Position Tracking Research Articles

Hierarchical approximate optimal interaction control of human-centered modular robot manipulator systems: A Stackelberg differential game-based approach

A Stackelberg game-based approximate optimal interaction control approach is presented for human-centered modular robot manipulator (MRM) systems. Joint torque feedback (JTF) technique is utilized to form the MRM dynamic model. The major objective of optimal control with human–robot collaboration (HRC) is transformed into approximating Stackelberg equilibrium by adopting Stackelberg game governed between the human and the MRM that are regarded as players with different hierarchical level in interaction process. On the basis of the adaptive dynamic programming (ADP), the approximate optimal interaction control policy with HRC task is developed via critic neural network (NN)-based Stackelberg game manner for addressing Hamilton–Jacobian (HJ) equations. The position tracking error is ultimately uniformly bounded (UUB) according to the Lyapunov theory. Experiment results demonstrate the effectiveness of the proposed method.

Comparative Analysis of Force and Eddy Current Position Sensing Approaches for a Magnetic Levitation Platform with an Exceptional Hovering Distance

This paper provides a comparative analysis between a force sensor and an eddy current sensor, focusing on their usability to determine the position of a circular levitating permanent magnet (PM) mover within an axially symmetric magnetic levitation platform (MLP) with an exceptionally large air gap. The sensors enable closed-loop control, which is essential for accurately and stably maintaining the mover’s radial position. For the considered MLP, a change in radial position in principle results in a tilting of the mover, i.e., a deviation from the parallel alignment relative to the stator. As both the radial position and the tilting angle affect the sensors’ (force and eddy current) output voltage, an observer must deduce the radial position from the output sensor’s voltage, requiring a comprehensive MLP dynamic model and calibration of the models for both sensing approaches. The paper discusses the advantages and weaknesses of each sensor concept, exploring operational principles and performance in levitation tests. The force sensor exhibits versatility, proving functional across various application scenarios, such as when the mover is sealed in a conductive, non-magnetic chamber. In contrast, due to its high-frequency operation, the eddy current sensor is more straightforward to characterize, simplifying its behavior relative to the mover’s slower dynamics. Measurements are conducted to validate the models, showing the eddy current sensor’s robustness against disturbances and imperfections in the MLPs and its immunity to cross-axis interference. Conclusively, in levitation experiments where the mover is vertically distanced at 104 mm from the stator, the eddy current sensor achieves a position tracking precision about ten times better and a signal-to-noise ratio (SNR) ten times higher compared to the off-the-shelf force sensor, confirming its better performance and reliability; however, it cannot be used in applications where conductive objects are present in the air gap. Furthermore, additional experiments are conducted on the MLP using the eddy current sensor to show the controller’s robustness and dynamic reference tracking capability, with and without a payload.

Simplified Indoor Localization Using Bluetooth Beacons and Received Signal Strength Fingerprinting with Smartwatch.

Variations in Global Positioning Systems (GPSs) have been used for tracking users' locations. However, when location tracking is needed for an indoor space, such as a house or building, then an alternative means of precise position tracking may be required because GPS signals can be severely attenuated or completely blocked. In our approach to indoor positioning, we developed an indoor localization system that minimizes the amount of effort and cost needed by the end user to put the system to use. This indoor localization system detects the user's room-level location within a house or indoor space in which the system has been installed. We combine the use of Bluetooth Low Energy beacons and a smartwatch Bluetooth scanner to determine which room the user is located in. Our system has been developed specifically to create a low-complexity localization system using the Nearest Neighbor algorithm and a moving average filter to improve results. We evaluated our system across a household under two different operating conditions: first, using three rooms in the house, and then using five rooms. The system was able to achieve an overall accuracy of 85.9% when testing in three rooms and 92.106% across five rooms. Accuracy also varied by region, with most of the regions performing above 96% accuracy, and most false-positive incidents occurring within transitory areas between regions. By reducing the amount of processing used by our approach, the end-user is able to use other applications and services on the smartwatch concurrently.

Combined longitudinal and lateral dynamics regulation of autonomous vehicles via induced ℒ2$$ {\mathcal{L}}_2 $$‐gain linear parameter varying control strategies based on parameter‐dependent Lyapunov functions

AbstractThis article considers a path tracking control problem for autonomous vehicles constrained to maintain a safe distance from the next vehicle in the lane. The control design problem is solved by considering a mathematical model of the vehicle that jointly describes the lateral and longitudinal dynamics. Specifically, the optimal controller is designed aimed at minimizing the orientation and position tracking errors with respect to a given reference path. Moreover, the controller is able to ensure that the vehicle can both follow a speed profile and automatically adjusts the vehicle speed to maintain a proper distance from the next vehicle. The lateral dynamic is regulated by a 2‐DOF feedforward/feedback controller, where the feedforward law is implemented by exploiting an inverse kinematic model of the vehicle. On the other side, the feedback action, along with the action of the controller in charge to regulate the longitudinal dynamics, is the optimal gain‐scheduling state‐feedback controller. In particular, a parameter‐dependent quadratic Lyapunov function approach is used to reduce the conservativeness of the solution and a suitable convex LMI optimization problem is formulated for the synthesis. The vehicle is described by a seven‐degrees‐of‐freedom (7DOF) full‐car model, with the tire‐generated forces described by the classical Pacejka's Magic Formula. In order to assess the performance of the proposed control strategy, simulations have been undertaken in Matlab/Simulink by considering an autonomous vehicle driving into an urban scenario.

The Adaptive Bilateral Control of Underwater Manipulator Teleoperation System with Uncertain Parameters and External Disturbance

A novel self-adaptive bilateral control strategy is introduced to manage uncertainties inherent in the teleoperation of an underwater manipulator system effectively. In response to uncertainties stemming from both the mathematical model and external disturbances, our approach offers innovative solutions. Firstly, to address uncertainties in the master model parameters, we propose a reference adaptive impedance control based on a nominal model. This control strategy dynamically adjusts the reference position of the desired model, leveraging adaptive control laws to compensate for model uncertainties. Additionally, to tackle uncertainties specific to the slave manipulator, we employ adaptive compensation using radial basis function (RBF) networks. Our unique combination of sliding mode variable structure controllers and robust adaptive controllers aims to mitigate approximation errors, ensuring precise tracking of the master manipulator’s position by the slave manipulator. By employing Lyapunov function analysis, we demonstrate the system’s superior tracking performance and global stability, with assured asymptotic convergence for force–position tracking. Through comprehensive experimentation, our results showcase the exceptional force–position tracking capabilities of the overall control system, even under challenging conditions of model uncertainties and external disturbances. Moreover, our system exhibits remarkable stability, reliability, and robustness, underscoring the effectiveness of our proposed adaptive control approach.

Dynamic Automation of a Moving Vehicle at Real time along with Position and Condition Tracking

The present work deals with real-time database updation of moving vehicle through dynamic automation system, where position and internal conditions of the car are auto-saved in the cloud server. The total embedded system is a simulated prototype, already implemented virtually for smaller distance movement on suitable road condition, where the auto-checking of the fuel remained shows the novelty of the system compared to the existing data available in literature. As evident form experimental results, soil moistures sensor detects the road condition, whereas ultrasonic helps to reduce the accident probability with real-time tracking. Humidity and temperature sensors also give real-time environmental condition outside the car which is crucial while driving at extreme climatic condition. Insurance companies as beneficiaries also check the status of it if the car is suffered from accidents or unnecessary external coercive influences. Data display facility is available at real time to avoid any unwanted proximity with nearby moving/standing objects, and later can be retrieved from the secured database. The work may be extended as a complete autonomous tracker with condition monitor in future automobile industry.

Robust adaptive control for a class of autonomous vehicle platoons

SummaryThis article studies robust adaptive control for a class of autonomous vehicle platoons. In particular, two innovative adaptive control laws are proposed to address both position and velocity tracking for a vehicle platoon. In addition, it is shown that robust asymptotic string stability can be delivered by the underlying adaptive control laws for the vehicle platoon, in the sense that these adaptive control laws are capable of mitigating parameter uncertainties involved in the nonlinear vehicular dynamics and achieving truly cooperative adaptive cruise control while ensuring the required safety spacing between each neighboring vehicle pair asymptotically. It is also shown that the control performance of the vehicle platoon can be further improved if the operating equilibrium points of all vehicles can be adaptively estimated, leading to two linear time‐invariant control laws for individual vehicles under both position and velocity controls and for the vehicle platoon. Simulation studies illustrate the effectiveness of the proposed control method, validating the results obtained for the class of vehicle platoons.

Computational methodology to support functional vision assessment in premature infants: A viability study.

Premature newborns have a higher risk of abnormal visual development and visual impairment. To develop a computational methodology to help assess functional vision in premature infants by tracking iris distances. This experimental study was carried out with children up to two years old. A pattern of image capture with the visual stimulus was proposed to evaluate visual functions of vertical and horizontal visual tracking, visual field, vestibulo-ocular reflex, and fixation. The participants' visual responses were filmed to compose a dataset and develop a detection algorithm using the OpenCV library allied with FaceMesh for the detection and selection of the face, detection of specific facial points and tracking of the iris positions is done. A feasibility study was also conducted from the videos processed by the software. Forty-one children of different ages and diagnoses participated in the experimental study, forming a robust dataset. The software resulted in the tracking of iris positions during visual function evaluation stimuli. Furthermore, in the feasibility study, 8 children participated, divided into Pre-term and Term groups. There was no statistical difference in any visual variable analyzed in the comparison between groups. The computational methodology developed was able to track the distances traveled by the iris, and thus can be used to help assess visual function in children.

Adaptive Active Disturbance Rejection Control for Vehicle Steer-by-Wire under Communication Time Delays

In this paper, an adaptive active disturbance rejection control is newly designed for precise angular steering position tracking of the uncertain and nonlinear SBW system with time delay communications. The proposed adaptive active disturbance rejection control comprises the following two elements: (1) An adaptive extended state observer and (2) an adaptive state error feedback controller. The adaptive extended state observer with adaptive gains is employed for estimating the unmeasured velocity, acceleration, and compound disturbance which consists of system parameter uncertainties, nonlinearities, exterior disturbances, and time delay in which the observer gains are dynamically adjusted based on the estimation error to enhance estimation performances. Based on the accurate estimations of the adaptive extended state observer, the proposed adaptive full state error feedback controller is equipped with variable gains driven by the tracking error to develop control precision. The integration of the advantages of the adaptive extended state observer and the adaptive full state error feedback controller can improve the dynamic transient and static steady-state effectiveness, respectively. To assess the superior performance of the proposed adaptive active disturbance rejection control, a comparative analysis is conducted between the proposed control scheme and the classical active disturbance rejection control in two different cases. It is worth noting that the active disturbance rejection control serves as a benchmark for evaluating the performance of the proposed control approach. The results from the comparison studies executing two simulated cases validate the superiority of the suggested control, in which estimation, tracking response rate, and steering angle precision are greatly improved by the scheme proposed in this article.

Trajectory tracking control of autonomous space-based simulators for the on-orbit assembly of large space optical telescopes

To enhance the precision of on-orbit assembly for large space optical telescopes, the control of attitude motion in the Autonomous Space-based Simulator (ASS) is imperative. This paper presents a robust finite-time trajectory tracking control method aimed at improving the position and attitude tracking performance of ASS. Considering the dynamic characteristics inherent in ASS, we introduce an improved non-singular fast terminal sliding mode controller (INFTSMC) incorporating an adaptive fuzzy mechanism to attain finite-time error convergence and robust control. The adaptive fuzzy logic control (AFLC) method yields an equivalent gain, eliminating discontinuous switching in terminal sliding mode control (TSMC). This reduction minimizes chattering in control inputs and compensates for uncertainties and time-varying disturbances within the dynamic model. The proposed method’s effectiveness is validated through comprehensive simulation and experimental studies.

High-Precision Position Tracking Control with a Hysteresis Observer Based on the Bouc–Wen Model for Smart Material-Actuated Systems

The Bouc–Wen model has been widely adopted to describe hysteresis nonlinearity in many smart material-actuated systems, such as piezoelectric actuators, shape memory alloy actuators, and magnetorheological dampers. For effective control design, it is of interest to estimate the hysteresis state that is not measurable. In this paper, the design of a state observer for the Bouc–Wen model is presented. It is shown that, with sufficiently high observer gains, the state estimate error, including that for the hysteresis state, converges to zero exponentially fast. The utility of the proposed hysteresis observer is illustrated in the design of a high precision output-feedback position tracking controller, and the resulting tracking error is shown to decay exponentially via Lyapunov analysis. Simulation and experimental results show that the proposed hysteresis observer and the high precision position tracking controller outperform a traditional extended state observer and the corresponding tracking controller, respectively.

Design and analysis of ELM-based predefined time sliding mode adaptive controller for PMLM position control under physical constraints

Achieving accurate position tracking for robotics and industrial servo systems is an extremely challenging task, particularly when dealing with control saturation, parameter perturbation, and external disturbance. To address these challenges, a predefined time convergent sliding mode adaptive controller (PTCSMAC) has been proposed for a permanent magnet linear motor (PMLM). A novel sliding mode surface (SMS) with predefined time convergence PDTC has been constructed, which ensures that the error converges to zero within the prescribed time. The system not only meets the expected performance standards but also has a uniformly bounded motor speed. The trajectory tracking error in SMS is proven to converge to zero within the predefined time. This predefined time stability of the closed-loop system has been demonstrated by using the Lyapunov stability criterion with PDTC. The convergence time (CT) can be arbitrarily set, and the upper bound of it is not affected by the initial value and control parameters of the system. A new updated version of extreme learning machine (ELM) is introduced to approximate the uncertain part of the system based on PDTC. The ELM is also provided with the hyperbolic tangent function to estimate the saturation constraint. This is done by converting the function into a linear function concerning the unconstrained control input variable. Then, based on established stability, a novel sliding mode adaptive controller (PTCSMAC) with predefined time convergence is designed. The convergence time (CT) of the controller is unaffected by the initial conditions as well as the control parameters. The rigorous numerical simulations on the PMLM model with complex disturbances verify the strong robustness and high-precision tracking characteristic of the proposed control law.

Analysis of Rotor Anisotropy and Position Tracking Error Prediction for Surface-Mounted PMSM Under High Frequency Signal Injection

Analysis of Rotor Anisotropy and Position Tracking Error Prediction for Surface-Mounted PMSM Under High Frequency Signal Injection

Virtual position predictive control with system delay observer to improve PMLSM position tracking accuracy

AbstractTo improve the position tracking accuracy of permanent magnet linear synchronous motors (PMLSM), this paper introduces a virtual position predictive control (VPPC) with a system delay observer (SDO). Un‐like conventional position predictive control (CPPC), which ignores the complexity of prediction models and velocity adjustments, the proposed VPPC combines a simplified position model with an active variable speed control. This design accelerates mover response and increases maximum reference speeds through active adjustments to better estimate the predicted output. Since the prediction period in CPPC often misaligns with the system delay, resulting in additional prediction errors, this paper further explores the relationship between predictive periods and system delay. Based on this analysis and a unified modelling concept, an SDO is included to observe and compensate for system delay, correcting the prediction period and optimising the control model. Experimental results on a PMLSM platform confirm the superior position tracking performance of the VPPC with SDO compared to conventional controllers.

The nonlinear model reference adaptive impedance control for underwater manipulator operation objects in bilateral teleoperation system

The bilateral teleoperation system is susceptible to model parameter uncertainty and unknown disturbances in both the master and slave manipulators, resulting in instability and inaccuracies in the force and position tracking performance. To address these issues, a novel nonlinear model reference adaptive impedance controller has been designed to achieve coordinated force and position synchronization of dual manipulators. The adaptive control laws, based on sliding mode functions, have been designed to compensate for the uncertainty of the manipulator model. Furthermore, an adaptive estimation law has been employed to appraise the unknown upper bound of external disturbances. This ensures that the closed-loop model parameters of the dual manipulator converge to the reference impedance model respectively. Simultaneously, it enables the position error between the reference model response and the end-effector task space position to asymptotically converge to zero. To verify the effectiveness of the proposed controller, simulations have been conducted on the MATLAB platform and experiments on a single degree of freedom teleoperation system have been performed. The results demonstrate that the controller exhibits strong robustness and has the capability of force-position tracking ability.

Impedance control for a Stewart‐structure‐based wheel‐legged robotic system in wheel motion

SummaryAn impedance control scheme is proposed for a Stewart‐structure‐based wheel‐legged robotic system to strengthen the dynamic attitude adjustment stability in wheel motion. The wheel‐leg, which is driven by electrical cylinders in the Stewart structure, is analyzed in kinematics and dynamics. The rotation in the axial direction of every electric cylinder is calculated to improve the accuracy of the kinematic model. To fulfill the impedance demands, a passive structure with 6 degrees of freedom (DOF) is modeled. The mass of the mechanism has a coupling effect on the impedance model for each DOF, which is a nonlinear function. As motion decoupling in the workspace has been completed for the Stewart structure, an impedance control strategy with inner‐loop position tracking is employed. An extended state observer (ESO) is designed to estimate the disturbances arising from the nonlinear coupling effects. Based on the ESO observation outputs, an active disturbance rejection control that explicitly handles the workspace limit is designed with guaranteed practical stability. By reducing force interaction and body vibration, the wheel‐legged robotic system keeps wheel motion stability on uneven roads. Multiple comparative experimental results are presented to validate the stability and effectiveness of the proposed method.

Control and Position Tracking for UAVs

There has been exponential development of UAV technology and related research areas such as artificial intelligence, which will raise UAVs’ ability for autonomous flights to a higher level [...]

Distributed Lyapunov-Based Model Predictive Control for AUV Formation Systems with Multiple Constraints

This paper focuses on the formation tracking issue of autonomous underwater vehicles (AUVs) subject to multiple constraints in three-dimensional space. We developed a novel distributed Lyapunov-based model predictive controller (DLMPC) with a fast finite-time extended state observer (FFTESO). Initially, the external disturbances and internal uncertainties of each AUV were precisely compensated using the designed FFTESO. Subsequently, we proposed DLMPC-based position tracking and velocity tracking controllers, which solved an online optimization problem to determine optimal velocities and control forces. This hierarchical framework effectively managed system constraints, such as state constraints and actuator saturation. Additionally, the Lyapunov-based backstepping control law was applied to construct stability constraints in the distributed optimization problem, ensuring the recursive feasibility and closed-loop system stability of the proposed scheme. Sufficient conditions and attraction regions to ensure stability were explicitly provided. Finally, the simulation results demonstrated that the proposed method improved both the convergence speed and tracking accuracy by at least 30% compared to other methods.

Modelling and characteristics analysis of an electro-hydraulic proportional valve with a discrete pilot stage for underwater hydraulic manipulators

As the harshness of the underwater operating environment and complexity of underwater tasks gradually increase, underwater hydraulic manipulators with high reliability and precision attract more research attention. To improve the reliability and dynamic performance of the traditional electro-hydraulic proportional valve (EHPV) used in the underwater hydraulic manipulator, an improved electro-hydraulic proportional valve with a discrete pilot stage (DEHPV) is proposed. In the pilot stage, two 2-position 3-way normally open high speed switching valves (HSVs) are used, and the initial oil spring stiffness in the control chamber is large enough to maintain the dynamic performance of the DEHPV. First, the working principle and configuration of the DEHPV are both given, and the coupled electric-magnetic-mechanical-fluid model of the DEHPV is presented. Moreover, a dual-valve hybrid pulse width modulation (DVHPWM) control strategy is proposed to improve the position tracking accuracy of the DEHPV. Furthermore, a co-simulation model of the DEHPV considering the multi-field coupling law is established to study the dynamic characteristics. Extensive experiments are carried out to verify the effectiveness of the proposed structure as well as its good dynamic performance and control accuracy.

Trajectory-Tracking Control for Quadrotors Using an Adaptive Integral Terminal Sliding Mode under External Disturbances

In the face of external disturbances affecting the trajectory tracking of quadrotors, a control scheme targeted at accurate position and attitude trajectory tracking was designed. Initially, a quadrotor dynamic model, essential for control design, was derived. Adaptive integral backstepping control (AIBS) was then employed within the position loop, enabling the upper boundaries of disturbances to be estimated through adaptive estimation. Subsequently, a new adaptive backstepping fast nonsingular integral terminal sliding mode control (ABFNITSM) was proposed to enable adherence to the desired Euler angles. Rapid convergence and accurate tracking were facilitated by the incorporation of the nonsingular terminal sliding mode and an integral component. The dead zone technique was deployed to curtail estimation errors, while a saturation function was used to eradicate the phenomenon of chattering. Finally, to validate the proposed control scheme, simulation experiments were conducted in the Simulink environment, and the results were contrasted with those obtained from traditional integral terminal sliding mode control (ITSM) and integral backstepping control (IBS), providing evidence of the effectiveness of the proposed method.