A Novel Adaptive Sliding Mode Controller for a 2-DOF Elastic Robotic Arm

Collaborative robots (or cobots) are robots that are capable of safely operating in a shared environment or interacting with humans. In recent years, cobots have become increasingly common. Compliant actuators are critical in the design of cobots. In real applications, this type of actuation system may be able to reduce the amount of damage caused by an unanticipated collision. As a result, elastic joints are expected to outperform stiff joints in complex situations. In this work, the control of a 2-DOF robot arm with elastic actuators is addressed by proposing a two-loop adaptive controller. For the outer control loop, an adaptive sliding mode controller (ASMC) is adopted to deal with uncertainties and disturbance on the load side of the robot arm. For the inner loops, model reference adaptive controllers (MRAC) are utilised to handle the uncertainties on the motor side of the robot arm. To show the effectiveness of the proposed controller, extensive simulation experiments and a comparison with the conventional sliding mode controller (SMC) are carried out. As a result, the ASMC has a 50.35% lower average RMS error than the SMC controller, and a shorter settling time (5% criterion) (0.44 s compared to 2.11 s).publishedVersio

Magnetorheological Variable Stiffness Robot Legs for Improved Locomotion Performance

In an increasingly automated world, interest in the field of robotics is surging, with an exciting branch of this area being legged robotics. These biologically inspired robots have leg-like limbs which enable locomotion, suited to challenging terrains which wheels struggle to conquer. While it has been quite some time since the idea of a legged machine was first made a reality, this technology has been modernised with compliant legs to improve locomotion performance. Recently, developments in biological science have uncovered that humans and animals alike control their leg stiffness, adapting to different locomotion conditions. Furthermore, as these studies highlighted potential to improve upon the existing compliant-legged robots, modern robot designs have seen implementation of variable stiffness into their legs. As this is quite a new concept, few works have been published which document such designs, and hence much potential exists for research in this area. As a promising technology which can achieve variable stiffness, magnetorheological (MR) smart materials may be ideal for use in robot legs. In particular, recent advances have enabled the use of MR fluid (MRF) to facilitate variable stiffness in a robust manner, in contrast to MR elastomer (MRE). Developed in this thesis is what was at the time the first rotary MR damper variable stiffness mechanism. This is proposed by the author for use within a robot leg to enable rapid stiffness control during locomotion. Based its mechanics and actuation, the leg is termed the magnetorheological variable stiffness actuator leg mark-I (MRVSAL-I). The leg, with a C-shaped morphology suited to torque actuation is first characterised through linear compression testing, demonstrating a wide range of stiffness variation. This variation is in response to an increase in electric current supplied to the internal electromagnetic coils of the MR damper. A limited degrees-of-freedom (DOF) bipedal locomotion platform is designed and manufactured to study the locomotion performance resulting from the variable stiffness leg. It is established that optimal stiffness tuning of the leg could achieve reduced mechanical cost of transport (MCOT), thereby improving locomotion performance. Despite the advancements to locomotion demonstrated, some design issues with the leg required further optimisation and a new leg morphology

Master of Science

thesisThis research studies the passive dynamics of an under-actuated trotting quadruped. The goal of this project is to perform three-dimensional (3D) dynamic simulations of a trotting quadruped robot to find proper leg configurations and stiffness range, in order to achieve stable trotting gait. First, a 3D simulation framework that includes all the six degrees of freedom of the body is introduced. Directionally compliant legs together with different leg configurations are employed to achieve passive stability. Compliant legs passively support the body during stance phase and during flight phase a motor is used to retract the legs. Leg configurations in the robot's sagittal and frontal plane are introduced. Numerical experiments are conducted to search the design space of the leg, focusing on increasing the passive stability of the robot. Increased stability is defined as decreased pitching, rolling, and yawing motion of the robot. The results indicate that optimized leg parameters can guarantee passive stable trotting with reduced roll, pitch, and yaw. Studies suggest that a quadruped robot with compliant legs is dynamically stable while trotting. Results indicate that the robot based on a biological model (i.e., caudal inclination of humeri and cranial inclination of femora) has the best performance. Stiff springs at hips and shoulders, soft spring at knees and elbows, and stiff springs at ankles and wrists are recommended. The results of this project provide a conceptual framework for understanding the movements of a trotting quadruped

Control of Nonlinear Mechatronic Systems

This dissertation is divided into four self-contained chapters. In Chapter 1, an adaptive nonlinear tracking controller for kinematically redundant robot manipulators is presented. Past research efforts have focused on the end-effector tracking control of redundant robots because of their increased dexterity over their non-redundant counterparts. This work utilizes an adaptive full-state feedback quaternion based controller developed in [1] and focuses on the design of a general sub-task controller. This sub-task controller does not affect the position and orientation tracking control objectives, but instead projects a preference on the configuration of the manipulator based on sub-task objectives such as the following: singularity avoidance, joint limit avoidance, bounding the impact forces, and bounding the potential energy. In Chapter 2, two controllers are developed for nonlinear haptic and teleoperator systems for coordination of the master and slave systems. The first controller is proven to yield a semi-global asymptotic result in the presence of parametric uncertainty in the master and the slave dynamic models provided the user and the environmental input forces are measurable. The second controller yields a global asymptotic result despite unmeasurable user and environmental input forces provided the dynamic models of the master and slave systems are known. These controllers rely on a transformation and a flexible target system to allow the master system\u27s impedance to be easily adjusted so that it matches a desired target system. This work also offers a structure to encode a velocity field assist mechanism to provide the user help in controlling the slave system in completing a pre-defined contour following task. For each controller, Lyapunov-based techniques are used to prove that both controllers provide passive coordination of the haptic/teleoperator system when the velocity field assist mechanism is disabled. When the velocity field assist mechanism is enabled, the analysis proves the coordination of the haptic/teleoperator system. Simulation results are presented for both controllers. In Chapter 3, two controllers are developed for flat multi-input/multi-output nonlinear systems. First, a robust adaptive controller is proposed and proven to yield semi-global asymptotic tracking in the presence of additive disturbances and parametric uncertainty. In addition to guaranteeing an asymptotic output tracking result, it is also proven that the parameter estimate vector is driven to a constant vector. In the second part of the chapter, a learning controller is designed and proven to yield a semi-global asymptotic tracking result in the presence of additive disturbances where the desired trajectory is periodic. A continuous nonlinear integral feedback component is utilized in the design of both controllers and Lyapunov-based techniques are used to guarantee that the tracking error is asymptotically driven to zero. Numerical simulation results are presented for both controllers. In Chapter 4, a new dynamic model for continuum robot manipulators is derived. The dynamic model is developed based on the geometric model of extensible continuum robot manipulators with no torsional effects. The development presented in this chapter is an extension of the dynamic model proposed in [2] (by Mochiyama and Suzuki) to include a class of extensible continuum robot manipulators. First, the kinetic energy of a slice of the continuum robot is evaluated. Next, the total kinetic energy of the manipulator is obtained by utilizing a limit operation (i.e., sum of the kinetic energy of all the slices). Then, the gravitational potential energy of the manipulator is derived. Next, the elastic potential energy of the manipulator is derived for both bending and extension. Finally, the dynamic model of a planar 3-section extensible continuum robot manipulator is derived by utilizing the Lagrange representation. Numerical simulation results are presented for a planar 3-section extensible continuum robot manipulator

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

Adaptive Robust Quadratic Stabilization Tracking Control for Robotic System with Uncertainties and External Disturbances

An adaptive robust quadratic stabilization tracking controller with hybrid scheme is proposed for robotic system with uncertainties and external disturbances. The hybrid scheme combines computed torque controller (CTC) with an adaptive robust compensator, in which variable structure control (VSC) and H∞ optimal control approaches are adopted. The uncertain robot manipulator is mainly controlled by CTC, the VSC is used to eliminate the effect of the uncertainties and ensure global stability, and H∞ approach is designed to achieve a certain tracking performance of closed-loop system. A quadratic stability approach, which allows separate treatment of parametric uncertainties, is used to reduce the conservatism of the conventional robust control approach. It can be also guaranteed that all signals in closed-loop system are bounded. The validity of the proposed control scheme is shown by computer simulation of a two-link robotic manipulator

Mechanisms of motor learning: by humans, for robots

Whenever we perform a movement and interact with objects in our environment, our central nervous system (CNS) adapts and controls the redundant system of muscles actuating our limbs to produce suitable forces and impedance for the interaction. As modern robots are increasingly used to interact with objects, humans and other robots, they too require to continuously adapt the interaction forces and impedance to the situation. This thesis investigated the motor mechanisms in humans through a series of technical developments and experiments, and utilized the result to implement biomimetic motor behaviours on a robot. Original tools were first developed, which enabled two novel motor imaging experiments using functional magnetic resonance imaging (fMRI). The first experiment investigated the neural correlates of force and impedance control to understand the control structure employed by the human brain. The second experiment developed a regressor free technique to detect dynamic changes in brain activations during learning, and applied this technique to investigate changes in neural activity during adaptation to force fields and visuomotor rotations. In parallel, a psychophysical experiment investigated motor optimization in humans in a task characterized by multiple error-effort optima. Finally a computational model derived from some of these results was implemented to exhibit human like control and adaptation of force, impedance and movement trajectory in a robot

High-performance series elastic actuation

textMobile legged robots have the potential to restructure many aspects of our lives in the near future. Whether for applications in household care, entertainment, or disaster response, these systems depend on high-performance actuators to improve their basic capabilities. The work presented here focuses on developing new high-performance actuators, specifically series elastic actuators, to address this need. We adopt a system-wide optimization approach, dealing with factors which influence performance at the levels of mechanical design, electrical system design, and control. Using this approach and based on a set of performance metrics, we produce an actuator, the UT-SEA, which achieves leading empirical results in terms of power-to-weight, force control, size, and system efficiency. We also develop general high-performance control techniques for both force- and position-controlled actuators, some of which were adopted for use on NASA-JSC's Valkyrie Humanoid robot and were used during DARPA's DRC Trials 2013 robotics competition.Electrical and Computer Engineerin

Integrated Trajectory-Tracking and Vibration Control of Kinematically-Constrained Warehousing Cable Robots

With the explosion of e-commerce in recent years, there is a strong desire for automated material handling solutions including warehousing robots. Cable driven parallel robots (CDPRs) are a relatively new concept which has yet to be explored for high-speed pick-&-place applications in the industry. Compared to rigid-link parallel robots, a CDPR possesses significant advantages including: large workspace, low moving inertia, high-speed motion, low power consumption, and incurring minimal maintenance cost. On the other hand, the main disadvantages of the CDPRs are the cable’s unilateral force exerting capability and low rigidity which is resulting in undesired vibrations of their moving platform. Kinematically-constrained CDPRs (KC-CDPRs) include a special class of CDPRs which provide a considerably higher level of stiffness in undesired degrees of freedom (DOFs) via connecting a set of constrained cables to the same actuator. Nevertheless, undesired vibrations of the moving platform are still their main problem which request more attention and investigation. Dynamic modeling, stiffness optimization, vibration and trajectory-tracking control, and stiffness-based trajectory-planning of redundant KC-CDPRs are studied in this thesis. As a new technique, we separate the moving platform’s vibration equations from its desired (nominal) equations of motion. The obtained vibration model forms a linear parametric variable (LPV) dynamic system which is based for the following contributions: 1) Proposing a new tension optimization approach to minimize undesired perturbations under external disturbances in a desired direction; and demonstrating the effectiveness of kinematically-constrained actuation method in vibration attenuation of CDPRs in undesired DOFs. 2) Providing the opportunity of using a wide class of well-established robust and optimal LPV-based control methods, such as H∞ control techniques, for trajectory-tracking control of CDPRs to minimize the effect of disturbances on the robot operation; and showing the effectiveness of kinematically-constrained actuation method in control design simplification of such robots. 3) Proposing the concept of stiffness-based trajectory-planning to find the stiffness-optimum geometry of trajectories for KC-CDPRs; and designing a time-optimal zero-to-zero continuous-jerk motion to track such trajectories. All the proposed concepts are developed for a generic KC-CDPR and verified via numerical analysis and experimental tests of a real planar warehousing KC-CDPR