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.

Modeling and Adaptive Neural Network Control for a Soft Robotic Arm With Prescribed Motion Constraints

This paper presents a dynamic model and performance constraint control of a line-driven soft robotic arm.The dynamics model of the soft robotic arm is established by combining the screw theory and the Cosserat theory.The unmodeled dynamics of the system are considered,and an adaptive neural network controller is designed using the backstepping method and radial basis function neural network.The stability of the closed-loop system and the boundedness of the tracking error are verified using Lyapunov theory.The simulation results show that our approach is a good solution to the motion constraint problem of the line-driven soft robotic arm.

Open-plus-closed-loop control for chaotic motion of 3D rigid pendulum

An open-plus-closed-loop(OPCL) control problem for the chaotic motion of a 3D rigid pendulum subjected to a constant gravitational force is studied. The 3D rigid pendulum is assumed to be consist of a rigid body supported by a fixed and frictionless pivot with three rotational degrees. In order to avoid the singular phenomenon of Euler's angular velocity equation, the quaternion kinematic equation is used to describe the motion of the 3D rigid pendulum. An OPCL controller for chaotic motion of a 3D rigid pendulum at equilibrium position is designed. This OPCL controller contains two parts: the open-loop part to construct an ideal trajectory and the closed-loop part to stabilize the 3D rigid pendulum. Simulation results show that the controller is effective and efficient.

Research trends in methods for controlling macro-micro motion platforms

With ongoing economic,scientific,and technological developments,the electronic devices used in daily lives are developing toward precision and miniaturization,and so the demand for high-precision manufacturing machinery is expanding.The most important piece of equipment in modern high-precision manufacturing is the macro-micro motion platform(M3P),which offers high speed,precision,and efficiency and has macro-micro motion coupling characteristics due to its mechanical design and composition of its driving components.Therefore,the design of the control system is crucial for the overall precision of the platform;conventional proportional–integral–derivative control cannot meet the system requirements,and so M3Ps are the subject of a growing range of modern control strategies.This paper begins by describing the development history of M3Ps,followed by their platform structure and motion control system components,and then in-depth assessments of the macro,micro,and macro-micro control systems.In addition to examining the advantages and disadvantages of current macro-micro motion control,recent technological breakthroughs are noted.Finally,based on existing problems,future directions for M3P control systems are given,and the present conclusions offer guidelines for future work on M3Ps.

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。

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 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.

Development of FPGA Based NURBS Interpolator and Motion Controller with Multiprocessor Technique

The high-speed computational performance is gained at the cost of huge hardware resource,which restricts the application of high-accuracy algorithms because of the limited hardware cost in practical use.To solve the problem,a novel method for designing the field programmable gate array(FPGA)-based non-uniform rational B-spline(NURBS) interpolator and motion controller,which adopts the embedded multiprocessor technique,is proposed in this study.The hardware and software design for the multiprocessor,one of which is for NURBS interpolation and the other for position servo control,is presented.Performance analysis and experiments on an X-Y table are carried out,hardware cost as well as consuming time for interpolation and motion control is compared with the existing methods.The experimental and comparing results indicate that,compared with the existing methods,the proposed method can reduce the hardware cost by 97.5% using higher-accuracy interpolation algorithm within the period of 0.5 ms.A method which ensures the real-time performance and interpolation accuracy,and reduces the hardware cost significantly is proposed,and it's practical in the use of industrial application.

Post-Impact Motion Planning and Tracking Control for Autonomous Vehicles

There is an increasing awareness of the need to reduce traffic accidents and fatality due to vehicle collision.Post-impact hazards can be more serious as the driver may fail to maintain effective control after collisions.To avoid subsequent crash events and to stabilize the vehicle,this paper proposes a post-impact motion planning and stability control method for autonomous vehicles.An enabling motion planning method is proposed for post-impact situations by combining the polynomial curve and artificial potential field while considering obstacle avoidance.A hierarchical controller that consists of an upper and a lower controller is then developed to track the planned motion.In the upper controller,a time-varying linear quadratic regulator is presented to calculate the desired generalized forces.In the lower controller,a nonlinear-optimization-based torque allocation algorithm is proposed to optimally coordinate the actuators to realize the desired generalized forces.The proposed scheme is verified under comprehensive driving scenarios through hardware-in-loop tests.

A Mode-Switching Motion Control System for Reactive Interaction and Surface Following Using Industrial Robots

This work proposes a sensor-based control system for fully automated object detection and exploration(surface following) with a redundant industrial robot. The control system utilizes both offline and online trajectory planning for reactive interaction with objects of different shapes and color using RGBD vision and proximity/contact sensors feedback where no prior knowledge of the objects is available. The RGB-D sensor is used to collect raw 3D information of the environment. The data is then processed to segment an object of interest in the scene. In order to completely explore the object, a coverage path planning technique is proposed using a dynamic 3D occupancy grid method to generate a primary(offline) trajectory. However, RGB-D sensors are very sensitive to lighting and provide only limited accuracy on the depth measurements. Therefore, the coverage path planning is then further assisted by a real-time adaptive path planning using a fuzzy self-tuning proportional integral derivative(PID)controller. The latter allows the robot to dynamically update the 3D model by a specially designed instrumented compliant wrist and adapt to the surfaces it approaches or touches. A modeswitching scheme is also proposed to efficiently integrate and smoothly switch between the interaction modes under certain conditions. Experimental results using a CRS-F3 manipulator equipped with a custom-built compliant wrist demonstrate the feasibility and performance of the proposed method.

Efficient Rate Control for Motion JPEG2000 under Constraint Memory

Fine scalability can provide not only precise rate control for constant bitrate (CBR) traffic, but also accurate quality control for variable bitrate (VBR) traffic. Motion JPEG2000 is a codec that can provide fine scalability with bitstreams. An efficient rate control approach utilizing a single buffer and two kinds of threshold for Motion JPEG2000 under resource constraint was proposed, which can offer good result in the constant quality video.

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.

Application of Single Neuron Adaptive PID Regulators with Auto-tuning Gain in Industrial Parameter(Pressure)Closed-loop Process Control Systems

1IntroductionTheworkcontroloffluidmachinessuchasfans,waterPUInpsandair-Pressersetc.frequentlyemploypressureclosed-loopprocesscontrolSystems[11.IndustrialproducingandPracticingshowthatthesystemshaveaseriousPressurefluctUationPhenomenonduringworkingPro...

Platform motion minimization using model predictive control of a floating offshore wind turbine

Wind turbines are installed offshore with the assistance of a floating platform to help meet the world’s increasing energy needs.However,the incident wind and extra incident wave disturbances have an impact on the performance and operation of the floating offshore wind turbine(FOWT)in comparison to bottom-fixed wind turbines.In this paper,model predictive control(MPC)is utilized to overcome the limitation caused by platform motion.Due to the ease of control synthesis,the MPC is developed using a simplified model instead of high fidelity simulation model.The performance of the controller is verified in the presence of realistic wind and wave disturbances.The study demonstrates the effectiveness of MPC in reducing platform motions and rotor/generator speed regulation of FOWTs.

Optimal Actuator Placement and Active Vibration Control of Over-Actuated Motion System in the Wafer Stage

The null space of the 6-DOF gain decoupling matrix of actuators and a modified velocity feedback controller are adopted to suppress the vibration of the wafer stage during exposure.To deal with varying flexibilities at different performance locations,the vibration controller is designed to be a time-variant linear quadratic regulator,using the conventional gain scheduling method,which could provide good vibration control for each field under exposure.This control method can guarantee the stability of the closed-loop system and will not deteriorate the rigid modes control of the wafer stage.To minimize the control spillover caused by the higher uncontrolled modes,actuator placement is optimized to minimize their controllability grammians in modal coordinates.An unconstrained rectangular plate is used to represent the fine stage of the wafer stage.Effectiveness of the proposed method is verified on the plate through a closed-loop simulation.

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.

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.

Precise robust motion control of cell puncture mechanism driven by piezoelectric actuators with fractional-order nonsingular terminal slidingmode control

A novel robust controller is proposed in this study to realize the precise motion control of a cell puncture mechanism(CPM)driven by piezoelectric ceramics(PEAs).The entire dynamic model of CPM is constructed based on the Bouc–Wen model,and the nonlinear part of the dynamic model is optimized locally to facilitate the construction of a robust controller.A model-based,nonlinear robust controller is constructed using time-delay estimation(TDE)and fractional-order nonsingular terminal sliding mode(FONTSM).The proposed controller does not require prior knowledge of unknown disturbances due to its real-time online estimation and compensation of unknown terms by using the TDE technology.The controller also has finite-time convergence and high-precision trajectory tracking capabilities due to FONTSM manifold and fast terminal sliding mode-type reaching law.The stability of the closed-loop system is proved by Lyapunov stability theory.Computer simulation and hardware-in-loop simulation experiments of CPM verify that the proposed controller outperforms traditional terminal sliding mode controllers,such as the integer-order or model-free controller.The proposed controller can also continuously output without chattering and has high control accuracy.Zebrafish embryo is used as a verification target to complete the cell puncture experiment.From the engineering application perspective,the proposed control strategy can be effectively applied in a PEA-driven CPM.