Modeling and Control of Flexible Link Manipulators

Autonomous maritime navigation and offshore operations have gained wide attention with the aim of reducing operational costs and increasing reliability and safety. Offshore operations, such as wind farm inspection, sea farm cleaning, and ship mooring, could be carried out autonomously or semi-autonomously by mounting one or more long-reach robots on the ship/vessel. In addition to offshore applications, long-reach manipulators can be used in many other engineering applications such as construction automation, aerospace industry, and space research. Some applications require the design of long and slender mechanical structures, which possess some degrees of flexibility and deflections because of the material used and the length of the links. The link elasticity causes deflection leading to problems in precise position control of the end-effector. So, it is necessary to compensate for the deflection of the long-reach arm to fully utilize the long-reach lightweight flexible manipulators. This thesis aims at presenting a unified understanding of modeling, control, and application of long-reach flexible manipulators. State-of-the-art dynamic modeling techniques and control schemes of the flexible link manipulators (FLMs) are discussed along with their merits, limitations, and challenges. The kinematics and dynamics of a planar multi-link flexible manipulator are presented. The effects of robot configuration and payload on the mode shapes and eigenfrequencies of the flexible links are discussed. A method to estimate and compensate for the static deflection of the multi-link flexible manipulators under gravity is proposed and experimentally validated. The redundant degree of freedom of the planar multi-link flexible manipulator is exploited to minimize vibrations. The application of a long-reach arm in autonomous mooring operation based on sensor fusion using camera and light detection and ranging (LiDAR) data is proposed.publishedVersio

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

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

Genetic algorithm optimization and control system design of flexible structures

This paper presents an investigation into the deployment of genetic algorithm (GA)-based controller design and optimization for vibration suppression in flexible structures. The potential of GA is explored in three case studies. In the first case study, the potential of GA is demonstrated in the development and optimization of a hybrid learning control scheme for vibration control of flexible manipulators. In the second case study, an active control mechanism for vibration suppression of flexible beam structures using GA optimization technique is proposed. The third case study presents the development of an effective adaptive command shaping control scheme for vibration control of a twin rotor system, where GA is employed to optimize the amplitudes and time locations of the impulses in the proposed control algorithm. The effectiveness of the proposed control schemes is verified in both an experimental and a simulation environment, and their performances are assessed in both the time and frequency domains

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

Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance

Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied

Dynamics and Control of Smart Structures for Space Applications

Smart materials are one of the key emerging technologies for a variety of space systems ranging in their applications from instrumentation to structural design. The underlying principle of smart materials is that they are materials that can change their properties based on an input, typically a voltage or current. When these materials are incorporated into structures, they create smart structures. This work is concerned with the dynamics and control of three smart structures: a membrane structure with shape memory alloys for control of the membrane surface flatness, a flexible manipulator with a collocated piezoelectric sensor/actuator pair for active vibration control, and a piezoelectric nanopositioner for control of instrumentation. Shape memory alloys are used to control the surface flatness of a prototype membrane structure. As these actuators exhibit a hysteretic nonlinearity, they need their own controller to operate as required. The membrane structures surface flatness is then controlled by the shape memory alloys, and two techniques are developed: genetic algorithm and proportional-integral controllers. This would represent the removal of one of the main obstacles preventing the use of membrane structures in space for high precision applications, such as a C-band synthetic aperture radar antenna. Next, an adaptive positive position feedback law is developed for control of a structure with a collocated piezoelectric sensor/actuator pair, with unknown natural frequencies. This control law is then combined with the input shaping technique for slew maneuvers of a single-link flexible manipulator. As an alternative to the adaptive positive position feedback law, genetic algorithms are investigated as both system identification techniques and as a tool for optimal controller design in vibration suppression. These controllers are all verified through both simulation and experiments. The third area of investigation is on the nonlinear dynamics and control of piezoelectric actuators for nanopositioning applications. A state feedback integral plus double integral synchronization controller is designed to allow the piezoelectrics to form the basis of an ultra-precise 2-D Fabry-Perot interferometer as the gap spacing of the device could be controlled at the nanometer level. Next, an output feedback linear integral control law is examined explicitly for the piezoelectric actuators with its nonlinear behaviour modeled as an input nonlinearity to a linear system. Conditions for asymptotic stability are established and then the analysis is extended to the derivation of an output feedback integral synchronization controller that guarantees global asymptotic stability under input nonlinearities. Experiments are then performed to validate the analysis. In this work, the dynamics and control of these smart structures are addressed in the context of their three applications. The main objective of this work is to develop effective and reliable control strategies for smart structures that broaden their applicability to space systems

Hybrid intelligent machine systems : design, modeling and control

To further improve performances of machine systems, mechatronics offers some opportunities. Traditionally, mechatronics deals with how to integrate mechanics and electronics without a systematic approach. This thesis generalizes the concept of mechatronics into a new concept called hybrid intelligent machine system. A hybrid intelligent machine system is a system where two or more elements combine to play at least one of the roles such as sensor, actuator, or control mechanism, and contribute to the system behaviour. The common feature with the hybrid intelligent machine system is thus the presence of two or more entities responsible for the system behaviour with each having its different strength complementary to the others. The hybrid intelligent machine system is further viewed from the system’s structure, behaviour, function, and principle, which has led to the distinction of (1) the hybrid actuation system, (2) the hybrid motion system (mechanism), and (3) the hybrid control system. This thesis describes a comprehensive study on three hybrid intelligent machine systems. In the case of the hybrid actuation system, the study has developed a control method for the “true” hybrid actuation configuration in which the constant velocity motor is not “mimicked” by the servomotor which is treated in literature. In the case of the hybrid motion system, the study has resulted in a novel mechanism structure based on the compliant mechanism which allows the micro- and macro-motions to be integrated within a common framework. It should be noted that the existing designs in literature all take a serial structure for micro- and macro-motions. In the case of hybrid control system, a novel family of control laws is developed, which is primarily based on the iterative learning of the previous driving torque (as a feedforward part) and various feedback control laws. This new family of control laws is rooted in the computer-torque-control (CTC) law with an off-line learned torque in replacement of an analytically formulated torque in the forward part of the CTC law. This thesis also presents the verification of these novel developments by both simulation and experiments. Simulation studies are presented for the hybrid actuation system and the hybrid motion system while experimental studies are carried out for the hybrid control system

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world