Adaptive Control

Adaptive control has been a remarkable field for industrial and academic research since 1950s. Since more and more adaptive algorithms are applied in various control applications, it is becoming very important for practical implementation. As it can be confirmed from the increasing number of conferences and journals on adaptive control topics, it is certain that the adaptive control is a significant guidance for technology development.The authors the chapters in this book are professionals in their areas and their recent research results are presented in this book which will also provide new ideas for improved performance of various control application problems

From model-driven to data-driven : a review of hysteresis modeling in structural and mechanical systems

Hysteresis is a natural phenomenon that widely exists in structural and mechanical systems. The characteristics of structural hysteretic behaviors are complicated. Therefore, numerous methods have been developed to describe hysteresis. In this paper, a review of the available hysteretic modeling methods is carried out. Such methods are divided into: a) model-driven and b) datadriven methods. The model-driven method uses parameter identification to determine parameters. Three types of parametric models are introduced including polynomial models, differential based models, and operator based models. Four algorithms as least mean square error algorithm, Kalman filter algorithm, metaheuristic algorithms, and Bayesian estimation are presented to realize parameter identification. The data-driven method utilizes universal mathematical models to describe hysteretic behavior. Regression model, artificial neural network, least square support vector machine, and deep learning are introduced in turn as the classical data-driven methods. Model-data driven hybrid methods are also discussed to make up for the shortcomings of the two methods. Based on a multi-dimensional evaluation, the existing problems and open challenges of different hysteresis modeling methods are discussed. Some possible research directions about hysteresis description are given in the final section

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

DEVELOPING NEW ANALYTICAL AND NUMERICAL MODELS FOR MR FLUID DAMPERS AND THEIR APPLICATION TO SEISMIC DESIGN OF BUILDINGS

Magnetorheological (MR) and Electrorheological (ER) fluid dampers provide a fail-safe semi-active control mechanism for suppressing vibration response of structures as these smart fluids can change their apparent viscosity immediately under the influence of magnetic and electrical fields, respectively. MR based damping devices have recently received appropriate attention as they have less power demand, provide better dynamic range and are less sensitive to the temperature and external contaminants as compared to their ER counterparts. This thesis studies physics-based modeling of MR fluid dampers and their application in seismic design of buildings. In the first part of thesis, MR damper modeling and its related subject are studied, while in the second part of the thesis, application of MR dampers in tuned mass damper and bracing system is investigated. The existing models, namely the phenomenological models for simulating the behavior of MR and ER dampers rely on various parameters determined experimentally by the manufacturers for each damper configuration. It is of interest to develop mechanistic models of these dampers which can be applied to various configurations so that their fundamental characteristics can be studied to develop flexible design solutions for smart structures. This research presents a formulation for dynamics analysis of ER and MR fluid dampers in flow and mix mode configurations under harmonic and random excitations. The procedure employs the vorticity transport equation and the regularization function to deal with the unsteady flow and nonlinear behaviour of ER/MR fluid in general motion. Using the developed approach, the damping force of ER/MR damper can be evaluated under any type of excitations. While tuned mass dampers are found to be effective in suppressing vibration in a tall building, integrating them with semi-active MR based control system enables them to perform more efficiently under varying external excitations. To study the application of MR damper in tuned mass damper, a forty-storey tall steel-frame building assumed to be located in the Pacific Coast region of Canada (Vancouver), designed according to the relevant Canadian code and standard, has been studied with and without semi-active and passive tuned mass dampers. The response of the structure has been studied under a variety of ground motions with low, medium and high frequency contents to investigate the performance of the optimally designed semi-active MR based tuned mass damper in comparison to that of a passive tuned mass damper. It has been shown that the semi-active MR based system modifies structural response more effectively than the conventional passive tuned mass damper in both mitigation of the maximum displacement and reduction of the settling time of the building. Finally, the effectiveness of MR damper in structural bracing has been examined. Two steel building structures, five and twenty-storey building designed according to Canadian national building code, have been modeled using the finite element method. These building structures have been equipped with MR dampers in different floors appropriately based on the seismic floor-shear distribution. The governing equations of motion of the structures integrated with MR dampers have been cast into the state space representation for the implementation of the full state LQR combined with clipped optimal control strategies. The response of building structures under passive on and active controlled modes have been obtained for low, medium and high frequency content seismic records and compared