained results revealed a strong dependence between mask resolution, and imbalance and power loss. Two strategies have been followed concerning the mitigation of power loss and imbalance: - Access waveguides tapering and adjustable power splitting ratios through the electro-optic effect. Both strategies revealed results that indicate an improvement on device’s performance. However, once built, the former is a static design that favors indiscriminately all propagating modes in the multimode section. In the latter, finer tuning capabilities targeting different propagating modes may be enabled by dynamic compensation of power loss and imbalance, when in a closed loop control architecture. Such a control architecture may operate by sampling the output waveguides, extracting the error signal and, finally, negatively feeding it back to the electrooptic effect system, hence improving imbalance and power loss.

Interconnected Pressure Estimation and Double Closed-Loop Cascade Control for an Integrated Electrohydraulic Brake System

In this article, a novel double closed-loop cascade control architecture with interconnected pressure estimation for a pressure-sensor-unequipped integrated electrohydraulic brake system suitable for automobile applications is presented. Starting from a control-oriented model, an interconnected pressure estimator is employed to estimate the pressure dealing with the nonlinear pressure-position relationship. To reduce the negative influence of system nonlinearities and uncertainties, i.e., friction, pressure-position relationship, brake pad wear, temperature variation, knockoff, a double closed-loop cascade controller is proposed. An outer pressure tracking loop employs sliding mode controller (SMC) with conditional integrator to ensure tracking accuracy with desired position of master cylinder piston as control output; an inner position control loop is designed using the SMC to improve the response speed. By this way, the bandwidth of inner position is wider than the outer pressure loop, which has advantages in quickly eliminating the disturbances caused by system nonlinearities and uncertainties. The overall system asymptotic stability is analytically investigated through the Lyapunov Theorem. Simulation and experimental validation demonstrate excellent tracking performance and robustness.

Reference Trajectory Generation for Closed-Loop Control of Electrical Stimulation for Rehabilitation of Upper Limb

Functional movements in the paralyzed upper limb can be restored with the help of brain-computer-interface (BCI). A BCI system typically adopts a functional electrical stimulation (FES) system that activates weakened muscles that are otherwise responsible for actuating finger movements. A BCI-FES system can enable muscle contraction through the delivery of electrical stimulation pulses. The control of voltage or current stimulation parameters such as pulse width, frequency, and amplitude along with feedback signals from finger joints positions are essential for stable grasping. For the design of a closed-loop functional electrical stimulation controller, it is obligatory to set standard reference trajectories of finger joints’ angular positions and velocities for controlling stimulation parameters in neuroprosthetics and rehabilitation. This study proposes a new closed-loop control architecture targeted for achieving successful and stable grasping of an upper limb paralyzed subject. This can be achieved by characterizing each of the finger joints’ instantaneous angular position and velocity, through reference trajectories. These reference trajectories are generated corresponding to various types of grasping for feeding to the controller, responsible for stimulation of muscles. Hence, to generate such trajectories, first, grasping classification has been implemented using standard machine learning algorithms on a large set of existing real-time data of different types of objects’ grasping such as various diameter, abducted thumb and other types of objects, from many healthy subjects. The results demonstrate the successful implementation of fairly accurate classifications and trajectory generations which are crucial for closed-loop control towards stable grasping.

Smoothing Tie-Line Power Fluctuations for Industrial Microgrids by Demand Side Control: An Output Regulation Approach

This paper investigates the problem of how to effectively smooth the short-term tie-line power fluctuations for grid-connected industrial microgrids (IMGs) from demand side. A wide-area closed-loop control architecture is proposed by directly and continuously modulating load power consumption, e.g., the aluminum electrolysis load. To optimally design the load smoothing controllers, an output regulation approach combined with LQ optimal control is developed. In particular, dominant frequencies of wind power fluctuations are analyzed and incorporated into the exogenous system that models time-varying disturbances. Simulations are conducted for a real industrial microgrid in the Inner Mongolia, China, to validate the practical feasibility and effectiveness of the proposed smoothing control strategy. It is demonstrated that the demand side control based on output regulation is able to achieve not only zero steady error in rejecting the time-varying wind power disturbance but also guarantee the satisfactory dynamic performance of modulated loads for the grid-connected IMG.

AUV Adaptive Sampling Methods: A Review

Autonomous underwater vehicles (AUVs) are unmanned marine robots that have been used for a broad range of oceanographic missions. They are programmed to perform at various levels of autonomy, including autonomous behaviours and intelligent behaviours. Adaptive sampling is one class of intelligent behaviour that allows the vehicle to autonomously make decisions during a mission in response to environment changes and vehicle state changes. Having a closed-loop control architecture, an AUV can perceive the environment, interpret the data and take follow-up measures. Thus, the mission plan can be modified, sampling criteria can be adjusted, and target features can be traced. This paper presents an overview of existing adaptive sampling techniques. Included are adaptive mission uses and underlying methods for perception, interpretation and reaction to underwater phenomena in AUV operations. The potential for future research in adaptive missions is discussed.