Motion Control Objective Research Articles

A Novel Robust Control Method for Motion Control of Uncertain Single-Link Flexible-Joint Manipulator

Single-link flexible-joint manipulator (FJM) is a kind of time-varying nonlinear system with underactuated characteristics. This paper takes the uncertain single-link FJM (USLFJM) as the object, and presents a novel robust control approach based on equivalent input disturbance (EID) method for motion control (i.e., position control and trajectory tracking control) of the USLFJM. Based on the uncertain dynamic model and desired target of this system, an error system is constructed. The error system is considered as a linear system with a nonlinear virtual disturbance. The motion control objective of the USLFJM can be realized by globally asymptotically stabilizing this linear system and compensating the influence of the nonlinear virtual disturbance. Then, an EID-based control system is designed to realize this control objective. Only position measurements are utilized in this paper, and the stability of the control system is proved. The simulation results are presented to illustrate the validity and the robustness of the proposed control method.

Periodic/Aperiodic Motion Control Using Periodic/Aperiodic Separation Filter

Motion control is a fundamental technique used in automated mechanical systems. Classically, velocity, force, and impedance are controlled in motion control systems, but simultaneous control is difficult. This article proposes periodic/aperiodic (P/A) motion control based on periodicity and aperiodicity of motion. The P/A motion control separately applies different control methods to P/A motions using P/A velocity and P/A force, which are extracted using a periodic/aperiodic separation filter (PASF) from velocity and force. Accordingly, six types of P/A motion controls are constructed in this article, which correspond to different combinations of the P/A velocity, P/A force, and P/A impedance controls. To construct the P/A motion control systems, acceleration control based on a disturbance observer is used. The ACS, which rejects disturbances, enables the P/A motion control design to ignore disturbances. The experiments were conducted to validate the six P/A motion controls, which simultaneously realized two P/A motion control objectives.

Design of motion trajectory and tracking control for underactuated cart‐pendulum system

SummaryA cart‐pendulum system is a nonlinear underactuated mechanical system with two degrees of freedom. This paper addresses the motion trajectory design and tracking control problems for this underactuated system. First, a friction‐like control law is designed for the system. Then, the characteristics of the closed‐loop control system are analyzed. Second, a new method of constructing an optimal trajectory for the system is developed. Then, a tracking control law is designed to quickly track the constructed trajectory. It guarantees that the motion control of the cart‐pendulum system is achieved along a reference trajectory. Finally, a numerical example is presented to demonstrate the effectiveness of the theoretical results. This study constructs an optimal trajectory for the cart‐pendulum system in its whole motion space and solves the motion control objective by tracking the constructed trajectory. It has many advantages compared with other motion control methods, eg, the optimal motion control objective of the system is achieved by a single control law; and the motion process and transient characteristics (eg, the settling time) of the control system can be accurately predicted.

Robot nonlinear control for Unmanned Aerial Vehicles’ multitasking

PurposeThis paper aims to present a unified motion control scheme for quadcopters which not only solves the point stabilization and trajectory tracking problems but also the path following problem.Design/methodology/approachThe control problem is solved based on the kinematic model of the unmanned aerial vehicles (UAV). Next, a dynamic compensation controller is considered through of a quadcopter-inner-loop system to independently track four velocity commands: forward, lateral, up/downward and heading rate. Stability and robustness of the whole control system are proved through the Lyapunov’s method. To evaluate the controller’s performance, a multi-user application which allows bilateral communication between a ground station and the Phantom 3 PRO quadrotor is developed.FindingsThe performance of the proposed unified controller is shown through real experiments for the different motion control objectives: point stabilization, trajectory tracking and path following. The experiments confirm the capability of the unified controller to solve different motion problems by an adequate selection of the control references.Originality/valueThis work proposes the design of three types of motion controllers, which can be switched to comply a task in outdoor. Based on the software development kit provided by the company DJI, an application to get and send data to the UAV is developed. By means of this application, the three tasks are tested and the robustness of the controllers is proved.

State transformation-based dynamic visual servoing for an unmanned aerial vehicle

abstractIn this paper, we propose a visual servoing control for a quadrotor unmanned aerial vehicle (UAV) which is based on a state transformation technique. The UAV is equipped with a single downwards facing camera, and the motion control objective is the regulation of relative displacement and yaw to a stationary visual target located on the ground. The state transformation is defined by a system of partial differential equations (PDEs) which eliminate roll and pitch rate dependence in the transformed image feature kinematics. A method for computing the general solutions of these PDEs is given, and we show a particular solution reduces to an established virtual camera approach. We treat point and line cases and introduce image moment features defined in the virtual camera image plane. Robustness of the control design is improved by accounting for attitude measurement bias, and uncertainty in thrust gain, mass, and image feature depth. The asymptotic stability of the closed-loop is proven. The method is based on a simple proportional-integral-derivative (PID) structure which can be readily implemented on-board. Experimental results show improved performance relative to previous work.

Global Convergence of a Decentralized Adaptive Fuzzy Control for the Motion of Robot Manipulators: Application to the Mitsubishi PA10-7CE as a Case of Study

In general terms, robot control consists in making a robot execute a commanded task. One of the most important cases is the trajectory tracking or motion control. In this paper, a control algorithm that uses adaptive fuzzy systems to approximate local portions of the robot manipulator dynamics is proposed in order to solve the trajectory tracking problem. This scheme is characterized by not requiring any knowledge of the dynamic model and, in contrast to some fuzzy adaptive controllers previously developed, the one proposed here is in a decentralized configuration, wherein each joint is considered as a subsystem and is independently controlled only through its local variables. Furthermore, a study that guarantees the stability and the boundedness of the solutions of the closed-loop system via Lyapunov theory is presented, including a functional analysis which proves for the first time that a decentralized adaptive fuzzy controller satisfies the motion control objective. The theoretical results exposed here are verified via experimentation by applying the designed algorithm to the Mitsubishi PA10-7CE robot arm and the outcomes are reported.

Hierarchical Adaptive Path-Tracking Control for Autonomous Vehicles

This paper presents a hierarchical controller for an autonomous vehicle to track a reference path in the presence of uncertainties in both tire–road condition and external disturbance. The hierarchical control architecture consists of three layers: high, low, and intermediate levels. The upper-layer module deals with the vehicle motion control objective, which generates the desired longitudinal/lateral forces and yaw moment. The low-level module handles the braking control for each wheel based on the wheel slip dynamics. The intermediate-level controller generates the longitudinal slip reference for the low-level brake control module and the front-wheel steering angles. To cope with the unknown and nonuniform road condition parameters appearing in the actuator models, an adaptive law is designed for each wheel, and the convergence of the adaptive parameters is guaranteed under a certain persistency-of-excitation condition. The stability of the integrated control system is analyzed by utilizing a Lyapunov function approach. Simulation results are included to illustrate the proposed control scheme.

Stabilization of underactuated two-link gymnast robot by using trajectory tracking strategy

This paper concerns the stabilization of an underactuated two-link gymnast robot called acrobot. A trajectory tracking control strategy is presented. First, we carry out a homeomorphous coordinate transformation on the acrobot system that transforms it into a new simplified nonlinear system. And then, a desired motion trajectory is designed for the new system. Finally, we use an equivalent-input-disturbance (EID) method to design a controller that makes the new system asymptotically track the desired trajectory. This enables the acrobot to be swung up from the downward position and to be stabilized at the upright position. The proposed strategy changes the stabilization of the nonlinear acrobot system into that of a linear time-invariant error dynamic system with an artificial disturbance. And it uses a single controller to accomplish the motion control objective of the acrobot. These makes the strategy simple and efficient. Simulation results demonstrate its validity and its superiority over others.

Dynamic IBVS of a rotary wing UAV using line features

SUMMARYIn this paper we propose a dynamic image-based visual servoing (IBVS) control for a rotary wing unmanned aerial vehicle (UAV) which directly accounts for the vehicle's underactuated dynamic model. The motion control objective is to follow parallel lines and is motivated by power line inspection tasks where the UAV's relative position and orientation to the lines are controlled. The design is based on a virtual camera whose motion follows the onboard physical camera but which is constrained to point downwards independent of the vehicle's roll and pitch angles. A set of image features is proposed for the lines projected into the virtual camera frame. These features are chosen to simplify the interaction matrix which in turn leads to a simpler IBVS control design which is globally asymptotically stable. The proposed scheme is adaptive and therefore does not require depth estimation. Simulation results are presented to illustrate the performance of the proposed control and its robustness to calibration parameter error.

A generalized global adaptive tracking control scheme for robot manipulators with bounded inputs

SummaryIn this work, a generalized adaptive scheme for the global motion control of robot manipulators with constrained inputs is proposed. It gives rise to various families of bounded adaptive controllers defined through a general class of saturation functions. Compared with adaptive tracking control algorithms previously developed in a bounded input context, the proposed adaptive approach guarantees the motion control objective for any initial condition, avoiding discontinuities throughout the scheme, preventing the inputs to reach their natural saturation bounds, and permitting innovation on the saturating structure through its generalized form, giving a wide range of possibilities for performance improvement. Experimental results corroborate the efficiency of the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.

Control allocation—A survey

The control algorithm hierarchy of motion control for over-actuated mechanical systems with a redundant set of effectors and actuators commonly includes three levels. First, a high-level motion control algorithm commands a vector of virtual control efforts (i.e. forces and moments) in order to meet the overall motion control objectives. Second, a control allocation algorithm coordinates the different effectors such that they together produce the desired virtual control efforts, if possible. Third, low-level control algorithms may be used to control each individual effector via its actuators. Control allocation offers the advantage of a modular design where the high-level motion control algorithm can be designed without detailed knowledge about the effectors and actuators. Important issues such as input saturation and rate constraints, actuator and effector fault tolerance, and meeting secondary objectives such as power efficiency and tear-and-wear minimization are handled within the control allocation algorithm. The objective of the present paper is to survey control allocation algorithms, motivated by the rapidly growing range of applications that have expanded from the aerospace and maritime industries, where control allocation has its roots, to automotive, mechatronics, and other industries. The survey classifies the different algorithms according to two main classes based on the use of linear or nonlinear models, respectively. The presence of physical constraints (e.g input saturation and rate constraints), operational constraints and secondary objectives makes optimization-based design a powerful approach. The simplest formulations allow explicit solutions to be computed using numerical linear algebra in combination with some logic and engineering solutions, while the more challenging formulations with nonlinear models or complex constraints and objectives call for iterative numerical optimization procedures. Experiences using the different methods in aerospace, maritime, automotive and other application areas are discussed. The paper ends with some perspectives on new applications and theoretical challenges.

Tire–road friction coefficient and tire cornering stiffness estimation based on longitudinal tire force difference generation

A sequential tire cornering stiffness coefficient and tire–road friction coefficient (TRFC) estimation method is proposed for some advanced vehicle architectures, such as the four-wheel independently-actuated (FWIA) electric vehicles, where longitudinal tire force difference between the left and right sides of the vehicle can be easily generated. Such a tire force difference can affect the vehicle yaw motion, and can be utilized to estimate the tire cornering stiffness coefficient and TRFC. The proposed tire cornering stiffness coefficient and TRFC identification method has the potential of estimating these parameters without affecting the vehicle desired motion control and trajectory tracking objectives. Simulation and experimental results with a FWIA electric vehicle show the effectiveness of the proposed estimation method.

Global trajectory tracking through output feedback for robot manipulators with bounded inputs

In this work, a globally stabilizing output feedback scheme for the trajectory tracking of robot manipulators with bounded inputs is proposed. It achieves the motion control objective avoiding input saturation and excluding velocity measurements. Moreover, it is not defined using a specific sigmoidal function, but any one on a set of saturation functions. Consequently, the proposed scheme actually constitutes a family of globally stabilizing output feedback bounded controllers. Furthermore, the control gains are not tied to satisfy any saturation-avoidance inequality and may consequently take any positive value, which may be considered beneficial for performance adjustment/improvement purposes. Further, a class of desired trajectories that may be globally tracked avoiding input saturation and excluding velocity measurements is completely characterized. Global asymptotic stabilization of the closed-loop system solutions towards the pre-specified desired trajectory is proved through a strict Lyapunov function. The efficiency of the proposed scheme is corroborated through experimental results. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

Stabilization of Automotive Vehicles Using Active Steering and Adaptive Brake Control Allocation

In this work a dynamic control allocation approach is presented for an automotive vehicle yaw stabilization scheme. The stabilization strategy consists of a high level module that deals with the vehicle motion control objective (yaw rate reference generation and tracking), a low level module that handles the braking control for each wheel (longitudinal slip control and maximal tire-road friction parameter estimation), and an intermediate level dynamic control allocation module that generates the longitudinal slip reference for the low level brake control module and commands front wheel steering angle corrections. The control allocation design is such that the actual torque about the yaw axis tends to the desired torque calculated form the high level module, with desirable distribution of control forces satisfying actuator constraints and minimal control effort objectives. Conditions for uniform asymptotic stability are given for the case when the control allocation includes adaptation of the tire-road maximal friction coefficients, and the scheme has been implemented in a realistic non linear multi body vehicle simulation environment. The simulation cases show that the yaw control allocation strategy stabilizes the vehicle in extreme maneuvers where the non linear vehicle yaw dynamics otherwise (without active braking or active steering) becomes unstable in the sense of over- or under steering. The control allocation implementation is efficient and suitable for low cost automotive electronic control units.

Nanoscale Path Planning and Motion Control with Maglev Positioners

This paper addresses nanoscale path planning and motion control, which is essential in nanomanufacturing applications such as microstereolithography (muSTL), dip-pen-nanolithography (DPN), and scanning applications for imaging and manipulation of nanoscale surface phenomena, with the magnetic levitation (maglev) technology. We identified the motion trajectories commonly used in industrial applications along with the challenges in optimal path planning to meet the nanoscale motion-control objectives and achieve precise positioning and maximum throughput simultaneously. The key control parameters in path planning are determined, and control design methodologies, including a well-damped lead-lag controller and an optimal linear quadratic regulator are proposed to satisfy the positioning requirements. The proposed methodologies were implemented individually and collectively. The experimental results are presented in this paper to illustrate their effectiveness in planning optimal trajectories. The damped lead-lag controller exhibited the command overshoot values of as small as 0.37%, and the multivariable LQ controller reduced the dynamic coupling among the axes by 97.1% as compared with the decoupled single-input-single-output (SISO) lead-lag controllers. The position resolution of 5 nm was achieved in x and y with the errors in command tracking as small as 4.5 nm. The maglev stage demonstrated excellent performances for the chosen nanomanufacturing applications in terms of position resolution and accuracy, and speed

Adaptive servo visual robot control

Adaptive controllers for robot positioning and tracking using direct visual feedback with camera-in-hand configuration are proposed in this paper. The controllers are designed to compensate for full robot dynamics. Adaptation is introduced to reduce the design sensitivity due to robot and payload dynamics uncertainties. It is proved that the control system achieves the motion control objective in the image coordinate system. Simulations are carried out to evaluate the controller performance. Also, discretization and measurement effects are considered in simulations.

A Self-Organising Fuzzy Logic Controller for a Coordinate Machine

For a 3D coordinate measurement system, the dynamic accuracy of the moving table will influence the measuring accuracy directly. If a classical PID controller were designed for this measuring table without an accurate mathematical model, the gain parameters may need to be regulated frequently by trial-and-error to obtain the precise motion control objective, good adaptability, and robustness. In this paper, a model-free fuzzy controller and a self-organising fuzzy controller (SOFC) were employed to eliminate the above controller design problems and improve the tracking control accuracy. The control performances of these intelligent control strategies were compared, based on the experimental results. The SOFC has the best tracking accuracy and its learning ability significantly reduces the trial-and-error design effort of a traditional fuzzy controller.