CONTROL POR SEGUIMIENTO DE REFERENCIA PARA EL SISTEMA CAPSUBOT

En este documento se presenta una nueva técnica de control, en lazo cerrado, para el sistema Capsubot. La técnica combina el criterio de varianza mínima generalizada con el concepto de control por superficie deslizante en el dominio discreto. El objetivo de control es hacer seguimiento de la señal de referencia a través de la minimización de la varianza de la variable controlada, escogiéndose como señal de referencia una dinámica de velocidad adecuada de la masa interna del Capsubot, generándose así el movimiento adecuado del sistema Capsubot. El modelo no lineal del Capsubot es simplificado a un modelo lineal para poder aplicar la técnica de control propuesta

Modeling and Control of a Magnetic Drug Delivery System

Therapeutic operation risk has been reduced by the use of micro-robots, allowing highly invasive surgery to be replaced by low invasive surgery (LIS), which provides an effective tool even in previously inaccessible parts of the human body. LIS techniques help delivering drugs effectively via micro-carriers. The micro-carriers are divided into two groups: tethered devices, which are supported by internally supplied propulsion mechanism, and untethered devices. Remote actuation is the critical issue in micro-device navigation, especially through blood vessels. To achieve remote control within the cardiovascular system, magnetic propulsion offers an advantage over other proposed actuation methods. In the literature, most research has focused on micro-device structural design, while there is a lack of research into design and analysis of combined structure and control. As the main part, integrating the principle of electromagnetic induced force by feedback control design will lead to the desired automatic movement. An actuator configuration should thus first be designed to initiate the desired force. The design is basically defining the type and placement of a set of coils to achieve an operational goal. In this project, the magnetic actuation is initiated by a combination of four electromagnets and two sets of uniform coils. Preliminary studies on 2D navigation of a ferromagnetic particle are used to show the effect of actuator structure on controller performance. Accordingly, the performance of the four electromagnets combination is compared to the proposed augmented structure with uniform coils. The simulation results show the improved efficiency of the augmented structure. In more general cases, the arrangement and number of electromagnets are unknown and should be defined. An optimization method is suggested to find these variables when the working space is maximized. Finally, the problem of robust output regulation of the electromagnetic system driven by a linear exosystem, is also addressed in this project. The exosystem is assumed to be neutrally stable with unknown frequencies. The parallel connection of two controllers, a robust stabilizer and an internal model-based controller, is presented to eliminate the output error. In the latter one, an adaptation is used to tune the internal model frequencies such that a steady-state control is produced to maintain the output-zeroing condition. The robust regulation with a local domain of convergence is achieved for a special class of decomposable MIMO nonlinear minimum-phase system. The simulation results show the effectiveness and robustness of this method for the electromagnetic system when two different paths are considered

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