67 research outputs found

    Virtual metrology for plasma etch processes.

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    Plasma processes can present dicult control challenges due to time-varying dynamics and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the use of mathematical models with accessible measurements from an operating process to estimate variables of interest. This thesis addresses the challenge of virtual metrology for plasma processes, with a particular focus on semiconductor plasma etch. Introductory material covering the essentials of plasma physics, plasma etching, plasma measurement techniques, and black-box modelling techniques is rst presented for readers not familiar with these subjects. A comprehensive literature review is then completed to detail the state of the art in modelling and VM research for plasma etch processes. To demonstrate the versatility of VM, a temperature monitoring system utilising a state-space model and Luenberger observer is designed for the variable specic impulse magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The temperature monitoring system uses optical emission spectroscopy (OES) measurements from the VASIMR engine plasma to correct temperature estimates in the presence of modelling error and inaccurate initial conditions. Temperature estimates within 2% of the real values are achieved using this scheme. An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate plasma etch rate for an industrial plasma etch process is presented. The VM models estimate etch rate using measurements from the processing tool and a plasma impedance monitor (PIM). A selection of modelling techniques are considered for VM modelling, and Gaussian process regression (GPR) is applied for the rst time for VM of plasma etch rate. Models with global and local scope are compared, and modelling schemes that attempt to cater for the etch process dynamics are proposed. GPR-based windowed models produce the most accurate estimates, achieving mean absolute percentage errors (MAPEs) of approximately 1:15%. The consistency of the results presented suggests that this level of accuracy represents the best accuracy achievable for the plasma etch system at the current frequency of metrology. Finally, a real-time VM and model predictive control (MPC) scheme for control of plasma electron density in an industrial etch chamber is designed and tested. The VM scheme uses PIM measurements to estimate electron density in real time. A predictive functional control (PFC) scheme is implemented to cater for a time delay in the VM system. The controller achieves time constants of less than one second, no overshoot, and excellent disturbance rejection properties. The PFC scheme is further expanded by adapting the internal model in the controller in real time in response to changes in the process operating point

    Advances and Trends in Mathematical Modelling, Control and Identification of Vibrating Systems

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    This book introduces novel results on mathematical modelling, parameter identification, and automatic control for a wide range of applications of mechanical, electric, and mechatronic systems, where undesirable oscillations or vibrations are manifested. The six chapters of the book written by experts from international scientific community cover a wide range of interesting research topics related to: algebraic identification of rotordynamic parameters in rotor-bearing system using finite element models; model predictive control for active automotive suspension systems by means of hydraulic actuators; model-free data-driven-based control for a Voltage Source Converter-based Static Synchronous Compensator to improve the dynamic power grid performance under transient scenarios; an exact elasto-dynamics theory for bending vibrations for a class of flexible structures; motion profile tracking control and vibrating disturbance suppression for quadrotor aerial vehicles using artificial neural networks and particle swarm optimization; and multiple adaptive controllers based on B-Spline artificial neural networks for regulation and attenuation of low frequency oscillations for large-scale power systems. The book is addressed for both academic and industrial researchers and practitioners, as well as for postgraduate and undergraduate engineering students and other experts in a wide variety of disciplines seeking to know more about the advances and trends in mathematical modelling, control and identification of engineering systems in which undesirable oscillations or vibrations could be presented during their operation

    A Doppler Lidar system with preview control for wind turbine load mitigation

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    This dissertation focuses on the development of a system for wind turbine in order to mitigate the load from unstable wind speed. The work is divided into 2 main parts: a cost efficient Doppler wind Lidar system is developed based on a short coherence length laser system in combine with multiple length delayline concept; a preview pitch control is developed based on the design of a combination of 2 degree of freedom (2-DOF) feedback / feedforward control with a model predictive control

    Nonlinear Time-Frequency Control Theory with Applications

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    Nonlinear control is an important subject drawing much attention. When a nonlinear system undergoes route-to-chaos, its response is naturally bounded in the time-domain while in the meantime becoming unstably broadband in the frequency-domain. Control scheme facilitated either in the time- or frequency-domain alone is insufficient in controlling route-to-chaos, where the corresponding response deteriorates in the time and frequency domains simultaneously. It is necessary to facilitate nonlinear control in both the time and frequency domains without obscuring or misinterpreting the true dynamics. The objective of the dissertation is to formulate a novel nonlinear control theory that addresses the fundamental characteristics inherent of all nonlinear systems undergoing route-to-chaos, one that requires no linearization or closed-form solution so that the genuine underlying features of the system being considered are preserved. The theory developed herein is able to identify the dynamic state of the system in real-time and restrain time-varying spectrum from becoming broadband. Applications of the theory are demonstrated using several engineering examples including the control of a non-stationary Duffing oscillator, a 1-DOF time-delayed milling model, a 2-DOF micro-milling system, unsynchronized chaotic circuits, and a friction-excited vibrating disk. Not subject to all the mathematical constraint conditions and assumptions upon which common nonlinear control theories are based and derived, the novel theory has its philosophical basis established in the simultaneous time-frequency control, on-line system identification, and feedforward adaptive control. It adopts multi-rate control, hence enabling control over nonstationary, nonlinear response with increasing bandwidth ? a physical condition oftentimes fails the contemporary control theories. The applicability of the theory to complex multi-input-multi-output (MIMO) systems without resorting to mathematical manipulation and extensive computation is demonstrated through the multi-variable control of a micro-milling system. The research is of a broad impact on the control of a wide range of nonlinear and chaotic systems. The implications of the nonlinear time-frequency control theory in cutting, micro-machining, communication security, and the mitigation of friction-induced vibrations are both significant and immediate

    Disturbance Suppression in PMSM Drives Physical Investigation, Algorithm Design and Implementation

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    The work of this Ph.D. focuses on the investigation of advanced control algorithms for the control of constant and periodic disturbances in Permanent Magnet Synchronous Machines (PMSMs), with the discussion of different methods for improving their negative influence on the machine current and the torque produced at the shaft. The discussion of the disturbances from a control perspective starts with the study of the parameter uncertainties effect on the dynamical performances of the current control and after the detailed analysis in the frequency domain, simple methods for improving the state-of-art decoupling network are given and validated on the testbench. Thanks to the feature of the introduced estimator, the transient behavior of the proposed strategy results in a consistent fast and precise performance. The control scheme allows to avoid the implementation of anti-windup mechanisms in the current control, making the overall controller less sensitive to parameter mismatch. Further, due to the low computational burden, the algorithm is suitable for low cost hardware. Subsequently, the more complex issue of periodic disturbances has been deeply investigated. The theoretical model proposed is validated by comparing the real measured torque with an estimation based on the recovered disturbance affecting the observed voltages and currents. The results are clearly acceptable and further, the experimental validation stresses out the fact that few terms have a predominant role in producing the harmonic disturbances, compared to the others. This consideration lets develop two strategies for suppressing the different harmonic orders present in the machine torque at low-speed operation. One strategy relies on on-line adaptive policies, where the estimated information is passed through a sequence of optimization algorithms with different objectives. In this context, hints on the guaranteed stability are also provided in order to confirm the practical feasibility of the algorithm. The other strategy is based on the off-line generation of some pre-determined functions, limiting the on-line burden to the computation of look-up tables. Both methods brought satisfactory results during the experimental validation, confirming the validity of our approximations made on the original complex model. Although the hardware testbed setup limited the opportunity to validate the methodologies at low speed, this represents a realistic scenario, in fact at higher speed the artificial injection of harmonics within the machine current becomes challenging due to the high electrical rotational speed and it brings more negative effects, in terms of losses and audible noise than benefits on the shaft stress, in fact, the machine inertia acts as a natural filter for the high frequencies harmonics. In summary, it can be said that the research work on advanced control algorithms for the disturbance suppression in PMSM drives has produced affordable and reliable methodologies, which can be of practical implementation for various industrial drives
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