High-precision Control Research Articles

Active Disturbance Rejection Control Algorithm for the Driven Branch Chain of a Polishing Robot

To overcome poor error suppression performance and low control accuracy in the polishing robot-driven branch chain control system, this paper proposes an improved active disturbance rejection control (ADRC) from the design of the derived nonlinear function. Subsequently, the tracking differentiator (TD), extended state observer (ESO) and nonlinear state error feedback (SEF) are designed in the ADRC, and the driven branch’s ADRC servo-control system is established based on the permanent magnet synchronous motor (PMSM) with each driven branch. Meantime, by establishing first-order and second-order ADRC, current-loop control, and speed-and-position-loop control are realized, respectively. Finally, this study analysed differences in the speed and motor rotor error performance between the proportional-integral-derivative (PID)control and ADRC control strategy by using Simulink. Furthermore, an experiment platform, including hardware and software, is built to validate some inclusions. The results show that the ADRC not only realises high-precision trajectory tracking control but also ensures the rapid response performance of the system.

Optofluidic-based cell multi-axis controllable rotation and 3D surface imaging

The controlled rotation of individual cells plays a crucial role in enabling three-dimensional multi-angle observation of cellular structure, function, and dynamic processes. Reported cell rotation techniques often struggle to strike a balance between high precision and simple control, and they exhibit limited control flexibility, typically achieving only uniaxial cell rotation. In this study, we propose a cell rotation technique in three dimensions based on optofluidics, which utilizes optical tweezers to immobilize the cell and exploits the asymmetry of the surrounding flow to drive cell rotation. By adjusting the focal position of the optical tweezers, cells can be positioned within various flow profiles, enabling control of the rotation speed, rotation direction, and rotation axis of cells. This approach simplifies the manipulation procedure, achieving desirable control precision and greater rotation flexibility. Using our approach, multi-angle surface imaging projections of target cells can be rapidly obtained, followed by capturing the cell contour data from the images. By combining the cell contour data with corresponding angular position information, we have reconstructed the 3D surface of the target cell. We have employed this technique in experiments for the analysis of red blood cell morphology. Based on the constructed 3D surface images of diverse-shaped red blood cells, we quantified structural parameters including cell surface area, volume, sphericity, and surface roughness, which demonstrates the potential application of this cell rotation technique for cellular morphological analysis.

Dynamic optimal control of flow front position in injection molding process: A control parameterization-based method

High dynamic and precise control of process variables within permissible limits is the key to high product quality in the injection molding industry. Among these variables, the injection flow rate of molten polymer is particularly significant. In this paper, an effective optimal open-loop and state feedback controller design method is designed to realize the optimal tracking control of the melt polymer flow front position flow of melt polymer fluid during injection molding. To this end, the dynamic model of the filling process is firstly established, taking into account the nonlinearity of hydraulic control system and the effect of molten polymer flow on the dynamics of the injection ram, and then the dynamic optimal tracking control problem of flow front position of molten polymer in injection molding machine is proposed. Then, an open-loop controller and a multi-level feedback control law are well designed, wherein the control signal and the control feedback kernels are parameterized by control parameterization. The controller design problems are transformed into sequential optimal parameter decision problems. The explicit expressions of the gradient information of the objective function and constraints on the parameters of the decision variables are solved by using the state sensitivity equation analysis method, and the gradient information is combined with the nonlinear programming algorithm to solve the optimization problems efficiently. Finally, the viability and effectiveness of the proposed design method are verified by numerical simulations.

Use of a predictive display for the provision of flight safety in space missions requiring high-precision manual control

Theoretical and experimental studies were performed with the goal of determining the best kind of information presented on a predictive display to provide the highest accuracy in space mission execution, taking into account the requirement for reduced propellant consumption. The following space missions were studied: docking performed in manual and teleoperator control modes and lunar landing. By using a theoretical technique, algorithms for the flight path marker in manual and teleoperator control modes were developed. For the landing mission, a technique for determining the program trajectory and its calculation in real time was proposed. The experiments performed using a ground-based simulator demonstrated the high effectiveness of a predictive display and allowed to select the best variant of information to be presented on the display.

Identification and high-precision trajectory tracking control for space robotic manipulator

In this paper, an effective control and parameters identification scheme was proposed for high-precision trajectory tracking of space robotic manipulators. Our proposed control method employed a linear-extended-state-observer (LESO) based model predictive control (MPC) scheme. The feedback linearization approach was utilized to develop a model predictive controller. The optimization objective function was simplified to a standard quadratic programming (QP) problem for solution. To minimize the impact of the inaccuracy in the dynamics model, a LESO was designed to estimate the disturbance, and its convergence was demonstrated. In order to improve the accuracy of dynamic model, the physical consistency of inertial parameters was constrained using linear matrix inequality (LMI) techniques. Moreover, the dynamics parameters were estimated through semidefinite programming (SDP) techniques. To validate the effectiveness of the proposed control method, it was compared with existing controllers through simulations and experiments. The results demonstrated the superior performance of the proposed scheme, highlighting its potential for achieving high-precision trajectory tracking control in space robotic manipulators.

A Novel Longitudinal Control Method Integrating Driving Style and Slope Prediction for High-Efficiency HD Vehicles

Developing high-precision vehicle longitudinal control technology guided by ecological driving represents a highly promising yet challenging endeavor. It necessitates the fulfillment of the driver’s operational intentions, precise speed control, and reduced fuel consumption. In light of this challenge, this study presents a novel vehicle longitudinal control model that integrates real-time driving style analysis and road slope prediction. First, it utilizes spectral clustering based on Bi-LSTM automatic encoders to identify driver driving styles. Next, it examines the driving environment and predicts the current slope of the vehicle. Additionally, a fuzzy controller is designed to optimize control performance, adapt to various driving styles and slopes, and achieve better fuel efficiency. The research results indicate that the DS-MPC control model developed in this paper can effectively distinguish various driving modes and has high speed control accuracy while saving 3.27% of fuel.

Optimal Actuator Placement for the High-Precision Control of Quasi-Static Elastic Plates

Optimal Actuator Placement for the High-Precision Control of Quasi-Static Elastic Plates

Synchronous Vibration Force Suppression of Magnetically Suspended CMG Based on Modified Double SOGI-FLL

The mass imbalance of the rotor will produce the synchronous vibration force that is transmitted to the magnetically suspended control moment gyroscope (MSCMG) through the magnetic levitation stator, which affects the imaging performance of the satellite. The suppression of the synchronous vibration force needs the speed signal. In order to solve the synchronous vibration force of the MSCMG when the speed measurement sensor fails, this paper proposed an modified double second-order generalized integral frequency-locked loop (SOGI-FLL) method, which uses the frequency of the disturbance signal generated through the mass imbalance of the rotor to adaptively estimate the rotor speed and suppress the synchronous vibration force generated by the active magnetic bearing system. The phase compensation is introduced to ensure the stability of the system in full frequency band. The electromagnetic force is directly used as the input signal of the control algorithm to achieve zero magnetic force control. Simulation and experimental are carried out, and the results are given to prove that the algorithm proposed in this paper can accurately estimate the rotation speed and achieve the vibration force suppression in the full rotation speed range. It is of great significance for the high-precision control of the active magnetic bearing rotor system.

Optical flow-based closed-loop control of a multi-degree-of-freedom clamping-type ultrasonic motor.

Rotor speed and position detection are integral parts of the closed-loop control system for multi-degree-of-freedom (multi-DOF) ultrasonic motors. The non-contact speed detection method is important for the high-precision control of the spherical rotor. This paper proposes a closed-loop control method based on an optical flow sensor for the velocity-position control of a multi-DOF clamping-type ultrasonic motor. The optical flow information is analyzed using the conical L-K optical flow algorithm to obtain the rotor speed and position. An incremental PID control method is used to perform dual closed-loop positioning control of the motor regarding speed and position. An experimental platform for the optical flow sensor is designed, and the method's feasibility is verified experimentally.

A novel high-frequency resonance controllable pneumatic actuator and its high-precision motion trajectory tracking control

The strong nonlinearity and uncertainty of the pneumatic cylinder friction is one of the main reasons for the poor control accuracy of the pneumatic cylinder. For this reason, improving the friction characteristics of the pneumatic cylinder should contribute to the improvement of the pneumatic cylinder motion trajectory tracking accuracy. Reducing friction is a common method to improve the friction characteristics of pneumatic cylinders. In this paper, a novel longitudinal resonance friction-reducing pneumatic cylinder based on the principle of inverse piezoelectric effect is developed from the hardware perspective. Meanwhile, a promising adaptive robust controller (ARC) with online parameter identification and nonlinear robust control function is designed for the pneumatic position servo system from the software perspective. Finally, this paper focuses on exploring the possibility of further improving the accuracy by excitation of high-frequency resonance of the developed novel pneumatic actuator on the basis of the accuracy achievable at the software level (control algorithm). Experimental results show that friction reduction by means of high-frequency resonance can significantly improve the motion trajectory tracking accuracy of the pneumatic system. The maximum tracking error is reduced by 17.95% and 27.87% when tracking sinusoidal reference trajectories of 0.5 Hz and 0.25 Hz, respectively. The maximum tracking error is reduced by 15.79% when tracking a smooth square reference trajectory of 0.25 Hz. In addition, the designed controller is effective and robust to parameter variations and sudden perturbations.

High-Precision and Modular Decomposition Control for Large Hydraulic Manipulators

It is difficult to achieve a high-precision motion control in hydraulic manipulators due to their structural redundancy, strong coupling of closed-chain structures, and flow–pressure coupling. In this paper, a high-precision motion control method for hydraulic manipulators is proposed based on the traditional virtual decomposition control (VDC). The method proposed avoids an excessive virtual decomposition of the hydraulic manipulator and requires fewer model parameters than the traditional VDC. Further, the control precision improved by combining an adaptive real-time update of the inertial parameters. Compared with MBC, the proposed control method improved the motion accuracy of the hydraulic manipulator by more than 40% and 20% under elliptical and triangular trajectories. The simulation results showed that the proposed control method reduced the maximum position errors in Cartesian space by 90.4%, 86.8%, 23.6%, and 44.3% compared with PID and model-based control (MBC) in the absence of disturbances. The maximum position error in Cartesian space was reduced by 76.5% compared with that of MBC in a simulation with external disturbances. It can be seen from all the simulation results that with the proposed control method, the position error of the manipulator was less than 50 mm. The proposed control method effectively improved the motion precision of the examined hydraulic manipulator.

Dual PID Adaptive Variable Impedance Constant Force Control for Grinding Robot

High-precision and low-overshoot force control are important to guarantee the material removal rate and surface quality of robot grinding. However, traditional force control methods are subjected to positional disturbance, stiffness disturbance, contact process nonlinearity, and force-position coupling, leading to difficulties in robot constant force control. Therefore, how to achieve smooth, stable, and high-precision constant force control is an urgent problem. To address this problem, a dual PID adaptive variable impedance control is established (DPAVIC). Firstly, PD control is used to compensate for the force error, and PID is used to update the damping parameters to compensate for the disturbance. Secondly, a nonlinear tracking differentiator is used to smooth the desired force and reduce the contact force overshoot. Then, the stability, convergence, and effectiveness of the force control algorithm are verified via theoretical analysis, simulations, and experiments. The force tracking error and overshoot of a conventional impedance controller (CIC), adaptive variable impedance control (AVIC), and DPAVIC are analyzed. Finally, the algorithm is used in grinding experiments on a thin-walled workpiece. The force tracking error is controlled within ±0.2 N, and the surface roughness of the workpiece is improved to Ra 0.218 μm.

High precision control of direct-drive permanent magnet linear motor with adaptive friction compensation

To improve the control precision and stability of Direct-Drive Permanent Magnet Linear Motor (DPMLM) with frictional nonlinearity and uncertain disturbances at a low speed, an adaptive robust integral sign error control algorithm based on friction compensation of dual nonlinear observer is proposed in this study. An improved LuGre friction model is established to describe the friction phenomena of the system. The dual nonlinear observer is designed to observe the internal frictional state of the model. A parameter adaptive law is designed to perform parameter estimation of structured uncertainty. Robust integral of the sign of the error (RISE) term is designed to overcome the frictional nonlinear disturbances. The friction nonlinearity and parameter uncertainty are compensated by feedforward compensation. The bounded stability of the proposed controller is proved by Lyapunov stability theory. As suggested by the experimental results, RMSE index decreased by 10.8% and the control precision was improved effectively by the proposed control algorithm at a low speed.

Precision-milled simulated curved root canals in bovine dentine for the assessment of chemo-mechanical root canal preparation.

The aim was to develop a standardized curved root canal model in bovine dentine and to assess whether that natural substrate would behave differently from the resin in standard plastic training blocks when prepared chemo-mechanically. The impact of substrate microhardness on simulated canal transportation was considered. High-precision computer numerical control (CNC) milling was used to recreate a simulated root canal from a resin training block (Endo Training Bloc J-Shape, size 15) in longitudinally sectioned, dis- and re-assembled bovine incisor roots. Optical overlays obtained from 10 resin blocks were used to identify an average canal and program the CNC milling apparatus accordingly. Resin and dentine microhardness were measured. Simulated root canals in resin training blocks and their bovine counterparts were then instrumented at 37°C using Reciproc R25 instruments (VDW) with water or 17% EDTA (n = 10). Open-access image processing software was used to superimpose and analyse pre- and postoperative images obtained with a digital microscope. Centering ratios were averaged to indicate canal transportation. The effects of substrate and irrigant on canal transportation were assessed by two-way anova. Superimposed images showed that resin blocks under investigation varied considerably in terms of simulated canal length and curvature, whilst the milled canals were highly similar. The microhardness of dentine was more than three times higher than that of the resin. Conversely, canal transportation was considerably greater in dentine compared to resin, and in dentine had a tendency to be increased by EDTA. There was a strong effect of substrate on canal transportation (p < .001), no overall effect of irrigant, and a marginally significant interaction between irrigant and substrate (p = .077). CNC milling allows to create standardized simulated curved root canals in bovine dentine. These models may be useful to test and compare materials and concepts of chemo-mechanical root canal instrumentation. Microhardness is a bulk feature that does not predict the response to chemo-mechanical instrumentation of a composite material such as dentine.

Antisaturation fixed-time attitude tracking control based low-computation learning for uncertain quadrotor UAVs with external disturbances

External disturbances, uncertain parameters, asymmetric saturation input, and high computational burden can significantly damage the attitude tracking control performance of uncertain quadrotor unmanned aerial vehicles (UAVs). To accomplish the high-precision attitude tracking control, this study proposes an antisaturation fixed-time attitude tracking control based low-computation learning. Firstly, a fixed-time state observer is constructed to estimate the system states in fixed time. Secondly, by developing the fast fixed-time stable system with the time-varying gain function, a nonsingular fast fixed-time sliding mode surface is designed to improve the convergence speed and avoid the singularity problem. Thirdly, to solve the problem of asymmetric input saturation, an auxiliary compensation system is integrated to regulate the control inputs. Subsequently, an adaptive neural network (NN) technology is used to overcome the negative effects of external disturbances and uncertain parameters, where the designed adaptive mechanism is to adjust a virtual parameter online instead of the weight vector of the NN, which has the characteristics of low computational burden and simple structure. The Lyapunov-based stability analysis concludes that the closed-loop system is practical fixed-time stable and the tracking errors can converge to bounded regions around the origin in fixed time independently of the initial system states. Finally, comparative results are given to demonstrate that compared with the existing controllers, the controller developed in this study can achieve stronger robustness, faster convergence, and saturation elimination with lower error-index values.

An Overview of Flexible Jointed Robots

Background: Since the first industrial robots were created in the middle of the last century, robotics has shown strong growth prospects. Robotics has developed rapidly over time and is being used in more and more areas. Because of the need to minimize impact forces during robot movement, traditional rigid robots are no longer sufficient, flexible joints are more adaptable to the environment due to their adjustable stiffness and have higher application value in humancomputer interaction. Therefore, flexible jointed robots have become one of the research hotspots in recent years. Objective: Through a detailed analysis of the existing hardware and software control technologies of flexible joint robots, referring to papers and recent patents on flexible jointed robots, we aim to find ways to reduce the impact of flexible joint deformation of flexible joint robots and improve the overall force and position control accuracy of flexible joint robots. Methods: To categorize the hardware and software technologies of flexible jointed robots, to briefly explain the directions of the technologies categorized and to study them, to summarize the advantages and disadvantages of each type of technology respectively, and to outlook the future development trend. Results: Through the study and analysis of the various parts of the flexible joint robot, it can be seen that joint flexibility is mainly achieved through the drive motor and flexible components to achieve flexibility and then through the fusion control technology to control the deformation of the joint. Differences in structural materials affect the mechanical properties of robot motion. The detection and feedback accuracy of the sensor also has a significant impact on the control accuracy. Conclusion: The use of new motor technology, flexible component technology, material technology, and sensor technology, combined with improvements in software fusion control technology can reduce the impact of joint deformation, improve the control accuracy of joint flexibility, and achieve high-precision force-level control capability of flexible joint robots.

Compensation of friction and stick-slip uncertainties in trajectory tracking control of servo DC machines considering actuation constraints

Nowadays, electric motors are common in many precision instrument industries that require high-precision control. If a suitable model of a servo system is available, accurate results can be obtained using a model-based control algorithm. The DC motor is one of the most widely used systems in precision industries, for which a high-precision controller can be designed using its mathematical model with feedback on position and velocity. In such systems and other rotating systems, it is necessary to consider friction in the control system design. Friction enters the system in the form of resistant force or torque in both static and kinetic states, which causes uncertainty in the dynamic modeling of the system, the stick-slip phenomenon, and creates a deadzone in the actuation system. In this article, considering a switching dynamic model for different states of a system subject to friction which has a saturation limit on the control input and an actuation system dependent on the angular velocity feedback, first, the stable reaching laws in two modes of position control and velocity control for different dynamic model switch modes are defined. Then, the control input that forces the tracking error to follow the corresponding reaching law for each control mode is calculated. In the next step, according to the limitations of the actuation system, such as saturation and deadzone, using the filtering mechanism and optimal search for each control mode, the desired values are filtered and it is guaranteed that the control input will be chosen within the allowed range. Finally, using the optimal switching mode selection mechanism, the optimal control mode is selected and the voltage is calculated as the next step input.

Automated endpointing in microelectronics failure analysis using laser induced breakdown spectroscopy

Failure analysis of microelectronics is essential to identify the root cause of a device's failure and prevent future failures. This process often requires removing material from the device sample to reach the region of interest, which can be done through various destructive methods, such as mechanical polishing, chemical etching, focused ion beam milling, and laser machining. Among these, laser machining offers a unique combination of speed, precision, and controllability to achieve a high-throughput, highly targeted material removal. In using lasers for processing of microelectronic samples, a much-desired capability is automated endpointing which is crucial for minimizing manual checks and improving the overall process throughput. In this paper, we propose to integrate laser-induced breakdown spectroscopy (LIBS), as a fast and high-precision material detection and process control means, into an ultrashort pulsed laser machining system, to enable vertical endpointing for sample preparation and failure analysis of microelectronics. The capabilities of the proposed system have been demonstrated through several sample processing examples.

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.

Neural Network Learning Algorithms for High-Precision Position Control and Drift Attenuation in Robotic Manipulators

In this paper, different learning methods based on Artificial Neural Networks (ANNs) are examined to replace the default speed controller for high-precision position control and drift attenuation in robotic manipulators. ANN learning methods including Levenberg–Marquardt and Bayesian Regression are implemented and compared using a UR5 robot with six degrees of freedom to improve trajectory tracking and minimize position error. Extensive simulation and experimental tests on the identification and control of the robot by means of the neural network controllers yield comparable results with respect to the classical controller, showing the feasibility of the proposed approach.