Position Control Of Manipulator Research Articles

An Output Cooperative Controller for a Hydraulic Support Multi-Cylinder System Based on Neural Network Compensation

The straightness control of a fully mechanized working face is the key technology used in intelligent coal mining, so the position control of a hydraulic support multi-cylinder moving system is of great significance. However, due to the harsh environment of coal mines, complex friction, external disturbances, and the coupling relationship between adjacent cylinders, the accuracy of position control is restricted. Therefore, an output cooperative controller is proposed in this paper for a multi-cylinder system. A high-order sliding mode observer is utilized to estimate the system states with the only available output position signal. A neural network disturbance observer is applied to estimate the lump disturbance of the strict-feedback model, including the system uncertainty, disturbance force and the coupling force between adjacent cylinders. Then, continuous motion position tracking simulation is conducted and the estimation performance of the state observer and neural network is analyzed. Furthermore, a multi-cylinder collaborative control test rig is designed, and experiments based on the actual actions of the hydraulic support are conducted. The results show that the proposed output cooperative controller has an excellent position control performance compared with the traditional proportional–integral controller.

Position control of a digital electrohydraulic system with limited sensory data using double deep q-network controller

In this study, we propose a reinforcement learning controller for position control of a digital electrohydraulic system with independent metering valve structure. Our study addresses the inherent challenges of traditional control methods, such as the need for continuous pressure measurement and complex control structures. As a solution, a double deep q-network (DDQN) controller which relies solely on position feedback from D-EHS is suggested. A simulation environment was developed to train the DDQN controller, wherein the artificial neural network structure, training hyperparameters, and reward function were optimized through preliminary studies. The DDQN controller was trained using a sinusoidal position reference signal of a single frequency and evaluated experimentally for its position control performance. Tracking performance was assessed against various position reference signals, including ramp and sinusoidal signal with different frequencies. Robustness against external disturbances was also tested by increasing the nominal supply pressure by 20% and 40%. The results demonstrate that the DDQN controller successfully controls the digital electrohydraulic system and is achieving good tracking performance for the training position reference signal. Furthermore, the controller exhibits satisfactory tracking performance for non-training position reference signals, highlighting its ability to learn the digital electrohydraulic system dynamics with limited training data. Even under varying supply pressure conditions, the DDQN controller maintains an acceptable level of control performance. Our findings emphasize the generalizability and reliability of the DDQN reinforcement learning controller, making it a suitable candidate for application in digital electrohydraulic systems and contributing to the advancement of control theory research.

High frequency attitude determination of micro satellites based on FPGA

The accuracy and speed of satellite attitude calculation algorithms are one of the key factors affecting the performance of satellite attitude control. This article proposes a high-performance attitude calculation algorithm for micro satellites based on Field Programmable Gate Array (FPGA). This algorithm is designed and simplified based on the parallel characteristics and abundant computing resources of FPGA. The algorithm fully utilizes the parallel computing power of FPGA and designs a multi-stage pipeline for complex matrix operations in Kalman filtering. It can simultaneously complete data collection and final attitude determination result output, greatly improving the output frequency of attitude information and reducing output delay. The experimental results show that compared to traditional embedded processors, FPGA based attitude calculation has significant advantages in terms of speed.

In-Flight Calibration of Lorentz Actuators for Non-Contact Close-Proximity Formation Satellites with Cooperative Control

The non-contact close-proximity formation satellite (NCCPFS) is one of the technical solutions to improve the attitude performance, consisting of a payload module (PM) and a support module (SM). The non-contact Lorentz actuator (NCLA), as the core components of the NCCPFS, directly affect the attitude control performance of the entire satellite. In order to ensure the ultra-high attitude pointing performance and stability of the PM, an in-flight calibration method for the NCLAs based on minimum model error (MME) algorithm and Kalman filtering (KF) with cooperative control strategy is proposed in this article. In this method, the NCLAs generate a periodic nominal torque that causes the attitude of the PM to be periodically deflected. This periodic torque also reacts on the SM, and the SM counteracts this periodic torque through the flywheel to realize the cooperative tracking relative to the PM. Then, the gyroscope data are substituted into the MME algorithm to obtain the angular acceleration of the two modules, and the KF algorithm is adopted to observe the actual output torque of the NCLAs to complete the in-flight calibration of the NCLAs. Numerical simulation results show that the accuracy of the proposed calibration algorithm can reach about 8%, which proves the effectiveness of the proposed method.

Design and Position Control of a Bionic Joint Actuated by Shape Memory Alloy Wires.

Bionic joints are crucial for robotic motion and are a hot topic in robotics research. Among various actuators for joints, shape memory alloys (SMAs) have attracted significant interest due to their similarity to natural muscles. SMA exhibits the shape memory effect (SME) based on martensite-to-austenite transformation and its inverse, which allows for force and displacement output through low-voltage heating. However, one of the main challenges with SMA is its limited axial stroke. In this article, a bionic joint based on SMA wires and a differential pulley set structure was proposed. The axial stroke of the SMA wires was converted into rotational motion by the stroke amplification of the differential pulley set, enabling the joint to rotate by a sufficient angle. We modeled the bionic joint and designed a proportional-integral (PI) controller. We demonstrated that the bionic joint exhibited good position control performance, achieving a rotation angle range of -30° to 30°. The proposed bionic joint, utilizing SMA wires and a differential pulley set, offers an innovative solution for enhancing the range of motion in SMA actuated bionic joints.

Implementation of EnDat Interface Master Using Configurable Logic Block in MCU

In this study, we propose an implementation method of the Encoder Data (EnDat) interface master for slave encoders using only a configurable logic block (CLB) and a serial peripheral interface (SPI) integrated into microcontroller units. By programming the CLB device to execute logic functions and finite state machines designed for the EnDat interface master operation, we realize the EnDat and SPI clocks that are required for the EnDat interface master operation. This approach is cost-efficient because additional hardware components, such as a field-programmable gate array or a complex programmable logic device, are unnecessary for the master implementation. We build a one-axis feed drive system that is powered by an AC motor and equipped with an EnDat linear encoder for measuring table speed and position. By performing various experiments for table position and speed control based on the built feed drive system, we verify the performance and practical usefulness of the implemented EnDat interface master. The maximum EnDat clock frequency without the propagation delay compensation is achieved by 2 MHz, which can cope with 16 kHz control cycle frequency. The usefulness is demonstrated by showing the table speed and position control performance that are acceptable in real applications.

Utilization of PWM Signals in Automatic Parking Gate Speed Control Using PID System Modeling

Utilization of signals (Pulse Width Modulation) on the l298n motor driver and PID controller (Proportional Integral Derivative) is often used in industries, especially those that require robots as their automation medium, so that a process in robot automation does not only design system modeling, but is also required to implement a control system. angular position on a DC motor using the PID model. The PID control system in this study utilizes speed control with a PWM signal in the l298n motor driver and is applied as a DC motor angle position control module which is used for the parking doorstop system. The use of the trial error method is a suitable choice to be applied in finding values for the PID position control. This system keeps the speed and position in accordance with the set point when given a load as well as the ability of the system to catch up with the speed and position in order to reach the set point when the motor starts running are very important factors as a measure of speed and position control performance. because of its effectiveness, in the implementation of the parking gate latch produces a standard configuration of the PID controller with parameters Kp, Ki and Kd that can be determined so that the plant characteristics match the expected design criteria. In the trial error method, the most effective value was obtained with Kp = 10, Ki, 1.9 and Kd = 0.8 which resulted in steady state and no overshoot.

Design and control of a compliant robotic actuator with parallel spring-damping transmission

AbstractPhysically compliant actuator brings significant benefits to robots in terms of environmental adaptability, human–robot interaction, and energy efficiency as the introduction of the inherent compliance. However, this inherent compliance also limits the force and position control performance of the actuator system due to the induced oscillations and decreased mechanical bandwidth. To solve this problem, we first investigate the dynamic effects of implementing variable physical damping into a compliant actuator. Following this, we propose a structural scheme that integrates a variable damping element in parallel to a conventional series elastic actuator. A damping regulation algorithm is then developed for the parallel spring-damping actuator (PSDA) to tune the dynamic performance of the system while remaining sufficient compliance. Experimental results show that the PSDA offers better stability and dynamic capability in the force and position control by generating appropriate damping levels.

Analysis of Energy and Thermal Performance of High-Altitude Airship under Variable Attitude

The thermal problem of high-altitude airships has an essential impact on position control and energy system performance. Adjusting the airship’s attitude angle causes differences in thermal performance during position alterations. This paper studies an airship’s energy and thermal performance under variable attitudes. We establish an airship solar radiation and thermal model to analyze power output under different thermal conditions. The thermal performance of airships at varying pitch angles is investigated using computational fluid dynamic (CFD) software (Fluent V6.3.26). To determine the optimal distribution of pitch angles under various conditions, we have developed an optimization model that considers both the presence and absence of thermal influence. We have also assessed the impact of airship geometric parameters on the optimal pitch angle, considering the diversity of airship shapes. Our results demonstrate that pitch angle alterations significantly influence airships’ temperature and flow field distribution. But the degree of necessity of considering the thermal effect in calculating the optimal pitch angle distribution varies depending on the date and latitude, with the most vital need observed during low-latitude summer and the weakest during high-latitude winter. The findings of this research have significant reference value in selecting operation strategies and the control of operating performance for high-altitude airships.

Optimizing power consumption and position control in an electro-hydraulic system with cylinder bypass and NN-MPC

This study introduces an innovative approach to enhance the energy efficiency and position control performance of electro-hydraulic systems, employing a comprehensive comparative analysis. It presents and evaluates three control techniques: Proportional-Integral-Derivative (PID) control, Model Predictive Control (MPC), and Neural Network Model Predictive Control (NN-MPC). These methods are systematically assessed across varying load conditions. Notably, our research unequivocally establishes the exceptional performance of the NN-MPC approach, even when confronted with load variations. Furthermore, the study conducts an exhaustive examination of energy consumption by comparing a conventional system, where a flow control valve is not utilized as a hydraulic cylinder bypass, with a proposed system that employs a fully open Flow Control Valve (FCV). The results underscore the remarkable energy savings achieved, reaching up to 9% at high load levels.

Possibility of Quenching of Limit Cycles in Multi Variable Nonlinear Systems with Special Attention to 3X3 Systems

The present work proposes novel methods of Quenching self-sustained oscillations in the event of the existence of limit cycles (LC) in 3x3 non-linear systems. It explores the possibility of Stabilising/Quenching the LC by way of signal stabilization using high frequency dither signals both deterministic and random when 3X3 systems exhibit such self-sustained nonlinear oscillations under autonomous state. The present work also explores the suppression limit cycles of 3X3 systems using state feedback by either arbitrary pole placement or optimal selection of pole placement. The complexity involved, in implicit non-memory type nonlinearity for memory type nonlinearities, it is extremely difficult to formulate the problem. Under this circumstance, the harmonic linearization/harmonic balance reduces the complexity considerably. Furthermore, the method is made simpler assuming the whole 3X3 system exhibits the LC predominantly at a single frequency. It is equally a formidable task to make an attempt to suppress the limit cycles for 3X3 systems with memory type nonlinearity in particular. Backlash is one of the nonlinearities commonly occurring in physical systems that limit the performance of speed and position control in robotics, the automation industry, and other occasions of modern applications. The proposed methods are well illustrated through examples and substantiated by digital simulation (a program developed using MATLAB CODES) and the use of the SIMULINK Toolbox of MATLAB software.

Robust Position Control of a Continuum Manipulator Based on Selective Approach and Koopman Operator

Continuum manipulators have infinite degrees of freedom and high flexibility, making it challenging for accurate modeling and control. Some common modeling methods include mechanical modeling strategy, neural network strategy, constant curvature assumption, etc. However, the inverse kinematics of the mechanical modeling strategy is difficult to obtain while a strategy using neural networks may not converge in some applications. For algorithm implementation, the constant curvature assumption is used as the basis to design the controller. When the driving wire is tight, the linear controller under constant curvature assumption works well in manipulator position control. However, this assumption of linearity between the deformation angle and the driving input value breaks upon repeated use of the driving wires which get inevitably lengthened. This degrades the accuracy of the controller. In this work, the Koopman theory is proposed to identify the nonlinear model of the continuum manipulator. Under the linearized model, the control input is obtained through model predictive control (MPC). As the lifted function can affect the effectiveness of the Koopman operator-based MPC (K-MPC), a novel design method of the lifted function through the Legendre polynomial is proposed. To attain higher control efficiency and computational accuracy, a selective control scheme according to the state of the driving wires is proposed. When the driving wire is tight, the linear controller is employed; otherwise, the K-MPC is adopted. Finally, a set of static and dynamic experiments has been conducted using an experimental prototype. The results demonstrate high effectiveness and good performance of the selective control scheme.

Position control performance analysis of linear actuator in swashplate-controlled electro hydrostatic actuation system

The position control of an energy efficient electrohydraulic actuation system is a decisive characteristic of its performance. In position control applications, a servo valve and/or variable displacement pump are vital to control the position of the linear actuator. In this open-loop control experimental work, the position of a linear actuator having a stroke length of 0.2 m is controlled by a swashplate-controlled electro hydrostatic actuation system. LabVIEW is used to create the control algorithm, and the National Instrument compact-RIO controller is used to control the voltage supply. The National Instruments controller processes sinusoidal and square demand signals at frequencies of 1/16, 1/12, 1/8, and 1/4 Hz. Open-loop control performance is predominantly dependent on the appropriate tuning of the voltage supply. Control performance is evaluated using the parameters integrated absolute error, integrated square error, integrated time absolute error, and integrated time square error. In comparison to square demand, it has been found that sinusoidal demand offers better position control accuracy, and square demand also offers appropriate control accuracy only at lower frequencies (1/16 Hz).

Estimation and compensation of cutting force induced position error in robot machining system

Recently, industrial robots have been widely used in manufacturing due to their various advantages when compared with other equipment, such as maneuverability in a wide range of workspaces, high degrees of freedom, and flexibility. However, due to the low stiffness, they are difficult to be used for precision metal cutting process those require high position control performance under cutting force. This paper proposes a compensation method that estimates the position error induced by the cutting force and compensates the error by controlling the workpiece position by using additional two-axis servo system. The cutting force model was constructed to estimate the cutting force generated during milling without sensors. The kinematic and stiffness models of the industrial robot were developed to calculate the angular error of each joint and position error of the tool center position caused by cutting force. To verify the performance of the proposed compensation method, series of experiments were conducted under various cutting conditions and compared with traditional on-line compensation method. The position accuracy was increased by 63.68 % after the application of the proposed compensation method.

Aluminum Eddy Currents in PSRM Stator Arrays: Analysis and Mitigation for Improved Control Precision and Energy Efficiency

In this article, the influence of aluminum eddy currents in the PSRM stator array on electromagnetic properties and control performance is investigated. A model is developed to analyze the eddy current density distribution based on Maxwell’s equations, and an inductance model is derived that considers the eddy current effect. The effect of aluminum eddy currents on PSRM position control performance is qualitatively analyzed. The distribution of aluminum eddy currents and ohmic loss is verified through finite element analysis. The validity of the developed inductance model is experimentally verified. A material substitution method is proposed to eliminate the aluminum eddy current. Experimental results show that the position control accuracy of the PSRM prototype is improved by an average of 6.94% after the elimination of aluminum eddy currents, while the motor efficiency is improved by 6.51%.

The PID in the Control of Bilateral Teleoperation System with Time-Varying Delays: An Experimental Approach

The control of bilateral teleoperation systems with time-varying delays is a challenging problem that is usually dealt with advanced control techniques. The well-known controllers, such as PD or PID, are scarcely employed and usually in conjunction with other approaches or at least with gravity compensation. In this contribution we intend to show, experimentally, that the standard PID controller exhibits good performance and robustness in position control for teleoperators with variable delays. The results obtained are compared with a well-known algorithm used for teleoperator control.

Hierarchical perturbation compensation system with ERL sliding mode controller in a quadrotor

This article addresses the problem of perturbation in Unmanned Air Vehicle (UAV) quadrotors. Three subsystems are designed to provide a continuous and precise estimation of perturbation and residual perturbation. The three subsystems form a Hierarchical Perturbation Compensator (HPC), which is built to compensate for system dynamics uncertainties, non-modeled dynamics, and external disturbances. The nonlinear control Exponential Reaching Law Sliding Mode (ERLSM) is utilized with the HPC. Lyapunov stability analysis proves the stability of the entire compensator-controller system. This system has the ability to decrease unknown perturbation either external or internal. It also has the ability to maintain full control of the six-degree-of-freedom quadrotor. The system performance for position, altitude, and attitude control is demonstrated by analysis, simulation, and experiments.

Adaptive Super-Twisting Sliding Mode Control of Underwater Mechanical Leg with Extended State Observer

Underwater manipulation is one of the most significant functions of the deep-sea crawling and swimming robot (DCSR), which relies on the high-accuracy control of the body posture. As the actuator of body posture control, the position control performance of the underwater mechanical leg (UWML) thus determines the performance of the underwater manipulation. An adaptive super-twisting sliding mode control method based on the extended state observer (ASTSMC-ESO) is proposed to enhance the position control performance of the UWML by taking into account the system’s inherent nonlinear dynamics, uncertainties, and the external disturbances from hydrodynamics, dynamic seal resistance, and compensation oil viscous resistance. This newly designed controller incorporates sliding mode (SMC) feedback control with feedforward compensation of the system uncertainties estimated by the ESO, and the external disturbances of the hydrodynamics by fitting the parameters, the dynamic seal resistance, and the compensation oil viscous resistance to the tested results. Additionally, an adaptive super-twisting algorithm (AST) with integral action is introduced to eliminate the SMC’s chattering phenomenon and reduce the system’s steady-state error. The stability of the proposed controller is proved via the Lyapunov method, and the effectiveness is verified via simulation and comparative experimental studies with SMC and the adaptive fuzzy sliding mode control method (AFSMC).

Conceptual design and control method for a non-contact annular electromagnetic stabilized satellite platform

Disturbance-Free Payload (DFP) spacecraft can meet the requirements of ultra-high attitude pointing accuracy and stability for future space missions. However, as the main control actuators of DFP spacecraft, Linear Non-Contact Lorentz Actuators (LNCLAs) have control output problems with six-degree-of-freedom coupling and nonlinear effects, which will affect the attitude control performance of DFP spacecraft. To solve this problem, a novel concept for Non-Contact Annular Electromagnetic Stabilized Satellite Platform (NCAESSP) is proposed in this study. The concept is centered on replacing the LNCLAs with a non-contact annular electromagnetic actuator to solve the two problems mentioned above. Furthermore, for the different control requirements of the payload module and the support module of the NCAESSP, a high-precision attitude controller based on the robust model matching method and a dual quaternion-based adaptive sliding mode controller are proposed. Additionally, the simulation results verify the feasibility and effectiveness of the proposed approach.

PPO-Based Attitude Controller Design for a Tilt Rotor UAV in Transition Process

The complex aerodynamic changes of the tilt-rotor UAV (TRUAV) in the transition process show strong nonlinearity, which brings a great impact on the stability of the vehicle attitude. This study aims to design a PPO-based RL controller for attitude control in the transition process. A reinforcement-learning PPO approach is used to learn the control strategy by interacting directly with the environment. And the reward function is designed and improved for the transition process. The performance of the proposed controller is tested and compared by simulation. The results show that the PPO algorithm is more suitable for the tilt-rotor transition process control than the A2C algorithm. Our proposed reward function improves the attitude control performance and the designed RL controller has good adaptability to changes in the takeoff weight, the diagonal wheelbase and the tilt rate. This study highlights the effectiveness and potential of reinforcement learning for tilt-rotor UAV transition process attitude control. These findings contribute to the advancement of autonomous flight systems by providing insights into the application of reinforcement learning algorithms. These results have important implications for the development of intelligent flight control systems and could guide future research in this area.