Combined Time and Frequency Domain Approaches to the Operational Identification of Vehicle Suspension Systems

This research is an investigation into the identification of vehicle suspension systems from measured operational data. Methods of identifying unknown parameter values in dynamic models, from experimental data, are of considerable interest in practice. Much of the focus has been on the identification of mechanical systems when both force and response data are obtainable. In recent years a number of researchers have turned their focus to the identification of mechanical systems in the absence of a measured input force. This work presents a combined time and frequency domain approach to the identification of vehicle suspension parameters using operational measurements. An end– to–end approach is taken to the problem which involves a combination of focused experimental design, well established force–response testing methods and vehicle suspension experimental testing and simulation. A quarter car suspension test rig is designed and built to facilitate experimental suspension system testing. A novel shock absorber force measurement set–up is developed allowing the measurement of shock absorber force under both isolated and operational testing conditions. The quarter car rig is first disassembled and its major components identified in isolation using traditional force–response testing methods. This forms the basis for the development of an accurate nonlinear simulation of the quarter car test rig. A comprehensive understanding of the quarter car experimental test rig dynamics is obtained before operational identification is implemented. This provides a means of validating the suspension parameters obtained using operational testing methods. A new approach to the operational identification of suspension system parameters is developed. The approach is first developed under controlled simulated conditions before being applied to the operational identification of the quarter car experimental test rig. A combination of time and frequency domain methods are used to extract sprung mass, linear stiffness and nonlinear damping model parameters from the quarter car experimental test rig. Component parameters identified under operational conditions show excellent agreement with those identified under isolated laboratory conditions

Magneto-Rheological Actuators for Human-Safe Robots: Modeling, Control, and Implementation

In recent years, research on physical human-robot interaction has received considerable attention. Research on this subject has led to the study of new control and actuation mechanisms for robots in order to achieve intrinsic safety. Naturally, intrinsic safety is only achievable in kinematic structures that exhibit low output impedance. Existing solutions for reducing impedance are commonly obtained at the expense of reduced performance, or significant increase in mechanical complexity. Achieving high performance while guaranteeing safety seems to be a challenging goal that necessitates new actuation technologies in future generations of human-safe robots. In this study, a novel two degrees-of-freedom safe manipulator is presented. The manipulator uses magneto-rheological fluid-based actuators. Magneto-rheological actuators offer low inertia-to-torque and mass-to-torque ratios which support their applications in human-friendly actuation. As a key element in the design of the manipulator, bi-directional actuation is attained by antagonistically coupling MR actuators at the joints. Antagonistically coupled MR actuators at the joints allow using a single motor to drive multiple joints. The motor is located at the base of the manipulator in order to further reduce the overall weight of the robot. Due to the unique characteristic of MR actuators, intrinsically safe actuation is achieved without compromising high quality actuation. Despite these advantages, modeling and control of MR actuators present some challenges. The antagonistic configuration of MR actuators may result in limit cycles in some cases when the actuator operates in the position control loop. To study the possibility of limit cycles, describing function method is employed to obtain the conditions under which limit cycles may occur in the operation of the system. Moreover, a connection between the amplitude and the frequency of the potential limit cycles and the system parameters is established to provide an insight into the design of the actuator as well as the controller. MR actuators require magnetic fields to control their output torques. The application of magnetic field however introduces hysteresis in the behaviors of MR actuators. To this effect, an adaptive model is developed to estimate the hysteretic behavior of the actuator. The effectiveness of the model is evaluated by comparing its results with those obtained using the Preisach model. These results are then extended to an adaptive control scheme in order to compensate for the effect of hysteresis. In both modeling and control, stability of proposed schemes are evaluated using Lyapunov method, and the effectiveness of the proposed methods are validated with experimental results

Modeling and Control of Piezoelectric Actuators

Piezoelectric actuators (PEAs) utilize the inverse piezoelectric effect to generate fine displacement with a resolution down to sub-nanometers and as such, they have been widely used in various micro- and nanopositioning applications. However, the modeling and control of PEAs have proven to be challenging tasks. The main difficulties lie in the existence of various nonlinear or difficult-to-model effects in PEAs, such as hysteresis, creep, and distributive vibration dynamics. Such effects can seriously degrade the PEA tracking control performances or even lead to instability. This raises a great need to model and control PEAs for improved performance. This research is aimed at developing novel models for PEAs and on this basis, developing model-based control schemes for the PEA tracking control taking into account the aforementioned nonlinear effects. In the first part of this research, a model of a PEA for the effects of hysteresis, creep, and vibration dynamics was developed. Notably, the widely-used Preisach hysteresis model cannot represent the one-sided hysteresis of PEAs. To overcome this shortcoming, a rate-independent hysteresis model based on a novel hysteresis operator modified from the Preisach hysteresis operator was developed, which was then integrated with the models of creep and vibration dynamics to form a comprehensive model for PEAs. For its validation, experiments were carried out on a commercially-available PEA and the results obtained agreed with those from model simulations. By taking into account the linear dynamics and hysteretic behavior of the PEA as well as the presliding friction between the moveable platform and the end-effector, a model of the piezoelectric-driven stick-slip (PDSS) actuator was also developed in the first part of the research. The effectiveness of the developed model was illustrated by the experiments on the PDSS actuator prototyped in the author's lab. In the second part of the research, control schemes were developed based on the aforementioned PEA models for tracking control of PEAs. Firstly, a novel PID-based sliding mode (PIDSM) controller was developed. The rational behind the use of a sliding mode (SM) control is that the SM control can effectively suppress the effects of matched uncertainties, while the PEA hysteresis, creep, and external load can be represented by a lumped matched uncertainty based on the developed model. To solve the chattering and steady-state problems, associated with the ideal SM control and the SM control with boundary layer (SMCBL), the novel PIDSM control developed in the present study replaces the switching control term in the ideal SM control schemes with a PID regulator. Experiments were carried out on a commercially-available PEA and the results obtained illustrate the effectiveness of the PIDSM controller, and its superiorities over other schemes of PID control, ideal SM control, and the SMCBL in terms of steady state error elimination, chattering suppression, and tracking error suppression. Secondly, a PIDSM observer was also developed based on the model of PEAs to provide the PIDSM controller with state estimates of the PEA. And the PIDSM controller and the PIDSM observer were combined to form an integrated control scheme (PIDSM observer-controller or PIDSMOC) for PEAs. The effectiveness of the PIDSM observer and the PIDSMOC were also validated experimentally. The superiority of the PIDSMOC over the PIDSM controller with σ-β filter control scheme was also analyzed and demonstrated experimentally. The significance of this research lies in the development of novel models for PEAs and PDSS actuators, which can be of great help in the design and control of such actuators. Also, the development of the PIDSM controller, the PIDSM observer, and their integrated form, i.e., PIDSMOC, enables the improved performance of tracking control of PEAs with the presence of various nonlinear or difficult-to-model effects

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

Bio-inspired robotic control in underactuation: principles for energy efficacy, dynamic compliance interactions and adaptability.

Biological systems achieve energy efficient and adaptive behaviours through extensive autologous and exogenous compliant interactions. Active dynamic compliances are created and enhanced from musculoskeletal system (joint-space) to external environment (task-space) amongst the underactuated motions. Underactuated systems with viscoelastic property are similar to these biological systems, in that their self-organisation and overall tasks must be achieved by coordinating the subsystems and dynamically interacting with the environment. One important question to raise is: How can we design control systems to achieve efficient locomotion, while adapt to dynamic conditions as the living systems do? In this thesis, a trajectory planning algorithm is developed for underactuated microrobotic systems with bio-inspired self-propulsion and viscoelastic property to achieve synchronized motion in an energy efficient, adaptive and analysable manner. The geometry of the state space of the systems is explicitly utilized, such that a synchronization of the generalized coordinates is achieved in terms of geometric relations along the desired motion trajectory. As a result, the internal dynamics complexity is sufficiently reduced, the dynamic couplings are explicitly characterised, and then the underactuated dynamics are projected onto a hyper-manifold. Following such a reduction and characterization, we arrive at mappings of system compliance and integrable second-order dynamics with the passive degrees of freedom. As such, the issue of trajectory planning is converted into convenient nonlinear geometric analysis and optimal trajectory parameterization. Solutions of the reduced dynamics and the geometric relations can be obtained through an optimal motion trajectory generator. Theoretical background of the proposed approach is presented with rigorous analysis and developed in detail for a particular example. Experimental studies are conducted to verify the effectiveness of the proposed method. Towards compliance interactions with the environment, accurate modelling or prediction of nonlinear friction forces is a nontrivial whilst challenging task. Frictional instabilities are typically required to be eliminated or compensated through efficiently designed controllers. In this work, a prediction and analysis framework is designed for the self-propelled vibro-driven system, whose locomotion greatly relies on the dynamic interactions with the nonlinear frictions. This thesis proposes a combined physics-based and analytical-based approach, in a manner that non-reversible characteristic for static friction, presliding as well as pure sliding regimes are revealed, and the frictional limit boundaries are identified. Nonlinear dynamic analysis and simulation results demonstrate good captions of experimentally observed frictional characteristics, quenching of friction-induced vibrations and satisfaction of energy requirements. The thesis also performs elaborative studies on trajectory tracking. Control schemes are designed and extended for a class of underactuated systems with concrete considerations on uncertainties and disturbances. They include a collocated partial feedback control scheme, and an adaptive variable structure control scheme with an elaborately designed auxiliary control variable. Generically, adaptive control schemes using neural networks are designed to ensure trajectory tracking. Theoretical background of these methods is presented with rigorous analysis and developed in detail for particular examples. The schemes promote the utilization of linear filters in the control input to improve the system robustness. Asymptotic stability and convergence of time-varying reference trajectories for the system dynamics are shown by means of Lyapunov synthesis

Modeling and controller design of an industrial hydraulic actuator system in the presence of friction and internal leakage

This paper presents a robust controller scheme and its capabilities to control the position tracking performance of an electro-hydraulic actuator system. Sliding mode control with fixed and varying boundary layer is proposed in the scheme. It is aimed to compensate nonlinearities and uncertainties caused by the presence of friction and internal leakage. Its capabilities are verified through simulations in Matlab Simulink environment. The friction was represented by the LuGre model and the internal leakage was assumed to change. The results indicate that the scheme successfully improves the robustness and the tracking accuracy of the system. This improvement offers a significant contribution in the control of modern equipment positioning applications