Real-Time Iterative Compensation Framework for Precision Mechatronic Motion Control Systems

With regard to precision/ultra-precision motion systems,it is important to achieve excellent tracking performance for various trajectory tracking tasks even under uncertain external disturbances.In this paper,to overcome the limitation of robustness to trajectory variations and external disturbances in offline feedforward compensation strategies such as iterative learning control(ILC),a novel real-time iterative compensation(RIC)control framework is proposed for precision motion systems without changing the inner closed-loop controller.Specifically,the RIC method can be divided into two parts,i.e.,accurate model prediction and real-time iterative compensation.An accurate prediction model considering lumped disturbances is firstly established to predict tracking errors at future sampling times.In light of predicted errors,a feedforward compensation term is developed to modify the following reference trajectory by real-time iterative calculation.Both the prediction and compen-sation processes are finished in a real-time motion control sampling period.The stability and convergence of the entire control system after real-time iterative compensation is analyzed for different conditions.Various simulation results consistently demonstrate that the proposed RIC framework possesses satisfactory dynamic regulation capability,which contributes to high tracking accuracy comparable to ILC or even better and strong robustness.

Contouring error modeling and simulation of a four-axis motion control system

A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by the high level layer. The first advantage of this model is that the complex error model of a four-axis motion control system can be divided into several simple layers and each layer has different coupling strength to match the real control system. The second advantage lies in the fact that the controller in each layer can be designed specifically for a certain purpose. In this research, a three-layered cross coupling scheme in a four-axis motion control system is proposed to compensate the contouring error of the motion control system. Simulation results show that the maximum contouring error is reduced from 0.208 mm to 0.022 mm and the integration of absolute error is reduced from 0.108 mm to 0.015 mm, which are respectively better than 0.027 mm and 0.037 mm by the traditional method. And in the bottom layer the proposed method also has remarkable ability to achieve high contouring accuracy.

Research on Contour Error Based on CNC Multi-axis Motion Control System

The contour error was analyzed based on CNC multi-axis motion control, the contour error model was obtained focused on beeline and different radius of curvature and common contour of curve, for a CNC biaxial motion control system and the mechanism of producing contour error and the relationship between tracking error and contour error were presented. The theoretical and practical significance of modeling error and controlling error in motion control systems was carried out.

Safe Motion Planning and Control Framework for Automated Vehicles with Zonotopic TRMPC

Model mismatches can cause multi-dimensional uncertainties for the receding horizon control strategies of automated vehicles(AVs).The uncertainties may lead to potentially hazardous behaviors when the AV tracks ideal trajectories that are individually optimized by the AV's planning layer.To address this issue,this study proposes a safe motion planning and control(SMPAC)framework for AVs.For the control layer,a dynamic model including multi-dimensional uncertainties is established.A zonotopic tube-based robust model predictive control scheme is proposed to constrain the uncertain system in a bounded minimum robust positive invariant set.A flexible tube with varying cross-sections is constructed to reduce the controller conservatism.For the planning layer,a concept of safety sets,representing the geometric boundaries of the ego vehicle and obstacles under uncertainties,is proposed.The safety sets provide the basis for the subsequent evaluation and ranking of the generated trajectories.An efficient collision avoidance algorithm decides the desired trajectory through the intersection detection of the safety sets between the ego vehicle and obstacles.A numerical simulation and hardware-in-the-loop experiment validate the effectiveness and real-time performance of the SMPAC.The result of two driving scenarios indicates that the SMPAC can guarantee the safety of automated driving under multi-dimensional uncertainties.

Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

MPC-based Motion Planning and Control Enables Smarter and Safer Autonomous Marine Vehicles:Perspectives and a Tutorial Survey

Autonomous marine vehicles(AMVs)have received considerable attention in the past few decades,mainly because they play essential roles in broad marine applications such as environmental monitoring and resource exploration.Recent advances in the field of communication technologies,perception capability,computational power and advanced optimization algorithms have stimulated new interest in the development of AMVs.In order to deploy the constrained AMVs in the complex dynamic maritime environment,it is crucial to enhance the guidance and control capabilities through effective and practical planning,and control algorithms.Model predictive control(MPC)has been exceptionally successful in different fields due to its ability to systematically handle constraints while optimizing control performance.This paper aims to provide a review of recent progress in the context of motion planning and control for AMVs from the perceptive of MPC.Finally,future research trends and directions in this substantial research area of AMVs are highlighted.

Blown sand motion within the sand-control system in the southern section of the Taklimakan Desert Highway

Although scientists have performed many studies in the Taklimakan Desert, few of them have reported the blown sand motion along the southern edge of the Taklimakan Desert Highway, which differs significantly from the northern region in terms of aeolian sand geomorphology and formation environment. Based on the field ob- servation data of airflow and aeolian sand transport, continuous monitoring data of erosional and depositional processes between 14 April 2009 and 9 April 2011 and data of surface sand grains from the classical section along the southern edge of the Taklimakan Desert Highway, this paper reported the blown sand motion within the sand-control system of the highway. The main results are as follows： 1） The existing sand-control system is highly effective in preventing and controlling desertification. Wind velocities within the sand-control system were ap- proximately 33%-100% of those for the same height above the mobile sand surface. Aeolian sand fluxes were approximately 0-31.21% of those of the mobile sand surface. Sand grains inside the system, with a mean diameter of 2.89 q）, were finer than those （2.15 q）） outside the system. In addition, wind velocities basically followed a loga- rithmic law, but the airflow along the classical section was mainly determined by topography and vegetation. 2） There were obvious erosional and depositional phenomena above the surface within the sand-control system, and these phenomena have very consistent patterns for all observation points in the two observed years. The total thicknesses of erosion and deposition ranged from 0.30 to 14.60 cm, with a mean value of 3.67 cm. In contrast, the deposition thicknesses were 1.90-22.10 cm, with a mean value of 7.59 cm, and the erosion thicknesses were 3.51-15.10 cm, with a mean value of 8.75 cm. The results will aid our understanding of blown sand within the sand-control system and provide a strong foundation for optimizing the sand-control system.

A measurement system of magnetism parameters for motion control

Magnetism parameters vary with the position and the speed of electromagnetic actuator's motion parts.The measurement unit presented in the paper can be applied to get the position and the speed feedback information from the measurement of electromagnetism parameters,and can constitute the untouched feedback sensing unit in the closed-loop motion control,and it adapts to the diversified feedback control of electromagnetic actuator.The digital miniaturization meter,based on MSP430 single chip processor,which can do the multi-purpose measurement of Φ & B through the menu selection,can be used for the electromagnetic actuator's performance evaluation and improvement,and also the online quality control in production process.Both real-time data graph and data table can be displayed in the meter.The paper presents the system's structure,describes the principle,discusses the working modes,and shows the software flowchart and the measuring results.

Development of motion controller and its application in automatic TIG welding system

To develop a control system of cantilever arm for barrels welding, a motion controller has been developed to fit the welding procedure. The main research fields of the controller are: (1) finding effective measures to protect the controller against interferences; (2) decreasing welding current gradually in order to alleviate arc craters which are harmful to seam forming and welding quality; (3) planning the arm velocity to minimize the influence of the arm swing on arc length regulator; (4) adopting adaptive control algorithm with PD feedback and velocity feed-forward to reduce the influence of system inertia and velocity planning on the system transient performance.

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.

A FIELD METHOD FOR INTEGRATING THE EQUATIONS OF MOTION OF NONHOLONOMIC CONTROLLABLE SYSTEMS

This paper presents a field method for integrating the equations of motion of nonholonomic controllable systems. An example is given to illustrate the application of the method.

Decentralized PD Control for Non-uniform Motion of a Hamiltonian Hybrid System

In this paper, a decentralized proportional-derivative （PD） controller design for non-uniform motion of a Hamiltonian hybrid system is considered. A Hamiltonian hybrid system with the capability of producing a non-uniform motion is developed. The structural properties of the system are investigated by means of the theory of Hamiltonian systems. A relationship between the parameters of the system and the parameters of the proposed decentralized PD controller is shown to ensure local stability and tracking performance. Simulation results are included to show the obtained non-uniform motion.

CAN-based Synchronized Motion Control for Induction Motors

A control area network （CAN） based multi-motor synchronized motion control system with an advanced synchronized control strategy is proposed. The strategy is to incorporate the adjacent cross-coupling control strategy into the sliding mode control architecture. As illustrated by the four-induction-motor-based experimental results, the multi-motor synchronized motion control system, via the CAN bus, has been successfully implemented. With the employment of the advanced synchronized motion control strategy, the synchronization performance can be significantly improved.

LESO-based Position Synchronization Control for Networked Multi-Axis Servo Systems With Time-Varying Delay

The position synchronization control(PSC) problem is studied for networked multi-axis servo systems(NMASSs) with time-varying delay that is smaller than one sampling period. To improve the control performance of the system, time-varying delays, modeling uncertainties, and external disturbances are first modeled as a lumped disturbance. Then, a linear extended state observer(LESO) is devised to estimate the system state and the lumped disturbance, and a linear feedback controller with disturbance compensation is designed to perform individual-axis tracking control. After that, a cross-coupled control approach is used to further improve synchronization performance. The bounded-input-bounded-output(BIBO) stability of the closedloop control system is analyzed. Finally, both simulation and experiment are carried out to demonstrate the effectiveness of the proposed method.

基于Motion Control的开放式数控系统的研究

传统数控系统专业性强、可扩展性差和联网通讯能力弱 ,不能适应现代柔性制造和网络化加工的要求。本文采用MotionControl运动控制卡加工业PC机的硬件结构 ,并以COM (componentobjectmodel)技术的模块化编程方法构建了一个开放式的数控系统。最后给出了一个应用实例。

基于VersaMax Micro Motion Controller的物料搬运系统的设计

设计了基于VersaMax运动控制模块的物料搬运系统,着重对运动控制模块的参数进行了计算和配置,给出了系统的程序设计。实践表明,该系统定位准确,运行可靠,使用效果良好。

Precision motion control for electro-hydraulic axis systems under unknown time-variant parameters and disturbances

This article focuses on asymptotic precision motion control for electro-hydraulic axis systems under unknown time-variant parameters,mismatched and matched disturbances.Different from the traditional adaptive results that are applied to dispose of unknown constant parameters only,the unique feature is that an adaptive-gain nonlinear term is introduced into the control design to handle unknown time-variant parameters.Concurrently both mismatched and matched disturbances existing in electro-hydraulic axis systems can also be addressed in this way.With skillful integration of the backstepping technique and the adaptive control,a synthesized controller framework is successfully developed for electro-hydraulic axis systems,in which the coupled interaction between parameter estimation and disturbance estimation is avoided.Accordingly,this designed controller has the capacity of low-computation costs and simpler parameter tuning when compared to the other ones that integrate the adaptive control and observer/estimator-based technique to dividually handle parameter uncertainties and disturbances.Also,a nonlinear filter is designed to eliminate the“explosion of complexity”issue existing in the classical back-stepping technique.The stability analysis uncovers that all the closed-loop signals are bounded and the asymptotic tracking performance is also assured.Finally,contrastive experiment results validate the superiority of the developed method as well.

Dynamics model of underwater robot motion control in 6 degrees of freedom

In order to analyze underwater robot control system dynamics features, a system 6-DOF dynamics model was founded. Underwater robot linear and nonlinear hydrodynamics were analyzed by Taylor series, based on general motion equation. Special control system motion equation was deduced by cluster of inertial items and non-inertial items. For program convenience, motion equation matrix format was presented. Experimental principles of screw propellers, rudders and wings were discussed. Experimental data least-square curve fitting, interpolation and their corresponding traditional equation helped us to obtain the whole system dynamic response procedure. A series of simulation experiments show that the dynamics model is correct and reliable. The model can provide theory proof for analyzing underwater robot motion control system physics characters and provide a mathematic model for traditional control method.

Fuzzy logic for large mining bucket wheel reclaimer motion control—from an engineer's perspective

The bucket wheel reclaimer(BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials(i.e.iron ore and coal) in places such as ports,iron-steel plants,coal storage areas,and power stations from stockpiles.BWRs are very large in size,heavy in weight,expensive in price,and slow in motion.There are many challenges in attempting to automatically control their motion to accurately follow the required trajectories involving uncertain parameters from factors such as friction,turbulent wind,its own dynamics,and encoder limitations.As BWRs are always heavily engaged in production and cannot be spared very long for motion control studies and associated developments,a BWR model and simulation environment closely resembling real life conditions would be beneficial.The following research focused mainly on the implementation of fuzzy logic to a BWR motion control from an engineer's perspective.First,the modeling of a BWR including partially known parameters such as friction force and turbulence to the system was presented.This was then followed by the design of a fuzzy logic-based control built on a model-based control loop.The investigation provides engineers with an example of applying fuzzy logic in a model based approach to properly control the motion of a large BWR following defined trajectories,as well as to show possible ways of further improving the controller performance.The result indicates that fuzzy logic can be applied easily by engineers to overcome most motion control issues involving a large BWR.

A learning-based flexible autonomous motion control method for UAV in dynamic unknown environments

This paper presents a deep reinforcement learning(DRL)-based motion control method to provide unmanned aerial vehicles(UAVs)with additional flexibility while flying across dynamic unknown environments autonomously.This method is applicable in both military and civilian fields such as penetration and rescue.The autonomous motion control problem is addressed through motion planning,action interpretation,trajectory tracking,and vehicle movement within the DRL framework.Novel DRL algorithms are presented by combining two difference-amplifying approaches with traditional DRL methods and are used for solving the motion planning problem.An improved Lyapunov guidance vector field(LGVF)method is used to handle the trajectory-tracking problem and provide guidance control commands for the UAV.In contrast to conventional motion-control approaches,the proposed methods directly map the sensorbased detections and measurements into control signals for the inner loop of the UAV,i.e.,an end-to-end control.The training experiment results show that the novel DRL algorithms provide more than a 20%performance improvement over the state-ofthe-art DRL algorithms.The testing experiment results demonstrate that the controller based on the novel DRL and LGVF,which is only trained once in a static environment,enables the UAV to fly autonomously in various dynamic unknown environments.Thus,the proposed technique provides strong flexibility for the controller.