Model-based Compensation Research Articles

Enhancing boundary detection of radiofrequency ablation lesions through photoacoustic mapping

Atrial fibrillation (A-fib) is the most common type of heart arrhythmia, typically treated with radiofrequency catheter ablation to isolate the heart from abnormal electrical signals. Monitoring the formation of ablation-induced lesions is crucial for preventing recurrences and complications arising from excessive or insufficient ablation. Existing imaging modalities lack real-time feedback, and their intraoperative usage is in its early stages. A critical need exists for an imaging-based lesion indexing (LSI) method that directly reflects tissue necrosis formation. Previous studies have indicated that spectroscopic photoacoustic (sPA) imaging can differentiate ablated tissues from their non-ablated counterparts based on PA spectrum variation. In this paper, we introduce a method for detecting ablation lesion boundaries using sPA imaging. This approach utilizes ablation LSI, which quantifies the ratio between the signal from ablated tissue and the total tissue signal. We enhance boundary detection accuracy by adapting a regression model-based compensation. Additionally, the method was cross-validated with clinically used intraoperative monitoring parameters. The proposed method was validated with ex vivo porcine cardiac tissues with necrotic lesions created by different ablation durations. The PA-measured lesion size was compared with gross pathology. Statistical analysis demonstrates a strong correlation (R > 0.90) between the PA-detected lesion size and gross pathology. The PA-detected lesion size also exhibits a moderate to strong correlation (R > 0.75) with local impedance changes recorded during procedures. These results suggest that the introduced PA imaging-based LSI has great potential to be incorporated into the clinical workflow, guiding ablation procedures intraoperatively.

Improving Robotic Milling Performance through Active Damping of Low-Frequency Structural Modes

Industrial robots are increasingly prevalent due to their large workspace and cost-effectiveness. However, their limited static and dynamic stiffness can lead to issues like mode coupling chatter and regenerative chatter in robotic milling processes, even at shallow cutting depths. These problems significantly impact performance, product quality, tool longevity, and can damage robot components. An active inertial actuator was deployed at the milling spindle to enhance dynamic stiffness and suppress low-frequency vibrations effectively. It was identified that the characteristics of the actuator change with its mounting orientation, a common scenario in robotic machining processes. This variation has not been reported in the literature. Our study includes the identification of model parameters for the actuator in both horizontal and vertical mountings. Additionally, the novelty of the present work lies in the specific design and implementation of compensation filters tailored for the active inertial actuator in both horizontal and vertical configurations. These filters address the unique challenges posed by low-frequency vibrations in robotic milling, offering significant improvements in dynamic stiffness and vibration suppression. Traditional model-based compensators were effective for vertical mounting, while pole-zero placement techniques with minimum phase systems were optimal for horizontal mounting. These compensators significantly enhanced dynamic stiffness, reducing maximum low-frequency robot structural modes by approximately 100% in horizontal mounting and approximately 214% in the vertical configuration of the actuator. This advancement promises to enhance industrial robot capabilities across diverse machining applications.

Model-based compensation of a concave nonlinear hysteresis in the displacement electro-hydraulic servo system

Abstract Nonlinearity exerts a profound influence on the displacement performance of actuators within electro-hydraulic servo systems, particularly in the context of hysteresis. This article analyses a specific hysteresis responsible for control instability, a consequence of the concave-hysteresis loop, giving rise to a notable peak phenomenon in displacement. The behavior of the concave-hysteresis loop is studied in the step load experiment of a triaxial apparatus. Subsequently, an accurately formulated mathematical model utilizing a mathematical function is derived. Notably, the article introduces an efficacious model-based compensation algorithm that integrates nonlinear iteration and fuzzy control. This strategic approach effectively addresses the issue associated with calculating the inverse model when the sensor is located in a nonlinear, hook-shaped domain. Simulation and experimentation verified the concave-hysteresis loop model and the compensation algorithm. The experiment demonstrated the elimination of peak phenomena and a decrease in sensor error from 3.7 mm to below 0.5 mm.

Evaluation of data-driven NARX model based compensation for multi-axial real-time hybrid simulation benchmark study

Actuator control takes a pivotal role in achieving stability and accuracy, particularly in the context of multi-axial real-time hybrid simulation (maRTHS). In maRTHS, multiple hydraulic actuators are necessitated to apply precise motions to experimental substructures thus necessitating the application of multiple-input multiple-output (MIMO)control strategies. This study evaluates the data-driven nonlinear autoregressive with external input (NARX) based compensation for the servo-hydraulic dynamics within the maRTHS benchmark model. Different from previous study, nonlinear terms are incorporated into the NARX model. Online least square and ridge regression techniques are utilized to estimate the model coefficients to achieve optimal compensation. The influence of various model order and window length is assessed for the NARX model-based compensation. The findings of this research demonstrate that NARX-based compensation has significant potential not only in facilitating precise actuator control for maRTHS but also in enabling robust control in the presence of unknown uncertainties inherent to the servo-hydraulic system.

Compensation Method for Current Measurement Errors in the Synchronous Reference Frame of a Small-Sized Surface Vehicle Propulsion Motor

This paper proposes a new method for compensating current measurement errors in shipboard permanent magnet propulsion motors. The method utilizes cascade decoupling second-order generalized integrators (SOGIs) and adaptive linear neurons (ADALINEs) as the current harmonic extractor and the compensator, respectively. It can compensate for the dq-axes offset and scaling errors simultaneously, improving phase current distortion while reducing the ripples of motor speed and torque. Compared to the traditional motor model-based compensation strategies, the proposed method is robust against the changes in motor parameters with the online adaptive capability of the ADALINE algorithm. Furthermore, due to the good real-time performance of SOGIs and ADALINEs, the proposed compensation strategy can effectively operate in both the steady state and transient state of the motor. Finally, the effectiveness of the proposed method is verified through the physical and hardware-in-the-loop (HIL) experiments. After compensating for the current measurement errors of a 1 kW test motor with the propeller-characteristics load, the torque ripple and speed ripple are reduced by more than 65% and 80%, respectively. At the same time, the DC component and the second-order and third-order harmonics in the phase currents are also significantly reduced. Similar test results can be also obtained on the HIL platform with a 100 kW permanent magnet motor.

LuGre model–based robust adaptive control for a pump-controlled hydraulic actuator experiencing friction

In this paper, a LuGre model–based robust adaptive control (RAC) approach is presented for a pump-controlled hydraulic actuator. We first decompose the LuGre friction model into its steady-state model and a lumped dynamic part applying the mean value theorem, which are compensated by a feedforward term and a robust adaptive term, respectively. The robust adaptive term also plays a part in mismatched disturbance attenuation. In addition, parametric uncertainties and matched disturbances are handled by σ-modified adaptation laws and a robust control law, respectively. The stability of the closed-loop system is proved via the Lyapunov analysis. The efficacy and robustness of the proposed approach are validated by comparative experiments. Compared with common adaptive friction compensation methods, the proposed method has a simpler structure, less computational burden, better control performance, and stronger robustness. Moreover, since the available information is separated from the LuGre model and acts as a model-based compensation term, the design conservativeness of RAC is effectively reduced.

Vibration Control of Base-Excited Rotors Supported by Active Magnetic Bearing Using a Model-Based Compensation Method

Active magnetic bearings (AMBs) are a type of mechatronics product widely used in high-speed rotating machinery. Considerable research has been conducted on the vibration rejection of the AMBs-rotor systems at the base standstill. However, little attention has been paid to the case where the rotor operates under base excitations, such as turbines mounted on ships with wave excitation. The increased rotor vibration caused by base excitations is a great challenge to operational safety. To address this issue, a base acceleration feedforward compensation (BAFC) algorithm was proposed in this paper. Using the online base excitation data and the dynamic model of the rotor system, the proposed model-based algorithm determines the optimal compensation current in real time. Further, to reject the decreased compensation performance due to inaccurate modeling, a method for correcting the compensation error has been presented. Moreover, the effect of controller parameters on system stability was explored to avoid parametric instability during base excitations. By employing the BAFC algorithm in the experiments, the rotor vibration was reduced considerably under both the harmonic and random base excitations with a maximum vibration reduction of 85%, demonstrating the remarkable effectiveness of the BAFC algorithm.

Time delay in a mechatronic Power-HIL system: Analysis and model-based compensation

The Power-Hardware-in-the-Loop (PHIL) methodology enables testbed solutions that support the development of complex mechatronic components. In PHIL testing, a unit under test (UUT) is coupled with a virtual representation of its surroundings. As an example, a real railway pantograph current collector UUT can be tested in real-time interaction with a virtual overhead catenary. However, due to the closed-loop feedback interconnection and the exchange of power between real and virtual systems, such a PHIL control structure is highly sensitive to time delays in the signal paths which limits its performance, accuracy, and stability. In this work, methods to evaluate and compensate for the effect of time delays in a typical PHIL structure are proposed. A model-based PHIL control system is introduced to demonstrate the effect of time-delay compensation techniques, including utilising specific reduced-order models to achieve efficient time-delay compensation. The performance of the control system is demonstrated and validated via simulations and experiments on a scaled PHIL test setup, which is related to railway pantograph testing. In addition, criteria to analyse system stability are formulated and demonstrated with respect to uncompensated time delays and unknown UUT contact stiffness.

Adaptive backstepping-extended state observer control for electrohydraulic position servo systems with multiple disturbances using the compound friction compensation

Multiple disturbances coming from friction, matched, and mismatched uncertainties make it difficult for electrohydraulic servosystems to obtain the satisfactory position-tracking performance. The existing adaptive backstepping controllers fail to effectively distinguish the difference of disturbance between the mechanical subsystem and the hydraulic subsystem, which limits the compensation effect of multiple disturbances, especially for friction nonlinearity. Therefore, the adaptive backstepping-extended state observer position-tracking controller combined with compound friction compensation is proposed to simultaneously compensate for the fast-varying friction disturbance of a mechanical subsystem and the slow-varying matched disturbance of a hydraulic subsystem. The extended state observer algorithm is integrated into the adaptive backstepping controller to suppress the null bias of the average tracking error. The compound friction compensation includes a LuGre model-based compensation and a high-order disturbance observer, which can improve the tracking performance of system and avoids the excessive gain of observer. A large number of comparative experiments are conducted to verify the effective of the proposed controller.

Designing and Modelling of Pivotal Friction Compensator of Actuator of Hard Disk Drives

Nowadays, hard disk drives are one of the most common devices for storing data. The growing demand for storing the bulk amount of data and retrieving the data as fast as possible from hard disk drives (HDDs) has posed manufacturers with various challenges. To overcome these hurdles different methods, techniques, and control systems are developed to improve the transient response of the HDDs. The transient response of a system is characterized by numerous specifications such as overshooting, peak time, settling time, delay, and rise time. This can also be achieved by using several stages of actuators servomechanism that can also help us to store a large amount of data, it also helps to increase the accuracy of head-positioning of the actuator that eventually leads to enhancement of the transient response of hard disk drives (HDDs). By increasing the accuracy of read/write head actuator there is a challenge to cater the friction at pivot of actuator. This friction can significantly reduce the speed of the actuator and that ultimately leads to the reduced transient responses of the system. This paper aims to design a new modelled-base friction compensator for the servo control of hard disk drives that can improve the transient response of HDDs. Thus, improving the transient responses of HDDs can make the computer more efficient than ever and can save a lot of time while making complex calculations. To achieve this aim measured and replicated responses will be used as guidance and the friction design of HDD will iteratively improve. This can be done by feeding the measured friction forces back to the voice coil motor (VCM) so that the frequencies of the actuator’s head and current be linearized. This proposed design will help in the cancelation scheme and the model-based compensator will be implemented. By improving the tracking seek of HDDs we can also write the data much faster on the HDD and by using numerous techniques we can store a large amount of data on HDDs. Our aim is also to integrate a PID controller into our control system so that we can improve the transient response as much as possible. Our work can be considered important as there are very few frictions compensator control designs that have integrated the PID controller. We are aiming to achieve a significantly improved pivotal friction compensator that can help us to achieve improved transient response of the hard disk drive (HDD).

New Decision for QAM Based on SVM for Complex Impairments

In this paper, we propose a new decision method based on a support vector machine for quadrature amplitude modulation (QAM) to improve the bit error rate (BER) performance of QAM for arbitrary complex impairments when both modeled and unknown impairments exist simultaneously. To do this, we first propose an algorithm for assigning bit decision boundaries corresponding to each quadrant for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> -ary QAM, considering the asymmetry of the QAM constellation caused by the impairments. Then, we determine the optimal decision boundaries by learning a linear classification model for each bit decision region from I and Q values of received QAM signals as two-dimensional support vectors. Finally, the decision rules for each bit are presented based on the obtained optimal decision boundaries, and the bit decisions are performed using the decision rules. Based on the above process, we can effectively demodulate QAM signals for arbitrary complex impairments without compensation processes. Through computer simulations, we show the proposed method outperforms conventional model-based compensation schemes in BER performance under the condition of complex impairments.

A Viscoelastic Compensator for Force Sensors With Soft Materials

Model-based compensators have been widely applied in force sensors with soft materials to eliminate viscoelasticity that causes creep output, slow dynamic response, and limits the performance of the sensors. However, the lack of accurate characterization of high-order viscoelasticity and the high computational complexity restricts the performance and application of existing methods. For the above problem, we propose a first-order Volterra grey box model-based viscoelastic compensator for force sensors with soft materials. First, the measurement mechanism of the soft-material-based force sensor is analyzed, and a grey box model for accurately characterizing the high-order linear viscoelasticity by the first-order Volterra series is proposed, without needing high-order spring-damping parameters and their exponential operations. Then, the high-order viscoelasticity compensator is designed and directly linearly fitted with the variation of the historical output, which avoids the computational complexity of the high-order creep compliance and its exponential parameters fitting. Finally, the proposed method is verified with a self-developed soft-material-based capacitive force sensor. The real-time experimental results show that, compared with existing methods, the proposed compensator not only has better compensation performance, but also has a shorter calculation time for force sensors with soft materials.

Inclusion of Bidirectional Angular Positioning Deviations in the Kinematic Model of a Six-DOF Articulated Robot for Static Volumetric Error Compensation

To improve a robot’s absolute positioning accuracy, researchers have extensively studied the robot kinematic model containing position and orientation errors of rotary axis average lines, widely known as Denavit–Hartenberg (D-H) parameters. To further improve the absolute positioning accuracy of industrial robots, this article proposes a novel kinematic model and its identification scheme. The proposed kinematic model for a serial-linked industrial robot contains the bidirectional angular positioning deviations of each rotary axis, represented in a lookup table, in addition to its D-H parameters. The angular positioning deviations of the rotary axes are modeled as a function of angular command positions, along with the direction of rotation to model the influence of backlash. This article also proposes a novel approach to identify the proposed kinematic model with the bidirectional angular positioning deviations using a laser tracker with indexing each rotary axis at specified angular positions (“circle point method”). Moreover, the model-based compensation technique is being experimentally investigated to validate the prediction accuracy of the proposed model. The findings of the experiment show that the proposed model enhances the robot’s absolute positioning accuracy significantly over the entire workspace.

General compensation control method of flexible manipulator driven by tendon-sheath mechanism

Flexible manipulator has been widely used because of its flexibility. In addition, the tendon-sheath mechanism has the advantages of compact structure and strong flexibility, and it can be used as the driving transmission mode of the flexible manipulator. However, the nonlinear and hysteretic characteristics of the tendon-sheath mechanism directly affect the motion accuracy of the manipulator. Firstly, the kinematic and static models of the flexible manipulator are analyzed considering the influence of multi section coupling. In addition, the mechanical transmission process of the tendon-sheath mechanism is analyzed. On this basis, a general feedforward compensation method for the flexible manipulator is established. The proposed model-based compensation control method can be applied to all flexible manipulators, and it is of great significance to promote the practical application of the manipulator.

Data‐driven nonlinear autoregressive with external input model‐based compensation for real‐time testing

Actuator control plays an important role for real-time testing based experimental techniques such as real-time hybrid simulation (RTHS). Accurate modeling of actuator dynamics can be challenging due to the complexity and nonlinearity of the servo-hydraulic system. In this study, nonlinear autoregressive with external input (NARX) modeling is introduced to emulate the servo-hydraulic dynamics. The command and measured displacements of the actuator are used as input and output of the NARX model. The coefficients of the NARX model of different orders are determined online through ordinary least square regression in a real-time manner. Data weight is further proposed to account for most recent variation in command and measured displacements. Real-time tests with predefined random and chirp signals are conducted to evaluate the performance of proposed NARX model-based compensation of different orders, window length, and data weight. The efficacy and robustness of proposed NARX model-based compensation are further verified through computational simulation of a RTHS benchmark model. Both numerical simulation and laboratory experiments demonstrate that the proposed method enables effective negation of servo-hydraulic dynamics for real-time testing.

Inductor Saturation Compensation in Three-Phase Three-Wire Voltage-Source Converters Via Inverse System Dynamics

In three-phase three-wire (3P3W) voltage-source converter (VSC) systems, utilization of filter inductors with deep saturation characteristics is often advantageous due to the improved size, cost, and efficiency. However, with the use of conventional synchronous frame current control methods, the inductor saturation results in significant dynamic performance loss and poor steady-state current waveform quality. This article proposes an inverse dynamic model-based compensation (IDMBC) method to overcome these performance issues. For this purpose, two-phase exact modeling of the 3P3W VSC control system is obtained. Based on the modeling, the inverse system dynamic model of the nonlinear system is obtained and employed such that the nonlinear plant is converted to a virtual linear inductor system for linear current regulators to perform satisfactorily. Further, to control phase currents in the synchronous frame, a two-phase coordinate transformation is proposed. The IDMBC method is tested via dynamic command response and waveform quality simulations and experiments that employ saturable inductors reaching down from full inductance at zero current to 1/9th inductance at full current. The results obtained demonstrate the suitability of the method for 3P3W VSCs employing saturable inductors.

Time Delay of Wide Area Damping Control in Urban Power Grid: Model-Based Analysis and Data-Driven Compensation

Due to the rapid development of economies, large urban cities consume an increasing amount of energy and have a higher requirement for power quality. Voltage source converter based high voltage direct current (VSC-HVDC) is a promising device to transmit clean power from remote regions to urban power systems, while also providing wide area damping control (WADC) for frequency stabilization. However, the time-delay naturally existing in the VSC-HVDC system may degrade the performance of WADC and even result in instability. To address this issue, this paper develops a time-delay correction control strategy for VSC-HVDC damping control in urban power grids. First, a small signal model of WADC is built to analyze the negative impacts of time delay. Then, a data-driven approach is proposed to compensate for the inherent time delay in VSC-HVDC damping control. The extensive training data will be generated under various disturbances. After offline training, the long short-term memory network (LSTM) can be implemented online to predict the actual frequency deviation based on real-time measurements. Finally, the proposed method is validated through MATLAB-Simulink in a two-area four-machine system. The results indicate that the data-driven compensation has a strong generalization ability for random delay time constants and can improve the performance of WADC significantly.

Real-Time Stylized Humanoid Behavior Control through Interaction and Synchronization.

Restricted by the diversity and complexity of human behaviors, simulating a character to achieve human-level perception and motion control is still an active as well as a challenging area. We present a style-based teleoperation framework with the help of human perceptions and analyses to understand the tasks being handled and the unknown environment to control the character. In this framework, the motion optimization and body controller with center-of-mass and root virtual control (CR-VC) method are designed to achieve motion synchronization and style mimicking while maintaining the balance of the character. The motion optimization synthesizes the human high-level style features with the balance strategy to create a feasible, stylized, and stable pose for the character. The CR-VC method including the model-based torque compensation synchronizes the motion rhythm of the human and character. Without any inverse dynamics knowledge or offline preprocessing, our framework is generalized to various scenarios and robust to human behavior changes in real-time. We demonstrate the effectiveness of this framework through the teleoperation experiments with different tasks, motion styles, and operators. This study is a step toward building a human-robot interaction that uses humans to help characters understand and achieve the tasks.

Input constraint control for hydraulic systems with asymptotic tracking

Due to the nonlinearity and various uncertainties, the controller design for hydraulic servo systems with input constraint is more complicated and challenging. This paper first proposes an asymptotic tracking controller for electrohydraulic servomechanisms considering input constraint, parametric uncertainties, and unmodeled disturbances. The core innovation of this controller is to decouple the control input and the input nonlinearity while guaranteeing the nonlinear decoupling term and its derivative to be available and bounded. Meanwhile, the decoupling operation could be skillfully integrated to realize accurate adaptive model-based compensation while remaining the unique feature of asymptotic control for residual disturbances. For this purpose, based on the desired trajectory and the estimated disturbance via an extended state observer (ESO), a desired load pressure signal is constructed to replace the actual load pressure and accomplish the required decoupling operation. In this case, a desired adaptive feedforward compensation in combination with a robust integral of the sign of the error (RISE) feedback is proposed to attenuate parametric uncertainties and residual unmodeled disturbances, respectively. Subsequently, a smooth hyperbolic tangent function is integrated into the controller to handle the input constraint. Theoretical analysis proves that the developed control strategy can achieve semi-global asymptotic tracking performance. Besides, numerical simulations and experimental tests demonstrate that the proposed control scheme can ensure high-precision tracking performance and simultaneously satisfy the preset control input range when encountering the input constraint and modeling uncertainties.

A comparative study between feedforward control and iterative learning control for trajectory tracking of Delta robot

This paper presents a comparative study between feedforward control (FF) and iterative learning control (ILC) with application to a parallel Delta robot performing repetitive trajectory. In order to improve the tracking trajectory of the Delta robot, a model-based feedforward compensation combined with the proportional derivative (PD) controller is introduced. As the Delta robot is affected by important frictions that are not taken into account in the dynamic model, the performance of the FF can be degraded considerably. To overcome these issues, a model-free control represented by the PD-type ILC controller is used instead the FF compensation. Experimental results show that the two strategies can ensure good tracking performance with better accuracy of ILC.