Accurate Position Control Research Articles

Modeling and Cascade Control of a Pneumatic Positioning System

Abstract A robust cascade control system based on active disturbance rejection controller (ADRC) is originally developed for accurate position control of a pneumatic servo system, which is usually characterized by nonlinearity, uncertainty, and disturbance. The proposed control system consists of inner and outer control loops. Particularly, a linear ADRC (LADRC) is utilized to adjust valve position for a linear spool valve dynamics in the inner loop. A nonlinear ADRC (NADRC) is designed to control the position of a nonlinear pneumatic actuator subsystem in the outer loop. LADRC and NADRC contain linear and nonlinear extended state observers (ESOs), respectively. The ESO can estimate both unknown nonlinear dynamics and external disturbances and thus make the ADRC robust against system uncertainties and disturbances. Simulation results successfully demonstrate the effectiveness and robustness of the proposed cascade control system. The stabilities of the inner and outer control loops were proved separately using a Lyapunov approach.

Energy-Efficiency-Oriented Vision Feedback Control of QCSP Systems: Linear ADRC Approach

How to save the energy of unmanned aerial vehicles (UAVs) and then enable long-distance transport is a very real and difficult task. However, for UAVs, the classic object detection algorithm, such as the deep convolutional neural network–based object detection algorithm and the classic flight control algorithm, such as the PID-based position control algorithm, require significant energy, which limits the application scenarios of the UAV system. In view of this problem, this paper proposes a lightweight object detection network and a linear active disturbance rejection controller (LADRC) for the quadrotor with the cable-suspended payload (QCSP) system to improve energy efficiency. The system uses a YOLOV3 network and embeds it into the Jesson NX mobile platform to accurately detect the target position. Furthermore, a nonlinear velocity controller with a cable-suspended structure to control the velocity of the payload, a LADRC algorithm is adopted to achieve fast and accurate control of the payload position. Simulations and real flight experiments show that the proposed object detection algorithm and the LADRC control strategy can save the energy of drone effectively.

A Trajectory Tracking Control Based on a Terminal Sliding Mode for a Compliant Robot with Nonlinear Stiffness Joints.

A nonlinear stiffness actuator (NSA) can achieve high torque/force resolution in the low stiffness range and high bandwidth in the high stiffness range. However, for the NSA, due to the imperfect performance of the elastic mechanical component such as friction, hysteresis, and unmeasurable energy consumption caused by former factors, it is more difficult to achieve accurate position control compared to the rigid actuator. Moreover, for a compliant robot with multiple degree of freedoms (DOFs) driven by NSAs, the influence of every NSA on the trajectory of the end effector is different and even coupled. Therefore, it is a challenge to implement precise trajectory control on a robot driven by such NSAs. In this paper, a control algorithm based on the Terminal Sliding Mode (TSM) approach is proposed to control the end effector trajectory of the compliant robot with multiple DOFs driven by NSAs. This control algorithm reduces the coupling of the driving torque, and mitigates the influence of parametric variation. The closed-loop system’s finite time convergence and stability are mathematically established via the Lyapunov stability theory. Moreover, under the same experimental conditions, by the comparison between the Proportion Differentiation (PD) controller and the controller using TSM method, the algorithm’s efficacy is experimentally verified on the developed compliant robot. The results show that the trajectory tracking is more accurate for the controller using the TSM method compared to the PD controller.

Optimization of Geomagnetic and Solar Reference Vector Algorithms for Micro-Nano Satellites

To optimize the geomagnetic reference vector and the solar reference vector calculation method, this paper proposes a geomagnetic fitting algorithm and simplifies the DE430 ephemeris structure to speed up the determination rate of the geomagnetic and solar reference vectors. The two optimized reference vector determination methods are simulated on the Attitude Measurement Unit (AMU). The simulation results show that the single-step elapsed time of the geomagnetic fitting algorithm is reduced by 99.5% compared with the IGRF-13 geomagnetic model algorithm, and the data capacity is reduced by 97.3% compared with the look-up table method. The data capacity of the simplified ephemeris algorithm is 66.9% lower than that of the DE430 ephemeris algorithm, and the calculation accuracy is nearly 3 orders of magnitude higher than that of the approximate calculation method. This method can significantly shorten the attitude determination time and increase the attitude determination frequency, dramatically improving attitude determination accuracy and attitude control accuracy. The AMU supported by these two algorithms has sound engineering practical value.

Magnetically Actuated Cell-Robot System: Precise Control, Manipulation, and Multimode Conversion.

Border-nearing microrobots with self-propelling and navigating capabilities have promising applications in micromanipulation and bioengineering, because they can stimulate the surrounding fluid flow for object transportation. However, ensuring the biosafety of microrobots is a concurrent challenge in bioengineering applications. Here, macrophage template-based microrobots (cell robots) that can be controlled individually or in chain-like swarms are proposed, which can transport various objects. The cell robots are constructed using the phagocytic ability of macrophages to load nanomagnetic particles while maintaining their viability. The robots exhibit high position control accuracy and generate a flow field that can be used to transport microspheres and sperm when exposed to an external magnetic field near a wall. The cell robots can also form chain-like swarms to transport a large object (more than 100 times the volume). This new insight into the manipulation of macrophage-based cell robots provides a new concept by converting other biological cells into microrobots for micromanipulation in biomedical applications.

UKF-Based Parameter Estimation and Identification for Permanent Magnet Synchronous Motor

The accuracy of rotor position estimation determines the performance of the sensorless control system of a permanent magnet synchronous motor. In order to realize the accurate control of rotor position and speed, it is necessary to identify the motor parameters. Modeling and simulation of the state estimation are investigated for a permanent magnet synchronous motor with parameter identification based on the unscented Kalman filter (UKF) in this article. Based on the mathematical model of the motor, the unscented Kalman filter is used to identify the rotor flux and quadrature axis inductance simultaneously, and the identified parameters are used to update the motor model in the sensorless vector control algorithm. The simulation results show that the unscented Kalman filter can converge to the real value in a short time with small errors. It can follow the changes of motor parameters well and achieve high-precision speed and position estimation.

Unified Accurate Attitude Control for Dual-Tiltrotor UAV with Cyclic Pitch Using Actuator Dynamics Compensated LADRC.

This paper proposes a unified attitude controller based on the modified linear active disturbance rejection control (LADRC) for a dual-tiltrotor unmanned aerial vehicle (UAV) with cyclic pitch to achieve accurate attitude control despite its nonlinear and time-varying characteristics during flight mode transitions. The proposed control algorithm has higher robustness against model mismatch compared with the model-based control algorithms. The modified LADRC utilizes the state feedbacks from the onboard sensors like IMU and Pitot tube instead of the mathematical model of the plane. It has less dependency on the accurate dynamics model of the dual-tiltrotor UAV, which can hardly be built. In contrast to the original LADRC, an actuator model is integrated into the modified LADRC to compensate for the non-negligible slow rotor flapping dynamics and servo dynamics. This modification eliminates the oscillation of the original LADRC when applied on the plant with slow-response actuators, such as propeller and rotors of the helicopter. In this way, the stability and performance of the controller are improved. The controller replaces the gain-scheduling or the control logic switching by a unified controller structure, which simplifies the design approach of the controller for different flight modes. The effectiveness of the modified LADRC and the performance of the unified attitude controller are demonstrated in both simulation and flight tests using a dual-tiltrotor UAV. The attitude control error is less than ±4° during the conversion flight. The control rising time in different flight modes is all about 0.5 s, despite the variations in the airspeed and tilt angle. The flight results show that the controller guarantees high control accuracy and uniform control quality in different flight modes.

Continuum Robot Proprioception: The Ionic Liquid Approach

Slender continuum robots are uniquely placed to address inspection and intervention tasks in difficult-to-access environments. Tasks such as minimally invasive surgery and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> maintenance of complex machinery require dexterous robots with accurate motion control, and benefit from instruments with small diameters and large internal passages for services. Intrinsic proprioception, or built-in position sensory feedback, has been described in prior work on continuum and soft robots but seldom employed for motion closed-loop control. In this research article, we present a novel tubular resistive stretch sensor with ionic liquid conductors to enable closed-loop position control of low-cost, 3-D printed continuum robots. We describe a methodology for sensor characterization and calibration drawing from a model of their behavior under strain, allowing us to apply four stretch sensors as proprioceptive feedback for motion control of a four-axis slender continuum manipulator. We demonstrate a substantial (approximately 65%) improvement in position control accuracy and repeatability over open-loop methods and show a promising step toward low-cost, scalable position feedback for slender continuum robots.

Rigid-flexible coupling identification and attitude control based on deep neural networks

Rigid-flexible coupling significantly affects the attitude control accuracy during attitude maneuvering of spacecraft with large flexible appendages. On-orbit identification of flexible parameters such as modal frequency is very important for attitude control. However, large errors could exist in current identification methods, especially for extreme scenarios such as large deformation or configuration transformation of spacecraft. Unlike previous studies that identified natural frequencies or modal shapes, this paper proposes a method of directly estimating the rigid-flexible coupling term based on deep neural networks (DNNs). By using the neural network (NN), the proposed identification method is independent of the specific dynamic model and has better adaptability. We establish a rigid-flexible dynamic model considering uncertainties and analyze the possibility of identifying the rigid-flexible coupling term in the attitude dynamic equation through selected system states. To verify the feasibility of training the neural networks mapping from system states to the coupling term, we design a numerical experiment. Five attitude maneuvers with different target attitude angles are conducted with the data collected for training. The experimental results show that all estimation errors of neural networks are relatively small. Based on this, we further propose an improved PD controller. We assume that the DNNs can be well trained offline, followed by online prediction of the rigid-flexible coupling term to improve attitude control accuracy. Five random attitude maneuvers are performed for offline training, and a large angle attitude maneuver under the proposed improved PD controller is simulated. The experiment proves that the improved PD controller is effective and can improve system performance. The Elman neural network appears the best choice for rigid-flexible estimation and the improved PD controller.

Composite anti-disturbance position and attitude control for spacecrafts with parametric uncertainty and flexible vibration

The rendezvous and proximity operations with respect to a tumbling non-cooperative target pose high requirement for the position and attitude control accuracy of servicing spacecraft. However, multiple disturbances including parametric uncertainties, flexible vibration, and unknown nonlinear dynamics degrade the control performance significantly. In order to enhance the system anti-disturbance ability, this paper proposes a composite anti-disturbance control law for the spacecraft position and attitude tracking. Firstly, the relative position and attitude dynamic models with multiple disturbances are established, where the refined descriptions of multiple disturbances are accomplished based on their characteristics. Then, by combining a dual Disturbance Observer-Based Control (DOBC) and a sliding mode control, a composite controller with hierarchical architecture is proposed, where the dual DOBC in the feedforward channel is used to reject the flexible vibration, environment disturbance, and complicated nonlinear dynamics, while the parametric uncertainties are attenuated by the sliding mode control in the feedback channel. Stability analysis is carried out for the closed-loop system by unifying the sliding mode dynamics and observer dynamics. Finally, the effectiveness of the proposed controller is verified via numerical simulation and hardware-in-the-loop test.

A Simulation and Experimental Study on Identification of an Electromechanical System

The current applications in electromechanical energy conversion demand highly accurate speed and position control. For this purpose, a better understanding of the motion characteristics and dynamic behavior of electromechanical systems including nonlinear effects is needed. In this paper, a suitable model of Permanent Magnet Direct Current (PMDC) motor rotating in two directions is developed for identification purposes. Model is parameterized and identified via simulation and using real experimental data. Linear and nonlinear models for the system are built for identification, and the effective nonlinearities in the system, which are Coulomb friction and dead zone, are integrated into the nonlinear model. A Weiner- Hammerstein nonlinear system description is used for identification of the model. MATLAB is selected as the investigating tool, and a simulation model is used to observe the error between the simulated and estimated outputs. Identification of the linear and nonlinear system models using experimental data is performed using the least squares (LS) and recursive least squares (RLS) methods. Performance of the model and identification method with the real time experiments are presented numerically and graphically, revealing the advantages of the proposed nonlinear identification approach.

Nonlinear cascade control of an electro‐hydraulic actuator with large payload variation

AbstractElectro‐hydraulic actuators have been widely used in industrial production, but the unknown variable payload seriously affects its position control accuracy. Therefore, a radial basis function neural network disturbance observer is designed to estimate the lumped disturbance force through strong online learning ability in the absence of force sensor. Besides, a nonlinear cascade controller with double loop structure is proposed in this paper. A global fast terminal sliding mode control method is firstly applied in the outer loop position system, which can eliminate chattering and improve convergence speed comparing to traditional sliding mode control. The inner loop force system adopts a backstepping control method to calculate the actual input of the whole system. Theoretical analysis indicates that the proposed controller is stable even if existing time‐variant disturbance. Moreover, three comparative controllers are designed and tested in both simulations and experiments. Comparative results show that the developed method has absolute average errors of 1.14 and 0.49 mm in different position tracking, which means more satisfactory tracking performance compared to the contrast controllers.

Position Control Algorithm of Fuzzy Adaptive PID of Hydraulic Interconnected Suspension Under Load Impact Disturbance

Position control accuracy of hydraulic interconnected suspension (HIS) for agricultural vehicle is unsatisfied under load impact conditions. In order to address this problem, advanced control methods were studied in this paper. The technical scheme of HIS was developed firstly. The transfer function from proportional valve spool displacement to hydraulic cylinder piston displacement was derived and then the parameters of the transfer function were also identified. The PID, sliding mode control (SMC) and fuzzy adaptive PID (FAPID) control algorithms were designed. The co-simulation of AMESim and SIMULINK was adopted to compare and analyze the control characteristics of the three algorithms. An experimental platform was also built to verify the improvement effect. The research conclusions show that when the HIS operates under load impact condition, for FAPID algorithm, the rise time is reduced by 0.27s, the maximum overshoot is reduced by 9.83mm, and the absolute value of average error is decreased by 62.62% compared with PID control algorithm. The response speed of SMC is the fastest, but there is a large chattering in the steady-state displacement. The designed FAPID control algorithm balances the advantages of fast response, high control precision and good stability, and the control performance is better than that of SMC and PID control algorithms. The research methods in this paper can provide reference value for position control accuracy improvement of hydraulic suspension.

Robust Control Design for Accurate Trajectory Tracking of Multi-Degree-of-Freedom Robot Manipulator in Virtual Simulator

Robot manipulators have complex dynamics and are affected by significant uncertainties and external disturbances (perturbations). Consequently, determining the exact mathematical model of a robot manipulator is a tedious task. Accordingly, accurate trajectory tracking is a dominant feature in the design of position control for robot manipulators. The main objective of this research is to design a robust and accurate position control for a robot manipulator despite the absence of an exact model. For this purpose, an extended state observer (ESO)-based sliding mode control (SMC) is proposed. The main concept in the ESO is to define and estimate the assumed perturbation, which includes known and unknown system dynamics, uncertainties, and external disturbances. Additionally, the ESO estimates the system states. This estimated perturbation information, which is combined with the SMC input, is utilized as a feedback term to compensate for the effect of the actual perturbation. The perturbation compensation improves the controller performance, resulting in a slight position error, less sensitivity to perturbation, and a small switching gain required for the SMC. The advantage of the proposed algorithm is that it only requires partial state information and position feedback. Thus, identifying the system parameters for the nominal model before designing the controller is unnecessary. The proposed algorithm is implemented and compared with the conventional SMC and the SMC with a sliding perturbation observer (SMCSPO) in a virtual environment based on MATLAB SimMechanics. The comparison results validate the robustness of the proposed technique in the presence of perturbation and show that the technique has a significantly reduced trajectory tracking error than the conventional SMC and SMCSPO.

Study and design of an active magnetorquer actuator model for nanosatellites

This paper focuses on the study and the design of an air core magnetorquer model dedicated to the 1U CubeSat (10×10×10 cm3). The objective is to obtain a solution which is able to provide accurate attitude control while having the smallest possible dimensions, electrical power, and total mass. To this end, the first part will provide theoretical mathematical knowledge on the laws of the coil to design an electromagnetic air core actuator. Then, this paper presents comparisons of the performances obtained by varying the type of material and the shape of the coil. Towards the end, the effect of temperature variation in LEO orbit is taken into consideration to predict the generated magnetic moment.

Dynamic Behavior Analysis and Stability Control of Tethered Satellite Formation Deployment.

In recent years, Tethered Space Systems (TSSs) have received significant attention in aerospace research as a result of their significant advantages: dexterousness, long life cycles and fuel-less engines. However, configurational conversion processes of tethered satellite formation systems in a complex space environment are essentially unstable. Due to their structural peculiarities and the special environment in outer space, TSS vibrations are easily produced. These types of vibrations are extremely harmful to spacecraft. Hence, the nonlinear dynamic behavior of systems based on a simplified rigid-rod tether model is analyzed in this paper. Two stability control laws for tether release rate and tether tension are proposed in order to control tether length variation. In addition, periodic stability of time-varying control systems after deployment is analyzed by using Floquet theory, and small parameter domains of systems in asymptotically stable states are obtained. Numerical simulations show that proposed tether tension controls can suppress in-plane and out-of-plane librations of rigid tethered satellites, while spacecraft and tether stability control goals can be achieved. Most importantly, this paper provides tether release rate and tether tension control laws for suppressing wide-ranging TSS vibrations that are valuable for improving TSS attitude control accuracy and performance, specifically for TSSs that are operating in low-eccentricity orbits.

A contraction length feedback method for the McKibben pneumatic artificial muscle

McKibben pneumatic artificial muscle (PAM) is a popular soft actuator used in robots, with excellent performance comparable to organic muscles. However, owing to a lack of feedback on contraction length, it is difficult to achieve highly precise position control in open-loop control systems using the PAM. For a given input air pressure, the end position of the PAM varies with load due to soft characteristics. To this end, this study proposes a simple and independent soft radial sensor, which is composed of liquid metal (gallium-indium-stannum) and a silicone substrate. Based on deformation characteristics, the contraction length can be evaluated from the expansion radius of the PAM measured by the proposed sensor. A model is also developed to demonstrate the relationship between the resistance of the sensor and the contraction length of the PAM. In addition, the effects of structure parameters, such as cross-section area of the liquid metal and the thickness-to-radial width ratio of the sensor on the performance are experimentally analyzed, and the results are compared to the predicted values to verify the validity of the model. Furthermore, a closed-loop system is developed on the basis of the proposed sensor. These results demonstrate that the position control accuracy of the PAM can be significantly improved under various loads.

Research on position offset compensation of underwater manipulator

A compensation method for end position offset of underwater manipulator is presented in this paper. Firstly, the end deformation of the underwater manipulator is obtained by ANSYS analysis, and then the end position offset equation is obtained by MATLAB curve fitting. Finally, the equation is added to the kinematic model of the underwater manipulator, which improves the accuracy of the kinematic model of the underwater manipulator and lays a foundation for the accurate position control of the underwater manipulator.

Active disturbance rejection attitude control of unmanned quadrotor via paired coevolution pigeon-inspired optimization

PurposeThe purpose of this paper is to develop a novel active disturbance rejection attitude controller for quadrotors and propose a controller parameters identification approach to obtain better control results.Design/methodology/approachAiming at the problem that quadrotor is susceptible to disturbance in outdoor flight, the improved active disturbance rejection control (IADRC) is applied to design attitude controller. To overcome the difficulty that adjusting the parameters of IADRC controller manually is complex, paired coevolution pigeon-inspired optimization (PCPIO) algorithm is used to optimize the control parameters.FindingsThe IADRC, where nonlinear state error feedback control law is replaced by non-singular fast terminal sliding mode control law and a third-order tracking differentiator is designed for second derivative of the state, has higher control accuracy and better robustness than ADRC. The improved PIO algorithm based on evolutionary mechanism, named PCPIO, is proposed. The optimal parameters of ADRC controller are found by PCPIO with the optimization criterion of integral of time-weighted absolute value of the error. The effectiveness of the proposed method is verified by a series of simulation experiments.Practical implicationsIADRC can improve the accuracy of attitude control of quadrotor and resist external interference more effectively. The proposed PCPIO algorithm can be easily applied to practice and can help the design of the quadrotor control system.Originality/valueAn improved active disturbance rejection controller is designed for quadrotor attitude control, and a hybrid model of PIO and evolution mechanism is proposed for parameters identification of the controller.

Reinforcement learning-based dynamic position control of mobile node for ocean sensor networks

In this paper, a novel dynamic position control (PC) approach for mobile nodes (MNs) is proposed for ocean sensor networks (OSNs) which directly utilizes a neural network to represent a PC strategy. The calculation of position estimation no longer needs to be carried out in the proposed scheme, so the localization error is eliminated. In addition, reinforcement learning is used to train the PC strategy, so that the MN can learn a more highly accurate and fast response control strategy. Moreover, to verify its applicability to the real-world environment, we conducted field experiment deployment in OSNs consisting of a MN designed by us and some fixed nodes. The experimental results demonstrate the effectiveness of our proposed control scheme with impressive improvements on PC accuracy by more than 53% and response speed by more than 15%.