Martin B. Brilliant. / "March 3, 1958." Based on a thesis submitted to M.I.T. Dept. of Electrical Engineering, January 13, 1958. / Bibliography: p. 58. / Army Signal Corps Contract DA36-039-sc-78101. Dept. of the Army Task 3-99-06-108 and Project 3-99-00-100.

Thesis (M. Phil.)--University of Hong Kong, 2006. / Also available in print.

Magneto-rheological damper is a nonlinear system. In this case study, system has been identified using Neural Network tool. Optimization between number of neurons in the hidden layer and number of epochs has been achieved and discussed by using multilayer perceptron Neural Network.

While nonlinear behavior in mechanical systems typically degrades the behavior and performance the devices, the presence of system nonlinearities can sometimes improve the quality of the system. A reason for avoiding nonlinearities within a device is the difficulty in controlling the device due to the effects of the nonlinearities on system behavior. However, careful analysis of nonlinear systems can allow for one to take advantage of the nonlinear behavior to improve system performance. The objective of this thesis is to exploit the use of nonlinearities to enhance system performance, specifically the sensitivity of a micromachined magnetic sensor. A device design will be presented that is similar to a prototype that has been fabricated by a student within the Electrical and Computer Engineering Department at Georgia Tech. The operating principle of the device is that changes in the orientation and the strength of an external magnetic field will result in changes in the dynamic behavior of the sensor. While previous device provided a proof of the design concept, it was unable to achieve a sensitivity that would allow for its use as a compass. Improvements in the sensitivity of the sensor are achieved through the modeling and optimization of the magnetic sensor. The optimization and redesign of the magnetic sensor will improve the quality of the device and provide another step towards sensor commercialization. A new design that incorporates the use of variable force comb drives will be proposed that will further improve the sensitivity of the device by modifying the dynamic behavior of the sensor. Another approach that is presented to exploit the nonlinear behavior of the magnetic sensor involves a frequency detection scheme that uses nonlinear vibrations to characterize sensor behavior. Some benefits of this detection technique are that it is insensitive to noise in the vibration of the sensor and is also independent of the damping present within the system. In addition, the implementation of this sensing technique can be readily applied to variety of sensors types without the redesign of a system or the addition of complex components such as vacuum packaging or signal processing electronics.

This dissertation deals with smooth feedback stabilization of control-affine systems via Interconnection and Damping Assignment - Passivity-Based Control (IDA-PBC). The IDA-PBC methodology is a feedback control design technique that aims to establish or manipulate a port-Hamiltonian structure of the closed-loop system. For a mechanical control system, a port-Hamiltonian system is a natural description of the dynamics, and several effective controller designs have been presented for this class of systems. In other fields of engineering, the development of such controller design is an active area of research. In particular, applications of IDA-PBC techniques prove to be difficult in practice for process control applications where the concept of energy is usually ill-defined. This thesis seeks to extend the application of the IDA-PBC methodology beyond mechanical control systems. This is achieved by following three directions of research. First, we establish conditions under which a port-Hamiltonian system can be written as a feedback interconnection of two port-Hamiltonian system. We identify such an interconnection structure for linear control systems based on their intrinsic properties. Second, as observed in application of IDA-PBC to non-mechanical systems, several additional assumptions on the structure of the desired port-Hamiltonian system can effectively reduce the complexity of the matching problem. We establish a unified approach that considers these additional assumptions. Third, we connect the matching problem to the classical feedback equivalence approach. We show that feedback equivalence between control-affine systems can be employed to construct some feasible interconnection and damping structures. / Thesis (Ph.D, Chemical Engineering) -- Queen's University, 2011-01-31 12:59:56.828

The problem of parameter and state estimation of a class of nonlinear systems is addressed. An adaptive identifier and observer are used to estimate the parameters and the state variables simultaneously. The proposed method is derived using a new formulation. Uncertainty sets are defined for the parameters and a set of auxiliary variables for the state variables. An algorithm is developed to update these sets using the available information. The algorithm proposed guarantees the convergence of parameters and the state variables to their true value. In addition to its application in difficult estimation problems, the algorithm has also been adapted to handle fault detection problems. The technique of estimation is applied to two broad classes of systems. The first involves a class of continuous time nonlinear systems subject to bounded unknown exogenous disturbance with constant parameters. Using the proposed set-based adaptive estimation, the parameters are updated only when an improvement in the precision of the parameter estimates can be guaranteed. The formulation provides robustness to parameter estimation error and bounded disturbance. The parameter uncertainty set and the uncertainty associated with an auxiliary variable is updated such that the set is guaranteed to contain the unknown true values. The second class of system considered is a class of nonlinear systems with timevarying parameters. Using a generalization of the set-based adaptive estimation technique proposed, the estimates of the parameters and state are updated to guarantee convergence to a neighborhood of their true value. The algorithm proposed can also be extended to detect the fault in the system, injected by drastic change in the time-varying parameter values. To study the practical applicability of the developed method, the estimation of state variables and time-varying parameters of salt in a stirred tank process has been performed. The results of the experimental application demonstrate the ability of the proposed techniques to estimate the state variables and time-varying parameters of an uncertain practical system. / Thesis (Master, Chemical Engineering) -- Queen's University, 2011-10-31 22:04:58.762

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The non-local stabilization of nonlinear systems by output feedback is a challenging problem that remains the subject of continuing investigation in control theory. In this thesis we develop two globally asymptotically stabilizing output feedback algorithms for multivariable nonlinear systems. Our first result is an extension a well-known output feedback method to a class of nonlinear systems whose dynamics can be written as a collection of subsystems that are dynamically coupled through output-dependent nonlinear terms. We show that this method must be modified to accommodate the dynamic coupling by introducing additional nonlinear damping terms into each control input. Our second contribution involves the application of observer backstepping to systems in a restricted block-triangular observer form. In this form, the nonlinearities entering each subsystem are allowed to depend on the output associated with the subsystem, and all upper subsystem states, including unmeasured ones. The proposed algorithm is demonstrated on a magnetically levitated ball. / Controls

Thesis (PhD)--University of South Australia, 1999