76 research outputs found
Modeling and Robust Control of Two Collaborative Robot Manipulators Handling a Flexibile Object
Robots are often used in industry to handle flexible objects, such as frames, beams, thin plates, rubber tubes, leather goods and composite materials. Moving long flexible objects in a desired path and also precise positioning and orienting the objects need a collaborative action between two robot arms. Most of the earlier studies have dealt with manipulation of rigid objects and only a few have focused on the collaborative manipulators handling flexible objects. Such studies on handling of flexible objects generally used finite element method or assumed mode method for deriving the dynamic model of the flexible objects.
These approximation methods require more number of sensors to feedback the vibration measurements or require an observer. Unlike in the earlier studies, this thesis concerns with development of a dynamic model of the flexible object in partial differential equation (PDE) form and design of a robust control strategy for collaborative manipulation of the flexible objects by two rigid robot arms. Two planar rigid manipulators each with three links and revolute joints handling a flexible object is considered during the model development. Kinematic and dynamic equations of the flexible object are derived without using any approximation techniques. The resulting dynamic equation of the flexible object together with the manipulator dynamic equations form the combined dynamic model of the system. The developed complete system of dynamic equations is described by the PDE’s having rigid as well as flexible parameters coupled together. Such a coupled system must be controlled without using any form
of approximation techniques and this is accomplished using the singular perturbation approach. By utilizing this technique, slow and fast subsystems are identified in two different time scales and controller is designed for each subsystem. The key issue in developing a control algorithm is that, it should be robust against uncertain parameters of the manipulators and the flexible object and it should also achieve the exponential convergence. Hence, for the slow subsystem, sliding mode control algorithm is developed and for the fast subsystem, a simple feedback control algorithm is designed. In general, usage of singular
perturbation technique necessitates exponential stability of the slow and fast subsystems, which is evaluated by satisfying the Tikhnov’s theorem. Hence, the exponential stability analysis for both the subsystems is performed. Simulation results are presented to validate
the composite control scheme. As a further consideration in the improvement of control law for the slow subsystem,
two modified control algorithms are suggested. The first one focused on the avoidance of velocity signal measurement which is useful to eliminate the need of velocity sensors and the second controller aims at avoiding the complex regressor in the control law. The capability of those controllers is illustrated through simulation studies. The extension of earlier analysis has been carried out by developing the complete system of dynamic equations in
joint space
Modeling and Robust Control of Two Collaborative Robot Manipulators Handling a Flexibile Object
Robots are often used in industry to handle flexible objects, such as frames, beams, thin plates, rubber tubes, leather goods and composite materials. Moving long flexible objects in a desired path and also precise positioning and orienting the objects need a collaborative action between two robot arms. Most of the earlier studies have dealt with manipulation of rigid objects and only a few have focused on the collaborative manipulators handling flexible objects. Such studies on handling of flexible objects generally used finite element method or assumed mode method for deriving the dynamic model of the flexible objects.
These approximation methods require more number of sensors to feedback the vibration measurements or require an observer. Unlike in the earlier studies, this thesis concerns with development of a dynamic model of the flexible object in partial differential equation (PDE) form and design of a robust control strategy for collaborative manipulation of the flexible objects by two rigid robot arms. Two planar rigid manipulators each with three links and revolute joints handling a flexible object is considered during the model development. Kinematic and dynamic equations of the flexible object are derived without using any approximation techniques. The resulting dynamic equation of the flexible object together with the manipulator dynamic equations form the combined dynamic model of the system. The developed complete system of dynamic equations is described by the PDE’s having rigid as well as flexible parameters coupled together. Such a coupled system must be controlled without using any form
of approximation techniques and this is accomplished using the singular perturbation approach. By utilizing this technique, slow and fast subsystems are identified in two different time scales and controller is designed for each subsystem. The key issue in developing a control algorithm is that, it should be robust against uncertain parameters of the manipulators and the flexible object and it should also achieve the exponential convergence. Hence, for the slow subsystem, sliding mode control algorithm is developed and for the fast subsystem, a simple feedback control algorithm is designed. In general, usage of singular
perturbation technique necessitates exponential stability of the slow and fast subsystems, which is evaluated by satisfying the Tikhnov’s theorem. Hence, the exponential stability analysis for both the subsystems is performed. Simulation results are presented to validate
the composite control scheme. As a further consideration in the improvement of control law for the slow subsystem,
two modified control algorithms are suggested. The first one focused on the avoidance of velocity signal measurement which is useful to eliminate the need of velocity sensors and the second controller aims at avoiding the complex regressor in the control law. The capability of those controllers is illustrated through simulation studies. The extension of earlier analysis has been carried out by developing the complete system of dynamic equations in
joint space
Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains
With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented.First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations
Modelling and Interactional Control of a Multi-fingered Robotic Hand for Grasping and Manipulation.
PhDIn this thesis, the synthesis of a grasping and manipulation controller of the Barrett hand, which
is an archetypal example of a multi-fingered robotic hand, is investigated in some detail. This
synthesis involves not only the dynamic modelling of the robotic hand but also the control
of the joint and workspace dynamics as well as the interaction of the hand with object it is
grasping and the environment it is operating in. Grasping and manipulation of an object by a
robotic hand is always challenging due to the uncertainties, associated with non-linearities of
the robot dynamics, unknown location and stiffness parameters of the objects which are not
structured in any sense and unknown contact mechanics during the interaction of the hand’s
fingers and the object. To address these challenges, the fundamental task is to establish the
mathematical model of the robot hand, model the body dynamics of the object and establish
the contact mechanics between the hand and the object.
A Lagrangian based mathematical model of the Barrett hand is developed for controller implementation.
A physical SimMechanics based model of the Barrett hand is also developed in
MATLAB/Simulink environment. A computed torque controller and an adaptive sliding model
controller are designed for the hand and their performance is assessed both in the joint space
and in the workspace. Stability analysis of the controllers are carried out before developing the
control laws. The higher order sliding model controllers are developed for the position control
assuming that the uncertainties are in place. Also, this controllers enhance the performance by
reducing chattering of the control torques applied to the robot hand.
A contact model is developed for the Barrett hand as its fingers grasp the object in the operating
environment. The contact forces during the simulation of the interaction of the fingers with
the object were monitored, for objects with different stiffness values. Position and force based
impedance controllers are developed to optimise the contact force. To deal with the unknown
stiffness of the environment, adaptation is implemented by identifying the impedance. An evolutionary
algorithm is also used to estimate the desired impedance parameters of the dynamics
of the coupled robot and compliant object.
A Newton-Euler based model is developed for the rigid object body. A grasp map and a hand
Jacobian are defined for the Barrett hand grasping an object. A fixed contact model with
friction is considered for the grasping and the manipulation control. The compliant dynamics of Barrett hand and object is developed and the control problem is defined in terms of the
contact force. An adaptive control framework is developed and implemented for different
grasps and manipulation trajectories of the Barrett hand. The adaptive controller is developed
in two stages: first, the unknown robot and object dynamics are estimated and second, the
contact force is computed from the estimated dynamics. The stability of the controllers is
ensured by applying Lyapunov’s direct method
Sliding Mode Control
The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area
Modelling and control of lightweight underwater vehicle-manipulator systems
This thesis studies the mathematical description and the low-level control structures for
underwater robotic systems performing motion and interaction tasks. The main focus is
on the study of lightweight underwater-vehicle manipulator systems. A description of
the dynamic and hydrodynamic modelling of the underwater vehicle-manipulator system
(UVMS) is presented and a study of the coupling effects between the vehicle and manipulator
is given. Through simulation results it is shown that the vehicle’s capabilities are
degraded by the motion of the manipulator, when it has a considerable mass with respect to
the vehicle. Understanding the interaction effects between the two subsystems is beneficial
in developing new control architectures that can improve the performance of the system.
A control strategy is proposed for reducing the coupling effects between the two subsystems
when motion tasks are required. The method is developed based on the mathematical
model of the UVMS and the estimated interaction effects. Simulation results show the validity
of the proposed control structure even in the presence of uncertainties in the dynamic
model. The problem of autonomous interaction with the underwater environment is further
addressed. The thesis proposes a parallel position/force control structure for lightweight underwater
vehicle-manipulator systems. Two different strategies for integrating this control
law on the vehicle-manipulator structure are proposed. The first strategy uses the parallel
control law for the manipulator while a different control law, the Proportional Integral
Limited control structure, is used for the vehicle. The second strategy treats the underwater
vehicle-manipulator system as a single system and the parallel position/force law is
used for the overall system. The low level parallel position/force control law is validated
through practical experiments using the HDT-MK3-M electric manipulator. The Proportional
Integral Limited control structure is tested using a 5 degrees-of-freedom underwater
vehicle in a wave-tank facility. Furthermore, an adaptive tuning method based on interaction
theory is proposed for adjusting the gains of the controller. The experimental results
show that the method is advantageous as it decreases the complexity of the manual tuning
otherwise required and reduces the energy consumption. The main objectives of this
thesis are to understand and accurately represent the behaviour of an underwater vehiclemanipulator
system, to evaluate this system when in contact with the environment and to
design informed low-level control structures based on the observations made through the
mathematical study of the system. The concepts presented in this thesis are not restricted
to only vehicle-manipulator systems but can be applied to different other multibody robotic
systems
Advanced Strategies for Robot Manipulators
Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored
MODELLING AND CONTROL OF A TWO-LINK RIGID-FLEXIBLE MANIPULATOR
The literature lacks data on the reliability of 3D models created by Autodesk Inventor software and imported to MATLAB Simulink software in comparison to mathematically generated models. In this contribution, a two-link rigid-flexible manipulator modelled in two different methods was demonstrated, one of which is using Lagrange equations and Finite Element Method to generate a mathematical model of the manipulator, and the other is creating a 3D model with the aid of Autodesk Inventor then import to MATLAB Simulink, both models were subsequently controlled by three types of controllers, conventional PID controller, LQR controller, and LQG controller. The research demonstrated the performance of the two models with response to the three types of controllers. Achieved results have proven that the Autodesk Inventor is considered a reliable tool for modelling mechanical systems. Results have also confirmed that modern controllers, i.e., LQR and LQG controllers perform much better than conventional PID controllers with regards to the manipulator movement. The implementation of Autodesk Inventor along with MATLAB Simulink indicates that the Autodesk Inventor can be considered as an instrumental tool for designers and engineers. The results enable future developments in the frontier area of robotics and mechanical systems, where sophisticated models could be generated by Autodesk Inventor instead of being modelled mathematically which will benefit engineers and designers by saving time and effort consumed in modelling using mathematical equations, and by reducing the potential errors associated with such modelling technique
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