High Tracking Accuracy Research Articles

Adaptive recursive sliding mode based trajectory tracking control for cable-driven continuum robots

To improve the transient response, accuracy and robustness of trajectory tracking control for cable-driven continuum robots (CDCRs), a recursive integral terminal sliding mode control combined with an adaptive disturbance observer (ADO-RITSMC) is proposed. The recursive integral terminal sliding mode control (RITSMC) guarantees fast transient response and high tracking accuracy with a fast zero convergence of the tracking error without chattering. To attenuate the effect of uncertain dynamics, an adaptive disturbance observer (ADO) is constructed to derive uncertain dynamics. Particularly, an improved grey wolf optimizer (IGWO) is merged into the ADO to enhance the estimating accuracy of uncertain dynamic factors. Simulation and experiment results demonstrate the superiority of the ADO-RITSMC in enabling fast transient response, high accuracy and strong robustness of trajectory tracking control.

Toward quantitative intrafractional monitoring in paraspinal SBRT using a proprietary software application: clinical implementation and patient results

Objective. We report on paraspinal motion and the clinical implementation of our proprietary software that leverages Varian’s intrafraction motion review (IMR) capability for quantitative tracking of the spine during paraspinal SBRT. The work is based on our prior development and analysis on phantoms. Approach. To address complexities in patient anatomy, digitally reconstructed radiographs (DRR’s) that highlight only the spine or hardware were constructed as tracking reference. Moreover, a high-pass filter and first-pass coarse search were implemented to enhance registration accuracy and stability. For evaluation, 84 paraspinal SBRT patients with sites spanning across the entire vertebral column were enrolled with prescriptions ranging from 24 to 40 Gy in one to five fractions. Treatments were planned and delivered with 9 IMRT beams roughly equally distributed posteriorly. IMR was triggered every 200 or 500 MU for each beam. During treatment, the software grabbed the IMR image, registered it with the corresponding DRR, and displayed the motion result in near real-time on auto-pilot mode. Four independent experts completed offline manual registrations as ground truth for tracking accuracy evaluation. Main results. Our software detected ≥1.5 mm and ≥2 mm motions among 17.1% and 6.6% of 1371 patient images, respectively, in either lateral or longitudinal direction. In the validation set of 637 patient images, 91.9% of the tracking errors compared to manual registration fell within ±0.5 mm in either direction. Given a motion threshold of 2 mm, the software accomplished a 98.7% specificity and a 93.9% sensitivity in deciding whether to interrupt treatment for patient re-setup. Significance. Significant intrafractional motion exists in certain paraspinal SBRT patients, supporting the need for quantitative motion monitoring during treatment. Our improved software achieves high motion tracking accuracy clinically and provides reliable guidance for treatment intervention. It offers a practical solution to ensure accurate delivery of paraspinal SBRT on a conventional Linac platform.

Tracking scheme of airborne star tracker based on event-triggered sliding mode control with known input delay

The airborne star tracker is crucial in aircraft navigation systems, with its tracking performance directly impacting navigation accuracy. Under airborne conditions, the performance of its tracking control will be compromised by various disturbances. Moreover, the limitation in computational resources is another issue that must be addressed. Assuming that the existing studies on this application did not consider these two aspects of the effects simultaneously, this study proposes a novel event-triggered sliding mode control (ET-SMC) scheme considering the known input time delay for star tracking control to address these two issues. First, an extended state observer (ESO) is presented to estimate the disturbance generated by airborne conditions. Second, the ET-SMC scheme further enhances the robustness and improves resource utilization, thus easing the processor burden. An ET mechanism related to the disturbance estimation triggering error in the ESO is introduced to ensure that the system input is only updated when necessary. A novel, easy-to-implement sliding gain is also proposed to increase system adaptability and reduce inherent chattering. The reachability of the sliding surface and the existence of a practical sliding mode of the system are ensured based on the Lyapunov theory. The ultimate upper bound of system states considering the known input time delay is also proven, thereby confirming the stability of the proposed design. The exclusion of Zeno behavior validates the feasibility of the proposed ESO-based ET-SMC. Finally, the effectiveness of the proposed method is verified using comparative simulations and target-tracking experiments. The experimental results demonstrate that the proposed method excels in robustness, disturbance attenuation, high tracking accuracy, and computational resource efficiency. These enhancements are anticipated to result in a more stable tracking performance for the star tracker, thereby contributing to precise aircraft navigation.

Finite-time attitude tracking control of stratospheric airship in the presence of multiple disturbances

AbstractThis paper proposes a composite non-singular fast terminal sliding mode attitude control scheme based on a reduced-order extended state observer for the stratospheric airship’s attitude system affected by multiple disturbances. First, the feedback linearisation method is applied to address the nonlinearity of the attitude motion model and achieve decoupling of the model in three channels. Second, the overall disturbances, encompassing airship parameter perturbations and external disturbances, are treated as an aggregate. A reduced-order extended state observer is designed for each channel to formulate a composite non-singular fast terminal sliding mode surface. In the control design phase, the hyperbolic sine function is adopted as replacement for the sign function to ensure the continuity of the control signal. The estimated disturbances are incorporated in the control law design to directly offset the effects of multiple disturbances on the attitude motion of the airship. Third, based on Lyapunov theory, it has been proven that the control law can drive the attitude tracking error to converge to zero within a finite time. Simulation results demonstrate that the proposed control scheme exhibits favorable disturbance rejection capability, as well as higher tracking accuracy and faster response speed.

Robust Adaptive Control of a Bimanual 3T1R Parallel Robot With Gray-Box-Model and Prescribed Performance Function

An elaborated bimanual 4-degrees-of-freedom (DOF) parallel robot is designed with large translational workspace, light moving mass and direct-drive actuation. The transient response greatly affects the throughput when using this robot for high-speed pick-and-place applications. However, this cannot be properly taken care by existing black-box model-based control schemes. Meanwhile, it is tedious to derive its dynamic model analytically and such a model is inapplicable for the real-time control. In this work, a gray-box-model-based control structure is proposed, with the retained inertial dynamics are directly derived by the principle of virtual work and the other parts are estimated by adaptive neural networks. This ensures calculation efficiency and integrity of the dynamics. Moreover, a prescribed performance function is constructed to ensure the specified tracking requirements both in transient and steady states. On the basis, the robust integral of signum of error term is incorporated to compensate the structural and unstructural uncertainties, which further improves the robustness during high-frequency motion. Comparative real-time experiments have been performed on the actual robot with attainment of the predefined performance and higher tracking accuracy.

Optimal Control Strategy of Electro-hydraulic Position Servo System Using Genetic Algorithm

Background: The optimal control strategy has been widely used in electro-hydraulic position servo systems to achieve high-precision position tracking. However, the difficulty of selecting the weighted matrices in optimal control often leads to poor tracking accuracy. Objective: This patent proposes an optimal control strategy using a genetic algorithm to improve the tracking accuracy of the electro-hydraulic servo system. Methods: The patent first established the system state equation of the valve-controlled asymmetric cylinder. Secondly, based on linear quadratic optimal control theory and genetic algorithm, an optimal control strategy using a genetic algorithm was proposed. Finally, the simulation and experimental results showed that the designed controller has high position tracking accuracy . Results: The optimal controller using a genetic algorithm was designed using Matlab/Simulink, and the effectiveness of the controller was verified through simulation. Additionally, experimental results showed that the proposed optimal control controller using a genetic algorithm had higher tracking accuracy than the proportional-integral-derivative controller and traditional backstepping controller for a given reference signal. Conclusion: The control technology of the optimal controller using a genetic algorithm was found to be superior to proportional-integral-derivative and traditional backstepping controllers, and the tracking error of the linear quadratic regulator controller was reported to be relatively small. This demonstrated the effectiveness of the optimal control strategy using a genetic algorithm in this patent.

Path-Tracking Control of Soft-Target Vehicle Test System Based on Compensation Weight Coefficient Matrix and Adaptive Preview Time

<div>In order to enhance the path-tracking accuracy and adaptability of the electric flatbed vehicle (EFV) in the soft-target vehicle test system, an improved controller is designed based on the linear quadratic regulator (LQR) algorithm. First, the LQR feedback controller is designed based on the EFV dynamics tracking error model, and the genetic algorithm is utilized to obtain the optimal weight coefficient matrix for different speeds. Second, a weight coefficient matrix compensation strategy is proposed to address the changes in the relationship between the vehicle–road position and attitude caused by external disturbances and the state of EFV. An offline parameter table is created to reduce the computational load on the microcontroller of EFV and enhance real-time path-tracking performance. Furthermore, an adaptive preview time control strategy is added to reduce the overshooting caused by control delay. This strategy is based on road curvature and traveling speed. Finally, the simulation experiment and field experiment are carried out. The results show that the improved LQR controller exhibits high tracking accuracy during the emergency double lane changes experiment and can maintain accuracy and stability at different speeds.</div>

Data-driven two-dimensional integrated control for nonlinear batch processes

Two-dimensional control has been considered as an effective strategy to accomplish high-accuracy tracking for batch processes because of its excellent learning ability and time-domain stability. However, being a model-based control method, the performance of the two-dimensional control system will inevitably decrease due to unknown uncertainties or unmodeled dynamics. In addition, the high computational cost and complex design process of the control system severely limit its application in batch processes. For this reason, this paper proposes a new data-driven two-dimensional integrated control (DDTDIC) method for nonlinear batch processes. In the presented control scheme, the P-type iterative learning control (ILC) is adopted along the batch-axis to ensure the convergence of the system, and the proportional-integral-differential (PID) control is used in the time-axis to reject the influence of real-time disturbance. The parameters of the PID controller are obtained by utilizing the virtual reference feedback tuning (VRFT) method. The entire design process of the control system only requires the input and output (I/O) data of the batch processes and does not depend on any explicit model information. The simulation results show that compared with the ILC and the two-dimensional control, the presented control method not only has faster convergence speed and smaller tracking error, but also the computational efficiency is improved by more than 40% and 50% respectively.

Internal Model Principle-Based Extended State Observer for the Uncertain Systems with Nonconstant Disturbances

Existing traditional expansion state observers exhibit good tracking performance for constant and low-frequency disturbances. However, their ability to track non-constant disturbances such as ramp and high-frequency harmonics is inadequate. This paper proposes an extended state observer design method based on the internal model principle. This method achieves precise tracking of non-constant disturbances in the system, effectively addressing the issue of disturbance estimation errors in conventional expansion state observers. When applied to control systems, this approach significantly mitigates or suppresses system vibrations caused by non-constant disturbances, thereby enhancing control accuracy. Furthermore, it demonstrates the stability of the controlled system and the active disturbance rejection controller parameters over a wide range of variations. Simulation results indicate that the ADRC controller based on the proposed observer in this paper offers notable advantages, including high tracking accuracy, strong disturbance rejection capability, and good stability, leading to commendable control performance.

Structural Flexibility Effect on Spaceborne Solar Observation System’s Micro-Vibration Response

The spaceborne solar observation system is crucial for the study of space phenomena such as solar flares, which requires high tracking accuracy. This study presents a coupling model that integrates mechanical, electrical, and control models to investigate the structural flexibility effect on the micro-vibration response. We established a rigid–flexible model using mechanical parts. We considered the influence of flexible features while studying the dynamic responses in its operation. The state-space equations of the system showed that modal frequency, damping, and modal participation factors played significant roles. We derived transfer functions using the Laplace transform of the coupling models to better understand this mechanism, and Simulink models were thereby established. We simulated the acceleration responses of the rigid–flexible and rigid models under angle tracking modes, and the results showed significant differences. We also simulated the acceleration responses of the models under various control frequencies, and the optimal control frequency was thus obtained. Finally, we performed experiments, and the results indicated that the rigid–flexible model could better predict the motion and acceleration responses for the spaceborne solar observation system. This study provides valuable information for understanding the role of flexible features in space performance high-tracking accuracy instruments and for micro-vibration suppression research.

Low-cost MPPT for triple-junction solar cells used in nanosatellites: A comparative study between P&O and INC algorithms

This paper presents a study of solar panels composed of triple-junction solar cells used in CubeSats; in particular, it focuses on optimizing the power supplied by these panels using the maximum power point tracking technique (MPPT). Optimizing this power is a challenge that is not easily overcome, due to the constraints associated with CubeSats applications, especially in terms of weight, area, budget, as well as the low power generated by these panels which do not exceed 2.4 W at the maximum power point. For all these considerations, both P&O and INC techniques were chosen, since P&O is relatively easy to implement and does not require complex equipment, while INC is known for its high tracking accuracy in difficult environments under fast changing solar conditions, plus the low cost characterizing both techniques, which makes them suitable for CubeSats applications. To select the most appropriate technique for CubeSats applications, a comparative study between both P&O and INC algorithms is performed theoretically using a MATLAB/SIMULINK simulation, followed by a hardware implementation to transfer ideas from theory to practice for realizing the CubeSats power system electronic board since the present study is carried out in the context of a CubeSat application, it focuses on the nanosatellite power system, making it distinct compared to ordinary photovoltaic systems, which have been widely used and studied in previous research in the field of photovoltaics.

Analytical parameter tuning for a class of extended disturbance observers and sliding mode control

This paper studies the parameter tuning problem for a class of extended disturbance observers (EDO) and the EDO-based sliding mode control (SMC). Based on a H2 optimization technique, analytical solutions for the parameter tuning of the EDO and the EDO-based SMC are obtained. The conditions under which higher-order EDOs are strictly better than lower-order EDOs are derived analytically. Furthermore, the steady-state performance of the EDO-based SMC is analyzed, where it is shown that the improvement of the tracking accuracy of the EDO can reduce the sensitivity of the state variables and the control input with respect to the controller parameters. This implies that the SMC parameter tuning requirement can be reduced if a high tracking accuracy of the EDO is guaranteed. Finally, the application to the active structural control problem of an offshore wind turbine is studied and the effectiveness of the obtained results is demonstrated based on a National Renewable Energy Laboratory (NREL) 5MW baseline offshore wind turbine.

Fixed-time Sliding Mode-based Adaptive Path Tracking Control of Maize Plant Protection Robot via Extreme Learning Machine

During the maize middle and late periods, the soil between rows is soft and also involved with weeds and straw. When the plant protection robot (PPR) moves on the soil, there exists uncertain shear perturbation because of the shear action and pressure subsidence, leading to the difficulty of the controller design. In this work, we propose an adaptive path tracking control (PTC) considering disturbances for the PPR. The disturbance of PRR in contact with soil is first revealed according to Bekker pressure subsidence and Janosi shear models, through which the plant model of PPR system is established. Then, we propose an adaptive fixed-time sliding mode (AFTSM)-based PTC to achieve excellent path tracking performance, where an extreme learning machine (ELM) estimator is developed, releasing the requirement for bound derivations in the control design. Using the fixed-time control and the ELM techniques in the proposed control, a remarkable control performance is well ensured, i.e., high-accuracy tracking, fast convergence, and excellent robustness. Experimental studies on a PPR are executed for demonstrating the validity and good performance of the designed controller.

Research on Yaw Stability Control Strategy Based on Direct Slip Rate Allocation

This paper deals with the integrated control of trajectory tracking and yaw stability for autonomous vehicles. Firstly, a nonlinear vehicle dynamics model is established. The MPC algorithm was used to determine the best front wheel angle. The PID control algorithm is used to ensure the accuracy of longitudinal speed tracking. The sliding mode control algorithm is used to generate additional yaw moment and optimize the distribution of longitudinal tire force. In order to ensure the most effective distribution of the driving torque of the four wheels of the vehicle, the PID algorithm is used to track and manage the longitudinal slip rate of each tire on the bottom layer. Simulation tools such as MATLAB/Simulink and Carsim are used to verify the effectiveness of the multi-closed-loop integrated control technology. Compared with the general control strategy (no slip rate control), the trajectory error of this control algorithm is reduced by 55.6%, which indicates that it has advantages in obtaining a high tracking accuracy and ensuring the stability of autonomous vehicles.

Lateral Trajectory Tracking of Self-Driving Vehicles Based on Sliding Mode and Fractional-Order Proportional-Integral-Derivative Control

The tracking accuracy and vehicle stability of self-driving trajectory tracking are particularly important. Due to the influence of high-frequency oscillation near the sliding mode surface and the modeling error of the single-point preview model itself when using sliding mode control (SMC) for the trajectory tracking lateral control of self-driving vehicles, the desired tracking effect of self-driving vehicles cannot be achieved. To address this problem, a combination of sliding mode control and fractional-order proportional-integral-derivative control (FOPID) is proposed for the application of a trajectory tracking lateral controller. In addition, in order to compare with the trajectory tracking controller built using the single-point preview model, 12 real drivers with different levels of proficiency were selected for operational data collection and comparison. The simulation results and hardware-in-the-loop results show that the designed SMC + FOPID controller has high tracking accuracy based on vehicle stability. The trajectory accuracy based on SMC + FOPID outperforms the real driver data, SMC controller, PID controller, and model prediction controller.

Adaptability enhancement of fractional‐order LLCL‐type grid‐connected inverter to weak grid based on grid voltage weighted feedforward scheme

SummaryGrid‐connected inverter with a novel fractional‐order LLCL filter has the advantage of high grid current tracking accuracy and low total harmonic distortion without passive or active dampers, and the grid voltage full feedforward scheme is an effective method to improve the quality of grid current. However, due to the digital control delay, the suppression of the grid current harmonics is weakened, and the inverter output impedance has an additional negative phase shift, which deteriorates the stability of grid‐connected systems under weak grid. In this paper, a weighted grid voltage fractional‐order feedforward control scheme is proposed based on a quasi‐proportional resonant (QPR) controller, which introduces two weighting factors in the full feedforward path of the grid voltage and compensates the phase lag of the output impedance by designing appropriate weighting factors. Then, an improved scheme combining the QPR controller with a phase compensator is presented. As a result, the suppression ability of grid current harmonics and the adaptability to grid impedance variations are enhanced. Simulation and experimental results verify the effectiveness of the proposed grid voltage fractional‐order weighted feedforward scheme.

A Novel Hierarchical Recursive Nonsingular Terminal Sliding Mode Control for Inverted Pendulum

This paper aims to develop a novel hierarchical recursive nonsingular terminal sliding mode controller (HRNTSMC), which is designed to stabilize the inverted pendulum (IP). In contrast to existing hierarchical sliding mode controllers (HSMC), the HRNTSMC significantly reduces the chattering problem in control input and improves the convergence speed of errors. In the HRNTSMC design, the IP system is first decoupled into pendulum and cart subsystems. Subsequently, a recursive nonsingular terminal sliding mode controller (RNTSMC) surface is devised for each subsystem to enhance the error convergence rate and attenuate chattering effects. Following this design, the HRNTSMC surface is constructed by the linear combination of the RNTSMC surfaces. Ultimately, the control law of the HRNTSMC is synthesized using the Lyapunov theorem to ensure that the system states converge to zero within a finite time. By invoking disturbances estimation, a linear extended state observer (LESO) is developed for the IP system. To validate the effectiveness, simulation results, including comparison with a conventional hierarchical sliding mode control (CHSMC) and a hierarchical nonsingular terminal sliding mode control (HNTSMC) are presented. These results clearly showcase the excellent performance of this approach, which is characterized by its strong robustness, fast convergence, high tracking accuracy, and reduced chattering in control input.

Model-Free Adaptive Nonsingular Fast Integral Terminal Sliding Mode Control for Wastewater Treatment Plants

The regulation of wastewater treatment plants (WWTPs) is a challenge due to their complex biological and chemical characteristics and their accurate mathematical model is generally not accessible because of the limitation of available measurements. To overcome such challenges, in this paper, a novel model-free adaptive nonsingular fast integral terminal sliding mode control (MFA-NFITSMC) is proposed. Firstly, based on the concept of dynamic linearization, a compact format dynamic linearized (CFDL) data model for the WWTP is established. Secondly, a novel fast integral terminal sliding mode surface is proposed to accelerate the convergence of tracking error and a discrete-time MFA-NFITSMC is created using the CFDL model as a basis; then, its stability is proved by theoretical analysis. Finally, the experimental verification is conducted based on the Benchmark Simulation Model No. 1 and the results show that the proposed method has a higher tracking accuracy and stronger robustness than other methods in the control of WWTPs.

Dynamic modeling and rotation control for flexible single-link underwater manipulator considering flowing water environment based on modified morison equation

Flexible single-link underwater manipulator (FSLUM) can be installed in autonomous underwater vehicles, it can carry out underwater tasks such as offshore oil and gas exploration, underwater cable maintenance as well as fishery farming and fishing. The design and development of the FSLUM are of great significance for ocean exploration and development. The FSLUM is affected by the underwater interference torque during underwater tasks in the flowing water environment, which will greatly affect the operational accuracy. In addition, many nonlinear factors such as the flexibility of the transmission system and the two-dimensional deformation of flexible links will aggravate the control difficulty of the FSLUM. An improved sliding mode control (SMC) strategy based on neural network identification is proposed to enhance the FSLUM's control accuracy. Neural networks are proposed to identify uncertain components including underwater interference and flexible nonlinear terms, so as to advance the control law design accuracy. Firstly, the FSLUM dynamic equations coupled with underwater interference torque considering multiple nonlinear factors are established according to the assumed mode method (AMM). A modified Morison equation is proposed to abbreviate the underwater interference torque in flowing water environments. Next, the control law of improved neural network sliding mode control (NNSMC) strategies are proposed according to the Lyapunov stability theorem, so as to ensure closed-loop stability of the FSLUM. Finally, the results of simulation and prototype tracking control experiments show that the improved NNSMC strategy has high tracking accuracy.

Trajectory planning and control of large robotic excavators based on inclination-displacement mapping

This paper proposes a trajectory planning and control method for heavy-duty manipulators based on inclination-displacement mapping. In this method, inclination sensors are employed to detect the excavator's orientation. By establishing a mapping relationship between joint inclination and cylinder displacement, the cylinder displacement is indirectly derived. Subsequently, considering the typical excavation operation process, the spatial trajectory of the excavator bucket is planned. The displacement of the driving cylinder is determined using kinematic inverse solutions and cubic polynomials. The cylinder displacement is then controlled using a position-velocity (PV) strategy. This method is tested on a 95-ton large excavator, and the results demonstrate several advantages, including easy installation, low maintenance requirements, smooth trajectory planning, and high tracking accuracy. These qualities make it suitable for the demands of intelligent operations in large excavators. Thus, this paper offers valuable insights for the intelligent transformation of heavy excavators.