Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

A Back-stepping Based Trajectory Tracking Controller for a Non-chained Nonholonomic Spherical Robot

Spherical robot has good static and dynamic stability, which provides it with strong viability in hostile environment, but the lack of effective control methods has hindered its application and development. This article deals with the dynamic trajectory tracking problem of the spherical robot BHQ-2 designed for unmanned environment exploration. The dynamic model of the spherical robot is established with a simplified Boltzmann-Hamel equation, based on which a trajectory tracking controller is designed by using the back-stepping method. The convergence of the controller is proved with the Lyapunov stability theory. Numerical simulations show that with the controller the robot can globally and asymptotically track desired trajectories, both linear and circular.

Model-based trajectory tracking control for an electrohydraulic lifting system with valve compensation strategy

The natural frequency of the electrohydraulic system in mobile machinery is always very low,which brings difficulties to the controller design.To improve the tracking performance of the hydraulic system,mathematical modeling of the electrohydraulic lifting system and the rubber hose was accomplished according to an electrohydraulic lifting test rig built in the laboratory.Then,valve compensation strategy,including spool opening compensation (SOC) and dead zone compensation (DZC),was designed based on the flow-pressure characteristic of a closed-centered proportional valve.Comparative experiments on point-to-point trajectory tracking between a proportional controller with the proposed compensations and a traditional PI controller were conducted.Experiment results show that the maximal absolute values of the tracking error are reduced from 0.039 m to 0.019 m for the slow point-to-point motion trajectory and from 0.085 m to 0.054 m for the fast point-to-point motion trajectory with the proposed compensations.Moreover,tracking error of the proposed controller was analyzed and corresponding suggestions to reduce the tracking error were put forward.

Dynamic modelling and PFL-based trajectory tracking control for underactuated cable-driven truss-like manipulator

In recent years,an innovative underactuated robot was developed,named as underactuated cable-driven trusslike manipulator(UCTM),to be suitable in aerospace applications.However,there has been strong consensus that the stabilization of planar underactuated manipulators without gravity is a great challenge since the system includes a second order nonholonomic constraint and most classical control methods are not suitable for this kind of system.Furthermore,the complexity of the truss-like structure results in tremendous difficulty of computational complicacy and high nonlinearity during dynamic modelling in addition to controller design.It is paramount to solve these difficulties for UCTM's future applications.To solve the above difficulties,this paper presents a dynamic modelling method for UCTM and a trajectory tracking control method based on partial feedback linearization(PFL)that fulfills the control goal of moving UCTM from its original position to a desired position by tracking a given trajectory of the joint angles.To achieve this,a model equivalent method is proposed to make UCTM equivalent with a three-link manipulator in the sense of dynamic behavior.Then the Lagrangian equation combined with complex vector method is proposed in the dynamic modelling process of UCTM,which simplifies the derivation procedure.Based on the established dynamic model,a coordinate transformation method is proposed to transform the control force matrix into the conventional form of an underactuated system,so that the control force can be separated from the unactuated term.The PFL method in combination with the LQR control method is then proposed to realize the targets that the joint angles can track given desired trajectory.Simulation experiments are conducted to verify the correctness and effectiveness of the proposed methods.

Trajectory tracking control of characteristic model for nonplanar hex-rotor UAV

The nonplanar hex-rotor unmanned aerial vehicle(UAV)has much higher driving property,greater payload capacity and damage tolerance than quad-rotor UAV.It is difficult to design a highperformance controller of easy engineering implementation for strongly coupled nonlinear hex-rotorUAV system.In response to this practical problem,an adaptive trajectory tracking control based oncharacteristic model for nonplanar hex-rotor is studied.Firstly,the dynamic model for the hex-rotorUAV is devised.Secondly,according to dynamic characteristics,environmental characteristics andcontrol performance requirements,the characteristic model of the hex-rotor UAV is constructed.Then,based on the characteristic model,a golden section adaptive controller is designed to realizetrajectory tracking.Furthermore,the stability analysis of the closed loop hex-rotor system is given.Finally,the validity of the proposed trajectory tracking control method adopted in the nonplanar hex-rotor UAV is demonstrated via numerical simulations and hex-rotor prototype experiments.

Trajectory tracking control based on linear active disturbance rejection controller for 6-DOF robot manipulator

The trajectory tracking control for a 6-DOF robot manipulator with multiple inputs and outputs,non-linearity and strong coupling is studied.Firstly,a dynamical model for the 6-DOF robot manipulator is designed.From the view point of practical engineering,considering the model uncertainties and external disturbances,the robot manipulator is divided into 6 independent joint subsystems,and a linear active disturbance rejection controller(LADRC)is developed to track trajectory for each subsystem respectively.LADRC has few parameters that are easy to be adjusted in engineering.Linear expansion state observer(LESO)as the uncertainty observer is able to estimate the general uncertainties effectively.Eventually,the validity and robustness of the proposed method adopted in 6-DOF robot manipulator are demonstrated via numerical simulations and 6-DOF robot manipulator experiments,which is of practical value in engineering application.

Trajectory Tracking Control for Under-Actuated Hovercraft Using Differential Flatness and Reinforcement Learning-Based Active Disturbance Rejection Control

This paper proposes a scheme of trajectory tracking control for the hovercraft.Since the model of the hovercraft is under-actuated,nonlinear,and strongly coupled,it is a great challenge for the controller design.To solve this problem,the control scheme is divided into two parts.Firstly,we employ differential flatness method to find a set of flat outputs and consider part of the nonlinear terms as uncertainties.Consequently,we convert the under-actuated system into a full-actuated one.Secondly,a reinforcement learning-based active disturbance rejection controller(RL-ADRC)is designed.In this method,an extended state observer(ESO)is designed to estimate the uncertainties of the system,and an actorcritic-based reinforcement learning(RL)algorithm is used to approximate the optimal control strategy.Based on the output of the ESO,the RL-ADRC compensates for the total uncertainties in real-time,and simultaneously,generates the optimal control strategy by RL algorithm.Simulation results show that,compared with the traditional ADRC method,RL-ADRC does not need to manually tune the controller parameters,and the control strategy is more robust.

An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot

We present an iterative linear quadratic regulator(ILQR) method for trajectory tracking control of a wheeled mobile robot system.The proposed scheme involves a kinematic model linearization technique,a global trajectory generation algorithm,and trajectory tracking controller design.A lattice planner,which searches over a 3D(x,y,θ) configuration space,is adopted to generate the global trajectory.The ILQR method is used to design a local trajectory tracking controller.The effectiveness of the proposed method is demonstrated in simulation and experiment with a significantly asymmetric differential drive robot.The performance of the local controller is analyzed and compared with that of the existing linear quadratic regulator(LQR) method.According to the experiments,the new controller improves the control sequences(v,ω) iteratively and produces slightly better results.Specifically,two trajectories,'S' and '8' courses,are followed with sufficient accuracy using the proposed controller.

Three-Dimensional Trajectory Tracking Control of Underactuated Autonomous Underwater Vehicles with Input Saturation

This paper addresses a three-dimensional(3D)trajectory tracking problem of underactuated autonomous underwater vehicles(AUVs)subjected to input saturation and external disturbances.The proposed controller can achieve practical convergence of tracking errors for general reference trajectories,including persistently exciting(PE)time varying trajectories and fixed points.At first,a modified error state formulation is introduced to tackle the situation that desired velocities do not satisfy PE condition.Then,on the basis of the backstepping technique and a Nussbaum-type even function,a saturated controller is designed so that the tracking errors can converge to a bounded neighborhood of the origin.The stability analysis based on Lyapunov theory shows that the tracking errors are globally ultimately uniformly bounded.Finally,some simulation results illustrate the effectiveness and robustness of the proposed control strategy.

Trajectory tracking control of robotic transcranial magnetic stimulation

Purpose–Transcranial magnetic stimulation(TMS)is a non-invasive brain stimulation technique.Based on the unique functions of TMS,it has been widely used in clinical,scientific research and other fields.Nowadays,the robot-assisted automatic TMS has become the trend.In order to simplify the operation procedures of robotic TMS and reduce the costs,the purpose of this paper is to apply the marker-based augmented-reality technology to robotic TMS system.Design/methodology/approach–By using the marker of ARToolKitPlus library and monocular camera,the patient’s head is positioned in real time.Furthermore,the force control is applied to keep contact between the coil and subject’s head.Findings–The authors fuse with visual positioning which is based on augmented-reality and force-control technologies to track the movements of the patient’s head,bring the coil closer to the stimulation site and increase treatment effects.Experimental results indicate that the trajectory tracking control of robotic TMS system designed in this paper is practical and flexible.Originality/value–This paper provides a trajectory tracking control method for the robotic TMS.The marker-based augmented-reality technology is implemented which simplifies the operation procedures of robotic TMS as well as reduce the costs.During the treatment process,the patients would wear an AR glasses,which can help patients relax through virtual scenes and reduce the uncomfortableness produce by treatment.

Trajectory tracking anti-disturbance control for unmanned aerial helicopter based on disturbance characterization index

This work studies the trajectory tracking control for unmanned aerial helicopter(UAH)system under both matched disturbance and mismatched ones.Initially,to tackle the strong coupling,an input-output feedback linearization method is utilized to simplify the nonlinear UAH system.Secondly,a set of finite-time disturbance observers(FTDOs)are proposed to estimate mismatched disturbances with their successive derivatives,which are utilized to design the feedforward controller via backstepping.Thirdly,as for matched disturbance,by defining the disturbance characterization index(DCI)to determine whether the disturbance is harmful or not for the UAH system,a feedback controller is proposed and a sufficient condition is established to ensure the convergence of the tracking error.Finally,some numerical simulations and comparisons illustrate the validity and advantages of our control scheme.

Hierarchical Control Strategy of Trajectory Tracking for Intelligent Vehicle

In order to track the desired trajectory for intelligent vehicle, a new hierarchical control strategy is presented. The control structure consists of two layers. The high-level controller adopts the model predictive control (MPC) to calculate the steering angle tracking the desired yaw angle and the lateral position. The low-level controller is designed as a gain-scheduling controller based on linear matrix inequalities. The desired longitudinal velocity and the yaw rate are tracked by the adjustment of each wheel torque. The simulation results via the high-fidelity vehicle dynamics simulation software veDYNA show that the proposed strategy has a good tracking performance and can guarantee the yaw stability of intelligent vehicle. © 2017, Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg.

Fuzzy adaptive robust control for space robot considering the effect of the gravity

Space robot is assembled and tested in gravity environment, and completes on-orbit service（OOS） in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control（FARC） strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative（PD） controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.

Task Space Division and Trajectory Planning for a Flexible Macro-Micro Manipulator System

This paper deals with a flexible macro-micro manipulator system, which includes a long flexible manipulator and a relatively short rigid manipulator attached to the tip of the macro manipulator. A flexible macro manipulator possesses the advantages of wide operating range, high speed, and low energy consumption, but the disadvantage of a low tracking precision. The macro-micro manipulator system improves tracking performance by compensating for the endpoint tracking error while maintaining the advantages of the flexible macro manipulator. A trajectory planning scheme was built utilizing the task space division method. The division point is chosen to optimize the error compensation and energy consumption for the whole system. Then movements of the macro-micro manipulator can be determined using separate inverse kinematic models. Simulation results for a planar 4-DOF macro-micro manipulator system are presented to show the effectiveness of the control system.

Dynamic Movement Primitives Based Robot Skills Learning

In this article,a robot skills learning framework is developed,which considers both motion modeling and execution.In order to enable the robot to learn skills from demonstrations,a learning method called dynamic movement primitives(DMPs)is introduced to model motion.A staged teaching strategy is integrated into DMPs frameworks to enhance the generality such that the complicated tasks can be also performed for multi-joint manipulators.The DMP connection method is used to make an accurate and smooth transition in position and velocity space to connect complex motion sequences.In addition,motions are categorized into different goals and durations.It is worth mentioning that an adaptive neural networks(NNs)control method is proposed to achieve highly accurate trajectory tracking and to ensure the performance of action execution,which is beneficial to the improvement of reliability of the skills learning system.The experiment test on the Baxter robot verifies the effectiveness of the proposed method.