Intelligent modelling and active vibration control of flexible manipulator system

Unwanted vibration of flexible manipulator results in unsatisfactory performance of any dynamic system using the flexile manipulator. This paper presents a robust control strategy in order to suppress undesirable vibration due to flexible manipulator maneuver. First, the appropriate model of the flexible manipulator is extracted by applying the control-model identification technique for linear and nonlinear model, namely, autoregressive with exogenous input (ARX) model and nonlinear ARX (NARX) respectively. The linear model is estimated by recursive least square method (RLS) and nonlinear model identified by artificial neural network (NN). Finally, the PID controller is designed for each proposed model to cancel the vibration of the flexible manipulator. The robustness of the controller is evaluated by imposing new disturbances into the linear and nonlinear systems. System identification and controller design is conducted by numerical and simulation approaches. The results from simulation indicate that performance of PID controller using linear model is satisfactory compared to nonlinear model

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

Proceedings of the Workshop on Computational Aspects in the Control of Flexible Systems, part 2

The Control/Structures Integration Program, a survey of available software for control of flexible structures, computational efficiency and capability, modeling and parameter estimation, and control synthesis and optimization software are discussed

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

Dynamic modelling and control of a flexible manipulator.

This thesis presents investigations into dynamic modelling and control of a flexible manipulator system. The work on dynamic modelling involves finite element and symbolic manipulation techniques. The control strategies investigated include feedforward control using command shaping techniques and combined feedforward and feedback control schemes. A constrained planar single-link flexible manipulator is used as test and verification platform throughout this work. Dynamic model of a single-link flexible manipulator incorporating structural damping, hub inertia and payload is developed using the finite element method. Experiments are performed on a laboratory-scale single-link flexible manipulator with and without payload for verification of the developed dynamic model. Simulated and experimental system responses to a single-switch bang-bang torque input are presented in the time and frequency domains. Resonance frequencies of the system for the first three modes are identified. The performance and accuracy of the simulation algorithm are studied in comparison to the experimental results in both domains. The effects of damping and payload on the dynamic behaviour of the manipulator are addressed. Moreover, the impact of using higher number of elements is studied. The application of a symbolic manipulation approach for modelling and performance analysis of a flexible manipulator system is investigated. System transfer function can be retained in symbolic form using this approach and good approximation of the system transfer function can be obtained. Relationships between system characteristics and parameters such as payload and hub inertia are accordingly explored. Simulation and experimental exercises are presented to demonstrate the effectiveness of the symbolic approach in modelling and simulation of the flexible manipulator system. Simulation and experimental investigations into the development of feedforward control strategies based on command shaping techniques for vibration control of flexible manipulators are presented. The command shaping techniques using input shaping, low-pass and band-stop filters are considered. The command shaping techniques are designed based on the parameters of the system obtained using the unshaped bang-bang torque input. ii Abstract Performances of the techniques are evaluated in terms of level of vibration reduction, time response specifications, robustness to error in natural frequencies and processing times. The effect of using higher number of impulses and filter orders on the system performance is also investigated. Moreover, the effectiveness of the command shaping techniques in reducing vibrations due to inclusion of payload into the system is examined. A comparative assessment of the performance of the command shaping techniques in vibration reduction of the system is presented. The development of hybrid control schemes for input tracking and vibration suppression of flexible manipulators is presented. The hybrid control schemes based on collocated feedback controllers for rigid body motion control with non-collocated PID control and feedforward control for vibration suppression of the system are examined. The non-collocated PID control is designed utilising the end-point deflection (elastic deformation) feedback whereas feedforward control is designed using the input shaping technique. The developed hybrid schemes are tested within the simulation environment of the flexible manipulator with and without payload. The performances of the control schemes are evaluated in terms of input tracking capability and vibration suppression of the flexible manipulator. Initially, a collocated PD utilising the hub-angle and hub-velocity feedback signals is used as a feedback controller. Subsequently, to achieve uniform performance in the presence of a payload, a collocated adaptive control is designed based on pole-assignment self-tuning control scheme. Lastly, a comparative assessment of the performance of the hybrid control schemes is presented

Fusion of low-cost and light-weight sensor system for mobile flexible manipulator

There is a need for non-industrial robots such as in homecare and eldercare. Light-weight mobile robots preferred as compared to conventional fixed based robots as the former is safe, portable, convenient and economical to implement. Sensor system for light-weight mobile flexible manipulator is studied in this research. A mobile flexible link manipulator (MFLM) contributes to high amount of vibrations at the tip, giving rise to inaccurate position estimations. In a control system, there inevitably exists a lag between the sensor feedback and the controller. Consequently, it contributed to instable control of the MFLM. Hence, there it is a need to predict the tip trajectory of the MFLM. Fusion of low cost sensors is studied to enhance prediction accuracy at the MFLM’s tip. A digital camera and an accelerometer are used predict tip of the MFLM. The main disadvantage of camera is the delayed feedback due to the slow data rate and long processing time, while accelerometer composes cumulative errors. Wheel encoder and webcam are used for position estimation of the mobile platform. The strengths and limitations of each sensor were compared. To solve the above problem, model based predictive sensor systems have been investigated for used on the mobile flexible link manipulator using the selected sensors. Mathematical models were being developed for modeling the reaction of the mobile platform and flexible manipulator when subjected to a series of input voltages and loads. The model-based Kalman filter fusion prediction algorithm was developed, which gave reasonability good predictions of the vibrations of the tip of flexible manipulator on the mobile platform. To facilitate evaluation of the novel predictive system, a mobile platform was fabricated, where the flexible manipulator and the sensors are mounted onto the platform. Straight path motions were performed for the experimental tests. The results showed that predictive algorithm with modelled input to the Extended Kalman filter have best prediction to the tip vibration of the MFLM

マルチ スケール キノウ ヲ ユウスル コウソク ジドウ マイクロ マニピュレーション システム

Ebubekir Avci, Chanh-Nghiem Nguyen, Kenichi Ohara, Yasushi Mae, Tatsuo Arai, Analysis and suppression of residual vibration in microhand for high-speed single-cell manipulation, International Journal of Mechatronics and Automation, 2013-Vol.3, No.2, pp.110-11

Geometric soft robotics: a finite element approach

Enabling remote semi-autonomous operations in hazardous environments is a challenging technological problem, given the difficulty to access in confined and constrained spaces using classical robotic systems. Inspired by biological trunks and tentacles, soft continuum robots constitute a possible solution to this problem, for their ability to traverse confined spaces, manipulate objects in complex environments, and conform their shape to nonlinear curvilinear paths. The need of reaching difficult-to-access industrial sites for maintenance and inspection procedures or anatomical sites for less invasive robotic surgery mainly motivates the current research. Despite the recent advances in the design and fabrication of soft robots, the community still suffers for the lack of a consolidate modeling framework for simulating their mechanical behavior. Such a modeling framework is the necessary condition for developing new physical design and control strategies, as well as path planning algorithms. Indeed, despite their appreciable features, soft robots usually generate undesired vibrations during normal procedures. This is one of the main reasons which still limits their potentially wide use in real scenario. Realistic modeling frameworks might leverage the development of model-based predictive controllers to compensate for the undesired vibrations, as well as design concepts and optimized trajectories to avoid the excitation of the vibration modes of the mechanical structure. The main objective of the thesis is to develop a unified mathematical framework for simulating the mechanical behavior of soft continuum robotic manipulators, which can also accommodate the dynamic simulation of classical rigid robots. The computer implementation of this theoretical framework leads to the development of SimSOFT, a physics engine for soft robots. The formulation has been validated through literature benchmark and some applications are presented. One of the major strengths of the framework is that it can accommodate the realistic simulation of kinematic trees or loops constituted either by rigid or soft arms connected by rigid or flexible joints.The simulation of hybrid mechanisms, composed by classical rigid kinematic chains and soft continuum manipulators, which can be used to have larger dexterity in smaller workspaces, as they are easily to miniaturize, is thus possible. To the best of the author's knowledge, the mathematical models developed in the thesis constitute the first attempt in the robotics community towards a unified framework for the dynamics of soft continuum multibody systems