Dynamic modeling and parameter estimation of a hydraulic robot manipulator using a multi-objective genetic algorithm

This article concerns the problem of dynamic modeling and parameter estimation for a seven degree of freedom hydraulic manipulator. The laboratory example is a dual-manipulator mobile robotic platform used for research into nuclear decommissioning. In contrast to earlier control model orientated research using the same machine, the article develops a nonlinear, mechanistic simulation model that can subsequently be used to investigate physically meaningful disturbances. The second contribution is to optimize the parameters of the new model, i.e. to determine reliable estimates of the physical parameters of a complex robotic arm which are not known in advance. To address the nonlinear and non-convex nature of the problem, the research relies on the multi-objectivization of an output error single performance index. The developed algorithm utilises a multi-objective Genetic Algorithm (GA) in order to find a proper solution. The performance of the model and the GA is evaluated using both simulated (i.e. with a known set of ‘true’ parameters) and experimental data. Both simulation and experimental results show that multi-objectivization has improved convergence of the estimated parameters compared to the single objective output error problem formulation. This is achieved by integrating the validation phase inside the algorithm implicitly and exploiting the inherent structure of the multi-objective GA for this specific system identification problem

A new approach to improve the parameter estimation accuracy in robotic manipulators using a multi-objective output error identification technique

The research behind this article primarily concerns the development of mobile robots for nuclear decommissioning. The robotic platform under study has dual, seven-function, hydraulically actuated manipulators, for which the authors have developed a vision based, assisted teleoperation interface for common decommissioning tasks such as pipe cutting. However, to improve safety, task execution speed and operator training-time, high performance control of the nonlinear manipulator dynamics is required. Hence, the present article focuses on an associated dynamic model, and addresses the challenging generic task of parameter estimation for a highly convex and nonlinear system. A novel approach for estimation of the fundamental parameters of the manipulator, based on the idea of multi-objectivization, is proposed. Here, a single objective output error identification problem is converted into a multi-objective optimization problem. This is solved using a multi-objective genetic algorithm with non-dominated sorting. Numerical and experimental results using the nuclear decommissioning robot, show that the performance of the proposed approach, in terms of both the output error index and the accuracy of the estimated parameters, is superior to the previously studied single-objective identification problem

Development of an assisted-teleoperation system for a dual-manipulator nuclear decommissioning robot

This thesis concerns a robotic platform that is being used for research into assisted tele–operation for common nuclear decommissioning tasks, such as remote handling and pipe cutting. The machine consists of dual, seven–function, hydraulically actuated HYDROLEK manipulators mounted (in prior research) on a mobile BROKK base unit. Whilst the original system was operated by remote control, the present thesis focusses on the development of a visual servoing system, in which the user selects the object of interest from an on–screen image, whilst the computer control system determines and implements via feedback control the required position and orientation of the manipulators. Novel research contributions are made in three main areas: (i) the development of a detailed mechanistic model of the system; (ii) the development and preliminary testing in the laboratory of the new assisted–teleoperation user interface; and (iii) the development of improved control systems for joint angle set point tracking, and their systematic, quantitative comparison via simulation and experiment. The mechanistic model builds on previous work, while the main novelty in this thesis relates to the hydraulic component of the model, and the development and evaluation of a multi–objective genetic algorithm framework to identify the unknown parameter values. To improve on the joystick direct teleoperation currently used as standard in the nuclear industry, which is slow and requires extensive operator training, the proposed assisted–teleoperation makes use of a camera mounted on the robot. Focussing on pipe cutting as an example, the new system ensures that one manipulator automatically grasps the user–selected pipe, and appropriately positions the second for a cutting operation. Initial laboratory testing (using a plastic pipe) shows the efficacy of the approach for positioning the manipulators, and suggests that for both experienced and inexperienced users, the task is completed significantly faster than via tele-operation. Finally, classical industrial, fuzzy logic, and novel state dependent parameter approaches to control are developed and compared, with the aim being to determine a relatively simple controller that yields good performance for the hydraulic manipulators. An improved, more structured method of dealing with the dead–zone characteristics is developed and implemented, replacing the rather ad hoc approach that had been utilised in previous research for the same machine

Visual Servoing in Robotics

Visual servoing is a well-known approach to guide robots using visual information. Image processing, robotics, and control theory are combined in order to control the motion of a robot depending on the visual information extracted from the images captured by one or several cameras. With respect to vision issues, a number of issues are currently being addressed by ongoing research, such as the use of different types of image features (or different types of cameras such as RGBD cameras), image processing at high velocity, and convergence properties. As shown in this book, the use of new control schemes allows the system to behave more robustly, efficiently, or compliantly, with fewer delays. Related issues such as optimal and robust approaches, direct control, path tracking, or sensor fusion are also addressed. Additionally, we can currently find visual servoing systems being applied in a number of different domains. This book considers various aspects of visual servoing systems, such as the design of new strategies for their application to parallel robots, mobile manipulators, teleoperation, and the application of this type of control system in new areas

Development of Novel Compound Controllers to Reduce Chattering of Sliding Mode Control

The robotics and dynamic systems constantly encountered with disturbances such as micro electro mechanical systems (MEMS) gyroscope under disturbances result in mechanical coupling terms between two axes, friction forces in exoskeleton robot joints, and unmodelled dynamics of robot manipulator. Sliding mode control (SMC) is a robust controller. The main drawback of the sliding mode controller is that it produces high-frequency control signals, which leads to chattering. The research objective is to reduce chattering, improve robustness, and increase trajectory tracking of SMC. In this research, we developed controllers for three different dynamic systems: (i) MEMS, (ii) an Exoskeleton type robot, and (iii) a 2 DOF robot manipulator. We proposed three sliding mode control methods such as robust sliding mode control (RSMC), new sliding mode control (NSMC), and fractional sliding mode control (FSMC). These controllers were applied on MEMS gyroscope, Exoskeleton robot, and robot manipulator. The performance of the three proposed sliding mode controllers was compared with conventional sliding mode control (CSMC). The simulation results verified that FSMC exhibits better performance in chattering reduction, faster convergence, finite-time convergence, robustness, and trajectory tracking compared to RSMC, CSMC, and NSFC. Also, the tracking performance of NSMC was compared with CSMC experimentally, which demonstrated better performance of the NSMC controller

Unknown and time-varying time delays in the modelling and control of hydraulic actuators:literature review

Uncertain time-delays can reduce the performance of hydraulic manipulator control systems. Variations in the time delay between, for example, an applied voltage and the associated manipulator movement, may be caused by the internal dynamics of the system and other nonlinear characteristics, such as fluid compressibility, dead-band of the pump, valve flow properties and friction characteristics. Robot control that addresses system time-delays, nonlinearities and uncertainty is the subject of much research but, whilst the specific concept of varying time delays in hydraulic systems is sometimes acknowledged, it appears to be less widely investigated than other types of uncertainty. The present article discuses some of the issues involved, exemplified by a dual manipulator device used in the laboratory for research into nuclear decommissioning, and presents a review of the relevant control literature in this area

Extended grey wolf optimization–based adaptive fast nonsingular terminal sliding mode control of a robotic manipulator

This article proposes a novel hybrid metaheuristic technique based on nonsingular terminal sliding mode controller, time delay estimation method, an extended grey wolf optimization algorithm and adaptive super twisting control law. The fast convergence is assured by nonsingular terminal sliding mode controller owing to its inherent nonlinear property and no prior knowledge of the robot dynamics is required due to time delay estimation. The proposed extended grey wolf optimization algorithm determines an optimal approximation of the inertial matrix of the robot. Moreover, adaptive super twisting control based on the Lyapunov approach overcomes the disturbances and compensate the higher dynamics not achievable by the time delay estimation method. First, the fast nonsingular terminal sliding mode controller relying on time delay estimation is designed and is combined with super twisting control for chattering attenuation. The constant gain matrix of the time delay is determined by the proposed extended grey wolf optimization algorithm. Second, an adaptive law based on Lyapunov stability theorem is designed for improving tracking performance in the presence of uncertainties and disturbances. The novelty of the proposed method lies in the adaptive law where the prior knowledge of parametric uncertainties and disturbances is not needed. Moreover, the constant gain matrix of time delay estimation method is obtained using the proposed algorithm. The control method has been tested in simulation on a 3-degrees of freedom robotic manipulator in trajectory tracking mode in the presence of control disturbances and uncertainties. The results obtained confirmed the effectiveness, robustness and the superior precision of the proposed control method compared to the classical ones

Reduced chatter sliding mode control for hydraulic manipulators based on continuous–time state dependent parameter models

Sliding Mode Control (SMC) systems are developed for a hydraulic manipulator. The control model is obtained via state-dependent parameter (SDP) system identification. In contrast to previous research using discrete-time SDP models, in which the model coefficients are functions of the sampling interval, the present work develops a new continuous-time approach. It is well known that for conventional SMC there is a trade-off between chattering and robust performance. Hence, a recently developed approach to address this problem is investigated, in which the controller is designed via a fractional exponent of the sliding surface. The approach is developed for both conventional and Nonsingular Terminal SMC (NTSMC). The new continuous version of the NTSMC algorithm successfully reduces chattering and provides the best overall performance of various SMC designs. However, for the preliminary experiments reported in this article, a PID lead-lag controller yields the lowest absolute errors, albeit at the cost of a higher control effort. Hence, given that dead-zone and other uncertainties provide the main motivation for use of SMC in this application, further research into the robustness of the new algorithm is required