Motion Control Of Manipulators Research Articles

V2X assisted co‐design of motion planning and control for connected automated vehicle

AbstractThe rapid development of vehicle‐to‐everything (V2X) communication technologies significantly promotes the revolution of intelligent transportation systems. V2X communication is expected to play a critical role in enhancing the safety and efficiency of connected and automated vehicles (CAVs), especially for mixed traffic scenarios. Additionally, the computational and storage capabilities of roadside units (RSUs) will be harnessed to effectively enhance the motion planning and control performance of CAVs within the constraints of limited on‐board computational resources. Thus, a V2X assisted co‐design of motion planning and control algorithm for CAVs to improve their situational awareness and computational efficiency is proposed. Under this architecture, a pre‐planning algorithm is proposed first to utilize the computational and storage capabilities of RSUs and generate feasible trajectories for different driving tasks. By analysing the relationship between driving risk index and motion planning performance, an online‐planning algorithm is derived to modify the pre‐planned trajectories in real‐time with static or dynamic obstacles. Furthermore, the lateral and longitudinal control of the vehicle using the Frenet coordinate system is decoupled. The lateral control employs an offline linear quadratic regulator (LQR) from RSUs to control the steering angle of the vehicle. The longitudinal control employs a dual‐loop PID to control the throttle opening of the vehicle. The performance of the proposed framework is evaluated and demonstrated by a Carsim‐Prescan simulation study in different mixed traffic scenarios. Compared with conventional methods, the proposed method improves the computational efficiency by 23% and reduces the collision rate by 13%.

An SMC-Based Accurate and Robust Load Speed Control Method for Elastic Servo System

In this paper, a modified sliding mode speed controller is designed in order to improve the load speed control performance of an elastic motor drive system with internal and external disturbances. Firstly, based on the load speed deviation and its first-order and second-order differentials, a two-dimensional sliding surface function is presented. The parameters of the sliding surface are determined by a novel particle swarm optimization (PSO) method. The method has improved inertia weights and evaluation functions, which can improve the accuracy and efficiency of the parameter search and enhance the immunity and robustness of the system. Secondly, on the basis of the integral of time-weighted absolute error (ITAE) criterion, the parameters of the exponential approach law are determined, which improves the tracking accuracy. Finally, the designed sliding mode control (SMC) with high tracking accuracy, fast dynamics, and strong robustness is verified by both simulations and experiments.

Energy-Saving Breakthrough in the Point-to-Point Control of a Flexible Manipulator

This study aims to contribute academically valuable insights into energy-efficient drives for the positioning control of flexible structures. It focuses on the point-to-point (PTP) motion control of a flexible manipulator to suppress residual vibration and reduce driving energy simultaneously. The driving energy for PTP motion is influenced by the initial deflection of the flexible manipulator. Considering this phenomenon, the study proposes a trajectory planning method for the joint angle of a flexible manipulator. In this method, the evaluation function is defined as the sum of drive torques, and its minimization through particle swarm optimization generates an optimal trajectory that minimizes drive energy and suppresses residual vibration. Numerical simulations indicate that significant energy savings can be achieved by actively deforming the manipulator. These simulation results are corroborated by experimental data, which demonstrate the practical applicability and effectiveness of the proposed method.

An Integrated Control Framework for Torque Vectoring and Active Suspension System

Four-wheel independently driven electric vehicles (FWID-EV) endow a flexible and scalable control framework to improve vehicle performance. This paper integrates the torque vectoring and active suspension system (ASS) to enhance the vehicle’s longitudinal and vertical motion control performance. While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden. To facilitate the controller design and ease the load, a half-vehicle dynamics system is built and simplified to the linear-time-varying (LTV) model. Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety, energy-saving and comfort requirements. The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption. Finally, the effectiveness of the proposed controller is verified through the rapid-control-prototype (RCP) test. The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

Actuators for Improving Robotic Arm Safety While Maintaining Performance: A Comparison Study

Since robotic arms operating close to people are becoming increasingly common, there is a need to better understand how they can be made safe when unintended contact occurs, while still providing the required performance. Several actuators and methods for improving robot safety are studied and compared in this paper. A robotic arm moving its end effector horizontally and colliding with a person’s head is simulated. The use of a conventional electric actuator (CEA), series elastic actuator (SEA), pneumatic actuator (PA) and hybrid pneumatic electric actuator (HPEA) with model-based controllers are studied. The addition of a compliant covering to the arm and the use of collision detection and reaction strategies are also studied. The simulations include sensor noise and modeling error to improve their realism. A systematic method for tuning the controllers fairly is proposed. The motion control performance and safety of the robot are quantified using root mean square error (RMSE) between the desired and actual joint angle trajectories and maximum impact force (MIF), respectively. The results show that the RMSE values are similar when the CEA, SEA, and HPEA drive the robot’s first joint. Regarding safety, using the PA or HPEA with a compliant covering can reduce the MIF below the safety limit established by the International Organization for Standardization (ISO). To satisfy this ISO safety limit with the CEA and SEA, a collision detection and reaction strategy must be used in addition to the compliant covering. The influences of the compliant covering’s stiffness and the detection delay are also studied.

Fuzzy PID control of permanent magnet synchronous motor electric steering engine by improved beetle antennae search algorithm.

The accuracy of control in permanent magnet synchronous motor system significantly affects overall mechanical structure safety. To satisfy high-performance control for the position servo of the electric steering engine, this study selects a suitable vector control model for permanent magnet synchronous motor. Additionally, an enhanced beetle antennae search algorithm is designed and employed to optimize the fuzzy proportional-integral-derivative controller. The hybrid fuzzy proportional-integral-derivative controller is then implemented in the control model of the permanent magnet synchronous motor, resulting in the establishment of a novel control model for the electric steering engine driven by the permanent magnet synchronous motor. The test results showed that root-mean-square error of this control model was 0.03 mm and 0.02 mm respectively under the conditions of sinusoidal response, square wave response and step response, which was obviously shorter than all the selected control models. In addition, the standard deviation of the control model designed in this study accounted for less than 4% of root-mean-square error of electric steering engine position under the sinusoidal response condition, so the calculation stability was high. The research results show that the designed control model has a certain reference value for improving servo control performance of permanent magnet synchronous motor.

MPMC-frame: Multiplatform migration control framework for manipulator control

Existing robot control models suffer from poor generalization performance due to varied tasks between manipulators, configuration differences, and physical limits of motion. To address this problem, a multiplatform migration control framework (MPMC-frame) based on a constrained dynamics model is proposed in this paper. First, a model of the robotic manipulator dynamics with configuration adjustment (CA) is constructed based on a neural network to unify the physical joint data of different manipulators. Second, the model-based controller that can be integrated into the framework is designed, and the constraint on the upper bound on the error of uncertain parameters in the control law to guarantee the control robustness and accuracy of the controller for different manipulator platforms. Final, the generic potential function is designed based on multiplatform task requirements, and a task parameter table is constructed to improve the joint motion control performance of MPMC-frame. The feasibility of the method proposed in this paper are verified through simulations and experiments based on the ABB_irb120 and AUBO_i5 robotic manipulators.

Compliance motion control of the hydraulic dual-arm manipulator with adaptive mass estimation of unknown object

Compliance motion control of the hydraulic dual-arm manipulator with adaptive mass estimation of unknown object

Multiple mobile robots motion control based on screw theory for aircraft panel assembly

As a crucial component of large aircraft, the assembly efficiency of aircraft skins directly impacts production efficiency. To achieve efficient manufacturing of aircraft skins, this paper proposes a multiple mobile robot control algorithm based on screw theory. The robot arm is integrated into a rail or AGV to increase its motion space, creating a mobile robot assembly system. To address the redundant degrees of freedom problem caused by the mobile manipulator, this paper adopts the screw theory to describe the motion of multiple robots. Furthermore, to ensure the constraint of the motion between multiple robots, this paper proposes a multi-robot control method based on screw constraint. Rigid body constraints are assigned to the end of each mobile manipulator, and the motion is decomposed to the mobile platform and the robot arm. Finally, the cooperative motion control of multiple mobile manipulators is realized. The proposed algorithm is applied in the multi-mobile manipulator cooperative aircraft panel assembly task, achieving efficient assembly of aircraft panel and long truss.

Improved Modulated Model Predictive Control Technique for PMSM Drives Using the Vector Projection

Compared to the model predictive control (MPC) technique, the modulated MPC (M2PC) method applies multiple voltage vectors in order within one switching cycle, enabling a fixed switching frequency and better motor control performance. However, the M2PC technique suffers from a significant computational burden and imprecise allocation method of the vector action time, affecting the control performance. To address these two issues, this paper proposes an improved M2PC method that utilizes the information of projection of the reference vector on the selected voltage vectors for efficiently selecting the optimal active vectors and also accurately calculating their action time. Compared to the conventional M2PC, the proposed technique demonstrates both excellent dynamic performance with reduced execution time by 15.3% and superior steady‐state performance in terms of lower torque/speed ripple as well as fewer current harmonics. Those benefits have been proven by the results of a 2.5k rpm permanent magnet synchronous motor drive. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Collective Neural Dynamics for Sparse Motion Planning of Redundant Manipulators Without Hessian Matrix Inversion.

Redundant manipulators have been widely used in various industries whose applications not only improve production efficiency and reduce manual labor but also promote innovation in robotics and artificial intelligence. Kinematic control plays a fundamental and crucial role in robot control. Over the past few decades, numerous motion control schemes have been proposed and applied to trajectory tracking tasks. However, most of these schemes do not consider the introduction of sparsity into the motion control of redundant manipulators, resulting in excessive joint movements, which not only consume extra energy but also increase the risk of unexpected collisions in complex environments. To solve this problem, we transform the issue of increasing the sparsity into a nonconvex optimization problem. Furthermore, a collective neural dynamics for sparse motion planning (CNDSMP) scheme for motion planning of redundant manipulators is proposed. By incorporating sparsity into the control scheme, the excessive joint movements are minimized, leading to improved efficiency and reduced collision risks. Through simulations, comparisons, and physical experiments, the effectiveness and superiority of the proposed scheme are demonstrated.

Optimal Fully Actuated System Approach-Based Trajectory Tracking Control for Robot Manipulators.

In this article, a trajectory tracking control strategy is proposed for robot manipulators via a fully actuated system (FAS) approach, which has shown its simplicity and flexibility for most of the nonlinear controller design. However, the motion control for robot manipulators is more complicated since unknown dynamical model, external disturbances, friction forces, and various physical constraints are required to be considered. Therefore, the FAS approach cannot be straightforwardly applied. To address these challenges, the dynamic model of robot manipulators is established via model identification methods. Furthermore, based on the identified model, an FAS composite control strategy with simple structure is designed, which is achieved by integrating a high-order disturbance observer (HODO) in the inner loop, with an FAS trajectory tracking controller in the outer loop. Specifically, the HODO is utilized for handling the uncertain dynamics and external disturbances. Moreover, the controller gains are optimized using a gradient-based optimal parameter tuning method (OPTM). By imposing joint angle constraints, joint angular velocity constraints, and input torque limits into the formulation, the OPTM also ensures the satisfaction of these physical constraints. Numerical simulations and experiments are provided to validate the performance of the proposed controller.

Comparison of The Effect of a Period of TRX and Yoga Versus Traditional Exercises on Balance of Archers

Archers engage in various exercises to maintain postural stability and balance to achieve peak performance in archery, as balance and fine motor control are critical components of success in this sport. Therefore, the aim of this study was to compare the effect of a period of TRX and yoga versus traditional exercises on the balance of archers. This study is quasi-experimental with a pre-test and post-test design. The present research is applied in nature and was conducted in the field. The statistical population included all male archers in Tehran Province aged 20 to 40 years. From this population, 30 individuals were selected based on inclusion and exclusion criteria through convenience sampling and then randomly assigned to three groups: traditional exercises, yoga, and TRX. In the pre-test, the balance in shooting was measured. After completing the measurements, each group received their respective exercises, and at the end of the last training session, the post-test including the measured variables was repeated. To examine the research hypotheses, initially, the normality of the data was checked using the Shapiro-Wilk test, which revealed that the data were not normally distributed. Therefore, non-parametric statistical tests were used for data analysis. The results of the Wilcoxon test indicated that all three types of traditional exercises, yoga, and TRX led to a significant improvement in balance, hand-arm stability, and performance of the archers. In the intergroup comparison using the Kruskal-Wallis test, it was found that there were significant differences among the three groups in the research variables. Pairwise comparisons using the Mann-Whitney U test revealed that TRX, yoga, and traditional exercises, respectively, had the most significant effects. Based on the obtained results, it is suggested that the training programs used in the present research, with priority given to TRX, yoga, and traditional exercises, be recommended for improving the balance of male archers.

Online Control Barrier Function Construction for Safety-Critical Motion Control of Manipulators

Online Control Barrier Function Construction for Safety-Critical Motion Control of Manipulators

Constrained Motion Control of an Electro- Hydraulic Actuator Under Multiple Time-Varying Constraints

The motion control technology of electro-hydraulic actuators has great significance in industrial applications. Constraints significantly limit the motion control performance of actuator motion control, in addition to the inherent nonlinearities and uncertainties of the electro-hydraulic systems. The constraints comprise kinematic and dynamic constraints, and they can be time-varying owing to variations in the system. If the constraints are not fulfilled, the control accuracy may be adversely affected, for instance by actuator vibration, cavitation, or even instability. This study proposes a constrained motion control strategy for a variable-speed pump-driven hydraulic actuator. To robustly track a desired trajectory under constraints, the control strategy combines a nonlinear filter-type trajectory planning strategy and an adaptive robust motion controller. The trajectory planning strategy is designed by considering dynamic and kinematic constraints of the electro-hydraulic system, and it synthesizes a trajectory that reaches the given reference in minimum time while fulfilling these multiple constraints. Meanwhile, the adaptive robust motion controller tracks the synthesized trajectory with guaranteed control accuracy in the presence of inherent nonlinearities of the electro-hydraulic actuator. In addition, the assignments of the multiple constraints are adjusted in real time, which further optimize the constrained motion control performance. Comparative experiments with various given references were conducted to verify the advantages of the proposed constrained control strategy.

Modeling and Simulation of the Stepping Motor Operation Curve

To improve the open-loop control performance of stepper motors, research was conducted on their operating curves. The acceleration-velocity characteristic equations of three common operating curves were established and compared with the torque frequency characteristic curves of stepper motors. Based on this, an improved segmented correction fitting S-shaped (SCFS) curve design method based on a high torque utilization sine curve was proposed to solve the problem of rotor blockage and overshoot caused by uneven acceleration during the operation of stepper motors. In the simulation of the stepper motor load motion system, the SCFS curve was compared with common curves. The simulation results showed that the position tracking error was reduced by approximately 82% compared to the trapezoidal curve and approximately 70% compared to the exponential curve. Research has found that this method is suitable for the design of high-precision motor operating curves and has a high application value in the field of precision motion control.

High-precise Motion Control Hardware System and Key Timing Management Research

High-precise and multi-axes motion control system is required in the application of semiconductor equipment and high-performance industrial equipment. To achieve the tight performance requirements, this paper presents the control system architecture, communication, and timing management solution. We use multiple cores DSP and FPGA as the main control chips, use SRIO @5Gbps *4 as the DSP and FPGA communication protocol, and use Aurora 8B/10B @5Gpbs as the inter-board communication protocol. This architecture with its high sampling rate and low latency can improve the motion control performance and raise the system sampling bandwidth. Analysis and test results of system communication and timing management are included to demonstrate the efficacy of the proposed scheme.

Research on system of ultra-flat carrying robot based on improved PSO algorithm

Ultra-flat carrying robots (UCR) are used to carry soft targets for functional safety road tests of intelligent driving vehicles and should have superior control performance. For the sake of analyzing and upgrading the motion control performance of the ultra-flat carrying robot, this paper develops the mathematical model of its motion control system on the basis of the test data and the system identification method. Aiming at ameliorating the defects of the standard particle swarm optimization (PSO) algorithm, namely, low accuracy, being susceptible to being caught in a local optimum, and slow convergence when dealing with the parameter identification problems of complex systems, this paper proposes a refined PSO algorithm with inertia weight cosine adjustment and introduction of natural selection principle (IWCNS-PSO), and verifies the superiority of the algorithm by test functions. Based on the IWCNS-PSO algorithm, the identification of transfer functions in the motion control system of the ultra-flat carrying robot was completed. In comparison with the identification results of the standard PSO and linear decreasing inertia weight (LDIW)-PSO algorithms, it indicated that the IWCNS-PSO has the optimal performance, with the number of iterations it takes to reach convergence being only 95 and the fitness value being only 0.117. The interactive simulation model was constructed in MATLAB/Simulink, and the critical proportioning method and the IWCNS-PSO algorithm were employed respectively to complete the tuning and optimization of the Proportional-Integral (PI) controller parameters. The results of simulation indicated that the PI parameters optimized by the IWCNS-PSO algorithm reduce the adjustment time to 7.99 s and the overshoot to 13.41% of the system, and the system is significantly improved with regard to the control performance, which basically meets the performance requirements of speed, stability, and accuracy for the control system. In conclusion, the IWCNS-PSO algorithm presented in this paper represents an efficient system identification method, as well as a system optimization method.

A Modified Wei-Yao-Liu Conjugate Gradient Method for Unconstrained Optimization and Motion Control of Robotic Motion Manipulators

A Modified Wei-Yao-Liu Conjugate Gradient Method for Unconstrained Optimization and Motion Control of Robotic Motion Manipulators

Performance analysis of input shaped model reference adaptive control for a single-link flexible manipulator

Motion control for flexible link manipulators will have a great influence on their overall performance. Conventional control systems have the problem that they cannot compensate for the presence of uncertainty due to a variety of factors such as a change in the system itself-payload variations, degradation and modelling uncertainty. In addition, the underdamped structure of these systems entails motion-induced transient deflection and residual vibration. On the contrary, adaptive control, in particular Model Reference Adaptive Control (MRAC), has therefore been proposed to handle problems of this type dealing with other systems such as cranes, steering stability control for ground vehicles, airplanes and so on. This study presents a review and discussion on the MRAC and some individual issues of MRAC for these flexible link manipulators are addressed to specify: the state tracking error, the limitation of the adaptation values corresponding to the control gains and the control effort. Dealing with the last one, this work proves that shaping the command input to a Model Reference Adaptive Control (IS-MRAC) reduces the control effort necessary for the plant to follow the reference model and also mitigates the detrimental effects of flexibility. The IS-MRAC is implemented in a Single-Link Flexible Manipulator whose natural frequencies, experimentally and analytically estimated using the Transfer Matrix Method plus symbolic computation, vary significantly depending on payload mass and position. To this structured or parametric uncertainty, the proposed Lyapunov control law using the states associated with the low mode is designed for asymptotic stability and accommodates correctly. The state tracking, vibration suppression and control effort reduction performances of the proposed IS-MRAC combined controller are analysed via numerical simulations and experiments.