A discrete decentralized variable structure robotic controller

A decentralized trajectory controller for robotic manipulators is designed and tested using a multiprocessor architecture and a PUMA 560 robot arm. The controller is made up of a nominal model-based component and a correction component based on a variable structure suction control approach. The second control component is designed using bounds on the difference between the used and actual values of the model parameters. Since the continuous manipulator system is digitally controlled along a trajectory, a discretized equivalent model of the manipulator is used to derive the controller. The motivation for decentralized control is that the derived algorithms can be executed in parallel using a distributed, relatively inexpensive, architecture where each joint is assigned a microprocessor. Nonlinear interaction and coupling between joints is treated as a disturbance torque that is estimated and compensated for

Variable structure control of robot manipulators (the example of the SPRINTA)

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 12/01/2000.The subject of this thesis is the design and practical application of a model-based controller with variable structure control (VSC). Robot manipulators are highly non-linear systems, however they form a specific class in the non-linear group. Exact mathematical descriptions of the robot dynamics can be achieved and further, robot manipulators have specific useful properties that can be used for the design of advanced controllers. The inclusion of the inverse dynamic description of the robot manipulator as a feedforward term of the controller (model-based controller) is used to transform two non-linear systems i.e. the controller and the robot, into one linear system. The limitation of this technique arises from the accuracy of the inverse dynamic model. The linearisation only takes place if the model is known exactly. To deal with the uncertainties that arise in the model, a control methodology based on variable structure control is proposed. The design of the controller is based on a Lyapunov approach and engineering considerations of the robot. A candidate Lyapunov function of a pseudo-energy form is selected to start the controller design. The general form of the controller is selected to satisfy the negative definiteness of the Lyapunov function. The initial uncertainties between the actual robot dynamics and the model used in the controller are dealt with using a classical VSC regulator. The deficiencies of this approach are evident however because of the chattering phenomenum. The model uncertainties are examined from an engineering point of view and adjustable bounds are then devised for the VSC regulator, and simulations confirm a reduction in the chattering. Implementation on the SPRINTA robot reveals further limitations in the proposed methodology and the bound adjustment is enhanced to take into account the position of the robot and the tracking errors. Two controllers based on the same principle are then obtained and their performances are compared to a PID controller, for three types of trajectory. Tests reveal the superiority of the devised control methodology over the classic PID controller. The devised controller demonstrates that the inclusion of the robot dynamics and properties in the controller design with adequate engineering considerations lead to improved robot responses.EPSRC; Department of Electronic and Computer Engineering of Brunel Universit

Folding Assembly by Means of Dual-Arm Robotic Manipulation

In this paper, we consider folding assembly as an assembly primitive suitable for dual-arm robotic assembly, that can be integrated in a higher level assembly strategy. The system composed by two pieces in contact is modelled as an articulated object, connected by a prismatic-revolute joint. Different grasping scenarios were considered in order to model the system, and a simple controller based on feedback linearisation is proposed, using force torque measurements to compute the contact point kinematics. The folding assembly controller has been experimentally tested with two sample parts, in order to showcase folding assembly as a viable assembly primitive.Comment: 7 pages, accepted for ICRA 201

Sliding mode control of robotics systems actuated by pneumatic muscles.

This dissertation is concerned with investigating robust approaches for the control of pneumatic muscle systems. Pneumatic muscle is a novel type of actuator. Besides having a high ratio of power to weight and flexible control of movement, it also exhibits many analogical behaviors to natural skeletal muscle, which makes them the ideal candidate for applications of anthropomorphic robotic systems. In this dissertation, a new phenomenological model of pneumatic muscle developed in the Human Sensory Feedback Laboratory at Wright Patterson Air Force Base is investigated. The closed loop stability of a one-link planar arm actuated by two pneumatic muscles using linear state feedback is proved. Robotic systems actuated by pneumatic muscles are time-varying and nonlinear due to load variations and uncertainties of system parameters caused by the effects of heat. Sliding mode control has the advantage that it can provide robust control performance in the presence of model uncertainties. Therefore, it is mainly utilized and further complemented with other control methods in this dissertation to design the appropriate controller to perform the tasks commanded by system operation. First, a sliding mode controller is successfully proposed to track the elbow angle with bounded error in a one-Joint limb system with pneumatic muscles in bicep/tricep configuration. Secondly, fuzzy control, which aims to dynamically adjust the sliding surface, is used along with sliding mode control. The so-called fuzzy sliding mode control method is applied to control the motion of the end-effector in a two-Joint planar arm actuated by four groups of pneumatic muscles. Through computer simulation, the fuzzy sliding mode control shows very good tracking accuracy superior to nonfuzzy sliding mode control. Finally, a two-joint planar arm actuated by four groups of pneumatic muscles operated in an assumed industrial environment is presented. Based on the model, an integral sliding mode control scheme is proposed as an ultimate solution to the control of systems actuated by pneumatic muscles. As the theoretical proof and computer simulations show, the integral sliding mode controller, with strong robustness to model uncertainties and external perturbations, is superior for performing the commanded control assignment. Based on the investigation in this dissertation, integral sliding mode control proposed here is a very promising robust control approach to handle systems actuated by pneumatic muscles

Control strategies for robotic manipulators

This survey is aimed at presenting the major robust control strategies for rigid robot manipulators. The techniques discussed are feedback linearization/Computed torque control, Variable structure compensator, Passivity based approach and Disturbance observer based control. The first one is based on complete dynamic model of a robot. It results in simple linear control which offers guaranteed stability. Variable structure compensator uses a switching/relay action to overcome dynamic uncertainties and disturbances. Passivity based controller make use of passive structure of a robot. If passivity of a feedback system is proved, nonlinearities and uncertainties will not affect the stability. Disturbance observer based controllers estimate disturbances, which can be cancelled out to achieve a nominal model, for which a simple controller can then be designed. This paper, after explaining each control strategy in detail, finally compares these strategies for their pros and cons. Possible solutions to cope with the drawbacks have also been presented in tabular form. © 2012 IEEE

The effect of fractional order in variable structure control

This paper studies fractional variable structure controllers. Two cases are considered namely, the sliding reference model and the control action, that are generalized from integer into fractional orders. The test bed consists in a mechanical manipulator and the effect of the fractional approach upon the system performance is evaluated. The results show that fractional dynamics, both in the switching surface and the control law are important design algorithms in variable structure controllers

Review and Analysis on Main Technology of Exoskeletal Robot System for Upper Limbs Rehabilitation

Major function of exoskeletal robot system for upper limbs rehabilitation is to assist patient to carry out upper limbs’ rehabilitation training. Main technology of exoskeletal robot system for upper limbs rehabilitation includes design of mechanical structure of exoskeletal robot, design of control system of exoskeletal robot and implemention of data and information transmission between exoskeletal robot and upper limbs of human body. Currently implemention of data and information transmission rely mainly on methods of acquiring sEMG signal and force feedback. Reviewing and analyzing the specific technical development and deficiency in field of exoskeletal robot system for upper limbs rehabilitation will be important way in improving and upgrading the technology in future

Robotic Manipulator Control in the Presence of Uncertainty

openThis research focuses on the problem of manipulator control in the presence of uncertainty and aims to compare different approaches for handling uncertainty while developing robust and adaptive methods that can control the robot without explicit knowledge of uncertainty bounds. Uncertainty is a pervasive challenge in robotics, arising from various sources such as sensor noise, modeling errors, and external disturbances. Effectively addressing uncertainty is crucial for achieving accurate and reliable manipulator control. The research will explore and compare existing methods for uncertainty handling such as robust feedback linearization , sliding mode control and robust adaptive control. These methods provide mechanisms to model and compensate for uncertainty in the control system. Additionally, modified robust and adaptive control methods will be developed that can dynamically adjust control laws based on the observed states, without requiring explicit knowledge of uncertainty bounds. To evaluate the performance of the different approaches, comprehensive experiments will be conducted on a manipulator platform. Various manipulation tasks will be performed under different levels of uncertainty, and the performance of each control approach will be assessed in terms of accuracy, stability, and adaptability. Comparative analysis will be conducted to highlight the strengths and weaknesses of each method and identify the most effective approach for handling uncertainty in manipulator control. The outcomes of this research will contribute to the advancement of manipulator control by providing insights into the effectiveness of different approaches for uncertainty handling. The development of new robust and adaptive control methods will enable manipulators to operate in uncertain environments without requiring explicit knowledge of uncertainty bounds. Ultimately, this research will facilitate the deployment of more reliable and adaptive robotic systems capable of handling uncertainty and improving their performance in various real-world applications.This research focuses on the problem of manipulator control in the presence of uncertainty and aims to compare different approaches for handling uncertainty while developing robust and adaptive methods that can control the robot without explicit knowledge of uncertainty bounds. Uncertainty is a pervasive challenge in robotics, arising from various sources such as sensor noise, modeling errors, and external disturbances. Effectively addressing uncertainty is crucial for achieving accurate and reliable manipulator control. The research will explore and compare existing methods for uncertainty handling such as robust feedback linearization , sliding mode control and robust adaptive control. These methods provide mechanisms to model and compensate for uncertainty in the control system. Additionally, modified robust and adaptive control methods will be developed that can dynamically adjust control laws based on the observed states, without requiring explicit knowledge of uncertainty bounds. To evaluate the performance of the different approaches, comprehensive experiments will be conducted on a manipulator platform. Various manipulation tasks will be performed under different levels of uncertainty, and the performance of each control approach will be assessed in terms of accuracy, stability, and adaptability. Comparative analysis will be conducted to highlight the strengths and weaknesses of each method and identify the most effective approach for handling uncertainty in manipulator control. The outcomes of this research will contribute to the advancement of manipulator control by providing insights into the effectiveness of different approaches for uncertainty handling. The development of new robust and adaptive control methods will enable manipulators to operate in uncertain environments without requiring explicit knowledge of uncertainty bounds. Ultimately, this research will facilitate the deployment of more reliable and adaptive robotic systems capable of handling uncertainty and improving their performance in various real-world applications

ROBOTS CONTROL BY ADAPTIVE GAIN SMOOTH SLIDING OBSERVER-CONTROLLER AND PARAMETER IDENTIFICATION

An adaptive gain, smooth sliding observer-controller are developed to control uncertain parameters, -degree of freedom rigid robotic manipulators. Furthermore, an on-line, closed loop identification scheme, for time-varying parameters is proposed in order to obtain useful information despite loads, external disturbances and faults detection. In order to reduce the chattering, a smooth switching function (parameterised tangent hyperbolic function) is used instead of pure relay one, into the observer and the controller. The gains of the switching functions are adaptively updated, depending on the estimation error and tracking error, respectively. By using adaptive gains, the transient and tracking responses are improved. Simulation results with a two degree of freedom (DOF) robot manipulator are presented to show the interest of the approach