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

Fuzzy PD control of an optically guided long reach robot

This thesis describes the investigation and development of a fuzzy controller for a manipulator with a single flexible link. The novelty of this research is due to the fact that the controller devised is suitable for flexible link manipulators with a round cross section. Previous research has concentrated on control of flexible slender structures that are relatively easier to model as the vibration effects of torsion can be ignored. Further novelty arises due to the fact that this is the first instance of the application of fuzzy control in the optical Tip Feedback Sensor (TFS) based configuration. A design methodology has been investigated to develop a fuzzy controller suitable for application in a safety critical environment such as the nuclear industry. This methodology provides justification for all the parameters of the fuzzy controller including membership fUllctions, inference and defuzzification techniques and the operators used in the algorithm. Using the novel modified phase plane method investigated in this thesis, it is shown that the derivation of complete, consistent and non-interactive rules can be achieved. This methodology was successfully applied to the derivation of fuzzy rules even when the arm was subjected to different payloads. The design approach, that targeted real-time embedded control applicat.ions from the outset, results in a controller implementation that is suitable for cheaper CPU constrained and memory challenged embedded processors. The controller comprises of a fuzzy supervisor that is used to alter the derivative term of a linear classical Proportional + Derivative (PD) controller. The derivative term is updated in relation to the measured tip error and its derivative obtained through the TFS based configuration. It is shown that by adding 'intelligence' to the control loop in this way, the performance envelope of the classical controller can be enhanced. A 128% increase in payload, 73.5% faster settling time and a reduction of steady state of over 50% is achieved using fuzzy control over its classical counterpart

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

Modelling and control of a robotic manipulator subject to base disturbances

This thesis presents the modelling and control of a high gear ratio robotic manipulator mounted on a heavier moving base which is subject to base disturbances. The manipulator motion is assumed not to affect the base motion. The problem of a robotic manipulator on a non-inertial base can be applied to operation on sea vessels or all-terrain vehicles, where the base motion is unknown and cannot be used as a feed-forward signal to the model. A dynamic model is derived for the PA10-6CE manipulator with the assumption of a fixed base and the model terms are analysed numerically when comparing the simulation and experimental results. Based on the obtained results a set of model based controllers is compared to a basic proportional and derivative type controller to evaluate the trajectory tracking gains and trade-offs. The dynamic model is extended to the case of a manipulator on a moving base and numerical comparisons of simulation and experimental results are used to verify the model validity and the significance of the various model terms. From the results of this study a set of model based controllers is obtained. A novel adaptive scheme is then proposed for compensation of an unknown and varying gravity acceleration vector acting on the manipulator base. Controllers based on using an additional sensor output are compared with static and adaptive gravity controllers and the latter proved to be superior in terms of trajectory tracking performance

Modeling and Control of 5DOF Robot Arm Using Supervisory Control

Modeling and control of 5 degree of freedom (DOF) robot arm is the subject of this thesis. The modeling problem is necessary before applying control techniques to guarantee the execution of any task according to a desired input with minimum error. Deriving both forward and inverse kinematics is an important step in robot modeling based on Denavit Hartenberg (DH) representation. The main objective of this thesis is to control a robot arm using three controllers to acquire the desired position. Proportional integral derivative (PID) controller is used as a reference benchmark to compare its results with fuzzy logic controller (FLC) and fuzzy supervisory controller (FSC) results. FLC is applied as a second controller because of the nonlinearity in the robot manipulators. We compare the result of the PID controller and FLC results in terms of time response specifications. FSC is a hybrid between the previous two controllers. The FSC is used for tuning PID gains since PID alone performs not satisfactory in nonlinear systems. Hence, comparison of tuning of PID parameters is utilized using classical method and FSC method. Based on simulation results, FLC gives better results than classical PID controller in terms of time response and FSC is better than classical methods such as Ziegler-Nichols (ZN) in tuning PID parameters in terms of time response

Performing heavy transfers for offshore wind maintenance

As offshore wind farms become larger and further from the shore, there are strong economic and climate incentives to perform transfers required for operations and maintenance from floating vessels, rather than employing expensive and slow jack up rigs. However, successful transfers of heavy and sensitive equipment from a floating vessel (in all but benign sea/wind conditions) are heavily dependent on multiple degrees of freedom, high performance control. This project aims to bring a novel modelling and simulation methodology in Simulink that could be used to assess offshore wind installation and maintenance procedures. More specifically, the goal is to demonstrate that a crane prototype assumed to be located on a floating ship can transfer loads of hundreds of tons onto a fixed platform. Furthermore, this process should be completed with good precision and minimal impact force during equipment loading onto the stand. This problem has not yet been answered in research, with the only relevant patent in the field being the Ampelmann platform, a motionless bridge allowing technicians to access the offshore turbine. The first main contribution to knowledge of this thesis was the design of a 90 m crane that could handle a 660 tons load. This thesis presents a procedure, based on both mechanical/hydraulics design as well as empirical findings, which could be re-used for scaling the crane model to a more realistic dimension. It is worth noting that the goal here was to assess whether a realistically weighing piece of equipment could be stably handled, while the actual size of the crane was deemed unimportant. Another missing gap in literature this project wanted to fill was achieving active motion compensation for a larger scale system such as the current one. This refers to balancing out the base motions on multiple axes, so the payload can be moved on a given trajectory unaffected by them. Currently, research in the field mainly consists of crane mechanisms that feature active heave compensation, which only refers to the vertical axis. Hence, two control design methods were employed to assess the viability of heavy payload positioning from floating vessels through the development of a simulation approach using Simulink. The crane prototype was designed and modelled to operate under simulated vessel motions given by sea states with a significant wave height of 5 m and maximum wave frequency of 1 rad/s. Then, traditional control (feedback and feedforward) was designed to achieve active motion compensation with steady-state position errors under 20 cm. A second controller architecture was then designed/implemented as a comparison basis for the first one, with the aim being to find the most robust solution of the two. The nonlinear generalised minimum variance (NGMV) control algorithm was chosen for control design in this application. Due to its ability to compensate for significant system nonlinearities and the ease of implementation, NGMV was a good candidate for the task at hand. Tuning controller parameters to stabilize the system could also be based on the previously determined traditional control solutions. An investigation of controllers’ robustness against model mismatch was carried out by introducing various levels of uncertainty which influence actuators’ natural frequency to assess system sensitivity. The outcome of the investigation determined that traditional and NGMV controllers provided comparable regulating performance in terms of reference tracking and disturbance rejection, for the nominal case. This confirmed the assertion that the PID-based NGMV weightings selection is a useful starting point for controller tuning. Increasing the mismatch between the nominal system based on which the controllers’ were designed and the actual plant showed that the traditional control was marginally more robust in this application. The final contribution to knowledge this thesis aimed to bring was minimising the impact force during load placement on a fixed and rigid platform. To that end, the contact forces between the payload and a platform were first successfully modelled and measured. A switching algorithm between position and force control was then developed based on a methodology found in literature but on a microscopic scale project. To execute smooth load placement, an automated hybrid force/position control scheme was implemented. The proposed algorithm enabled position control on x and y axes, while minimising impact forces on the z-axis. Unfortunately, preliminary findings showed that there is still work to be done to claim any success in this regard. However, the author hopes this offers a good starting point for future work.As offshore wind farms become larger and further from the shore, there are strong economic and climate incentives to perform transfers required for operations and maintenance from floating vessels, rather than employing expensive and slow jack up rigs. However, successful transfers of heavy and sensitive equipment from a floating vessel (in all but benign sea/wind conditions) are heavily dependent on multiple degrees of freedom, high performance control. This project aims to bring a novel modelling and simulation methodology in Simulink that could be used to assess offshore wind installation and maintenance procedures. More specifically, the goal is to demonstrate that a crane prototype assumed to be located on a floating ship can transfer loads of hundreds of tons onto a fixed platform. Furthermore, this process should be completed with good precision and minimal impact force during equipment loading onto the stand. This problem has not yet been answered in research, with the only relevant patent in the field being the Ampelmann platform, a motionless bridge allowing technicians to access the offshore turbine. The first main contribution to knowledge of this thesis was the design of a 90 m crane that could handle a 660 tons load. This thesis presents a procedure, based on both mechanical/hydraulics design as well as empirical findings, which could be re-used for scaling the crane model to a more realistic dimension. It is worth noting that the goal here was to assess whether a realistically weighing piece of equipment could be stably handled, while the actual size of the crane was deemed unimportant. Another missing gap in literature this project wanted to fill was achieving active motion compensation for a larger scale system such as the current one. This refers to balancing out the base motions on multiple axes, so the payload can be moved on a given trajectory unaffected by them. Currently, research in the field mainly consists of crane mechanisms that feature active heave compensation, which only refers to the vertical axis. Hence, two control design methods were employed to assess the viability of heavy payload positioning from floating vessels through the development of a simulation approach using Simulink. The crane prototype was designed and modelled to operate under simulated vessel motions given by sea states with a significant wave height of 5 m and maximum wave frequency of 1 rad/s. Then, traditional control (feedback and feedforward) was designed to achieve active motion compensation with steady-state position errors under 20 cm. A second controller architecture was then designed/implemented as a comparison basis for the first one, with the aim being to find the most robust solution of the two. The nonlinear generalised minimum variance (NGMV) control algorithm was chosen for control design in this application. Due to its ability to compensate for significant system nonlinearities and the ease of implementation, NGMV was a good candidate for the task at hand. Tuning controller parameters to stabilize the system could also be based on the previously determined traditional control solutions. An investigation of controllers’ robustness against model mismatch was carried out by introducing various levels of uncertainty which influence actuators’ natural frequency to assess system sensitivity. The outcome of the investigation determined that traditional and NGMV controllers provided comparable regulating performance in terms of reference tracking and disturbance rejection, for the nominal case. This confirmed the assertion that the PID-based NGMV weightings selection is a useful starting point for controller tuning. Increasing the mismatch between the nominal system based on which the controllers’ were designed and the actual plant showed that the traditional control was marginally more robust in this application. The final contribution to knowledge this thesis aimed to bring was minimising the impact force during load placement on a fixed and rigid platform. To that end, the contact forces between the payload and a platform were first successfully modelled and measured. A switching algorithm between position and force control was then developed based on a methodology found in literature but on a microscopic scale project. To execute smooth load placement, an automated hybrid force/position control scheme was implemented. The proposed algorithm enabled position control on x and y axes, while minimising impact forces on the z-axis. Unfortunately, preliminary findings showed that there is still work to be done to claim any success in this regard. However, the author hopes this offers a good starting point for future work

Development of New Adaptive Control Strategies for a Two-Link Flexible Manipulator

Manipulators with thin and light weight arms or links are called as Flexible-Link Manipulators (FLMs). FLMs offer several advantages over rigid-link manipulators such as achieving highspeed operation, lower energy consumption, and increase in payload carrying capacity and find applications where manipulators are to be operated in large workspace like assembly of freeflying space structures, hazardous material management from safer distance, detection of flaws in large structure like airplane and submarines. However, designing a feedback control system for a flexible-link manipulator is challenging due the system being non-minimum phase, underactuated and non-collocated. Further difficulties are encountered when such manipulators handle unknown payloads. Overall deflection of the flexible manipulator are governed by the different vibrating modes (excited at different frequencies) present along the length of the link. Due to change in payload, the flexible modes (at higher frequencies) are excited giving rise to uncertainties in the dynamics of the FLM. To achieve effective tip trajectory tracking whilst quickly suppressing tip deflections when the FLM carries varying payloads adaptive control is necessary instead of fixed gain controller to cope up with the changing dynamics of the manipulator. Considerable research has been directed in the past to design adaptive controllers based on either linear identified model of a FLM or error signal driven intelligent supervised learning e.g. neural network, fuzzy logic and hybrid neuro-fuzzy. However, the dynamics of the FLM being nonlinear there is a scope of exploiting nonlinear modeling approach to design adaptive controllers. The objective of the thesis is to design advanced adaptive control strategies for a two-link flexible manipulator (TLFM) to control the tip trajectory tracking and its deflections while handling unknown payloads. To achieve tip trajectory control and simultaneously suppressing the tip deflection quickly when subjected to unknown payloads, first a direct adaptive control (DAC) is proposed. The proposed DAC uses a Lyapunov based nonlinear adaptive control scheme ensuring overall system stability for the control of TLFM. For the developed control laws, the stability proof of the closed-loop system is also presented. The design of this DAC involves choosing a control law with tunable TLFM parameters, and then an adaptation law is developed using the closed loop error dynamics. The performance of the developed controller is then compared with that of a fuzzy learning based adaptive controller (FLAC). The FLAC consists of three major components namely a fuzzy logic controller, a reference model and a learning mechanism. It utilizes a learning mechanism, which automatically adjusts the rule base of the fuzzy controller so that the closed loop performs according to the user defined reference model containing information of the desired behavior of the controlled system. Although the proposed DAC shows better performance compared to FLAC but it suffers from the complexity of formulating a multivariable regressor vector for the TLFM. Also, the adaptive mechanism for parameter updates of both the DAC and FLAC depend upon feedback error based supervised learning. Hence, a reinforcement learning (RL) technique is employed to derive an adaptive controller for the TLFM. The new reinforcement learning based adaptive control (RLAC) has an advantage that it attains optimal control adaptively in on-line. Also, the performance of the RLAC is compared with that of the DAC and FLAC. In the past, most of the indirect adaptive controls for a FLM are based on linear identified model. However, the considered TLFM dynamics is highly nonlinear. Hence, a nonlinear autoregressive moving average with exogenous input (NARMAX) model based new Self-Tuning Control (NMSTC) is proposed. The proposed adaptive controller uses a multivariable Proportional Integral Derivative (PID) self-tuning control strategy. The parameters of the PID are adapted online using a nonlinear autoregressive moving average with exogenous-input (NARMAX) model of the TLFM. Performance of the proposed NMSTC is compared with that of RLAC. The proposed NMSTC law suffers from over-parameterization of the controller. To overcome this a new nonlinear adaptive model predictive control using the NARMAX model of the TLFM (NMPC) developed next. For the proposed NMPC, the current control action is obtained by solving a finite horizon open loop optimal control problem on-line, at each sampling instant, using the future predicted model of the TLFM. NMPC is based on minimization of a set of predicted system errors based on available input-output data, with some constraints placed on the projected control signals resulting in an optimal control sequence. The performance of the proposed NMPC is also compared with that of the NMSTC. Performances of all the developed algorithms are assessed by numerical simulation in MATLAB/SIMULINK environment and also validated through experimental studies using a physical TLFM set-up available in Advanced Control and Robotics Research Laboratory, National Institute of Technology Rourkela. It is observed from the comparative assessment of the performances of the developed adaptive controllers that proposed NMPC exhibits superior 7performance in terms of accurate tip position tracking (steady state error ≈ 0.01°) while suppressing the tip deflections (maximum amplitude of the tip deflection ≈ 0.1 mm) when the manipulator handles variation in payload (increased payload of 0.3 kg). The adaptive control strategies proposed in this thesis can be applied to control of complex flexible space shuttle systems, long reach manipulators for hazardous waste management from safer distance and for damping of oscillations for similar vibration systems

Controlo de uma plataforma servo-hidráulica com cinemática paralela para estampagem incremental

Mestrado em Engenharia MecânicaSPIF-A is an innovative project about Gough-Stewart platform using parallel kinematics for incremental forming that is supported by different fields of engineering. It is a long term work composed by a professional team that includes professors, students and researchers fancying to improve and contribute for scientific knowledge. Incremental forming is emerging due to its useful advantages, highlighting the high-speed machining. The objective is the control of a Gough-Stewart platform, planning and execution of G-code trajectories. Thereunto, a state-of-the-art regarding incremental forming, parallel platforms, parallel kinematics and control theory is carried out. Position controllers and trajectory planning are developed and implemented for a 6 degree-of-freedom manipulator. Accuracy and reliability tests are done to consummate an hardware improvement. Some types of controllers, based in fuzzy logic and one linear PID, were studied and executed on this platform in order to improve its control system.SPIF-A é um projecto inovador sobre uma plataforma de Gough- Stweart com cinemática paralela para estampagem incremental que abrange inúmeras áreas da engenharia. É um trabalho de longa data composto por uma equipa de profissionais entre professores, estudantes e investigadores que visa estimular o conhecimento científico. A estampagem incremental está muito em voga uma vez que as suas vantagens são tremendas. Dentro desta, destaca-se a estampagem incremental de alta velocidade. O objetivo é então o controlo de uma plataforma Gough-Stewart, planeamento e execução de trajetórias ISO. Para isso, é feita uma revisão do estado da arte sobre estampagem incremental, plataformas paralelas, cinemática paralela e teoria de controladores. São desenvolvidos e implementados controladores de posição e definidas trajetórias para um manipulador de 6 graus de liberdade. São levados a cabo testes de precisão e fiabilidade do hardware do manipulador tendo em vista a sua melhoria futura. Uma série de controladores, baseados em lógica difusa e um controlador PID linear, foram estudados e testados durante a implementação do novo hardware na plataforma tendo em conta a melhoria de todo o seu sistema de controlo