602 research outputs found

    Solving Optimal Control Problem Via Chebyshev Wavelet

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    Over the last four decades, optimal control problem are solved using direct and indirect methods. Direct methods are based on using polynomials to represent the optimal problem. Direct methods can be implemented using either discretization or parameterization. The proposed method in my thesis is considered as a direct method in which the optimal control problem is directly converted into a mathematical programming problem. A wavelet-based method is presented to solve the non-linear quadratic optimal control problem. The Chebyshev wavelets functions are used as the basis functions. The proposed method is also based on the iteration technique which replaces the nonlinear state equations by an equivalent sequence of linear time-varying state equations which is much easier to solve. Numerical examples are presented to show the effectiveness of the method, several optimal control problems were solved, and the simulation results show that the proposed method gives good and comparable results with some other methods

    A novel Chebyshev wavelet method for solving fractional-order optimal control problems

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    This thesis presents a numerical approach based on generalized fractional-order Chebyshev wavelets for solving fractional-order optimal control problems. The exact value of the Riemann– Liouville fractional integral operator of the generalized fractional-order Chebyshev wavelets is computed by applying the regularized beta function. We apply the given wavelets, the exact formula, and the collocation method to transform the studied problem into a new optimization problem. The convergence analysis of the proposed method is provided. The present method is extended for solving fractional-order, distributed-order, and variable-order optimal control problems. Illustrative examples are considered to show the advantage of this method in comparison with the existing methods in the literature

    Optimal control of systems with memory

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    The “Optimal Control of Systems with memory” is a PhD project that is borne from the collaboration between the Department of Mechanical and Aerospace Engineering of Sapienza University of Rome and CNR-INM the Institute for Marine Engineering of the National Research Council of Italy (ex INSEAN). This project is part of a larger EDA (European Defence Agency) project called ETLAT: Evaluation of State of the Art Thin Line Array Technology. ETLAT is aimed at improving the scientific and technical knowledge of potential performance of current Thin Line Towed Array (TLA) technologies (element sensors and arrays) in view of Underwater Surveillance applications. A towed sonar array has been widely employed as an important tool for naval defence, ocean exploitation and ocean research. Two main operative limitations costrain the TLA design such as: a fixed immersion depth and the stabilization of its horizontal trim. The system is composed by a towed vehicle and a towed line sonar array (TLA). The two subsystems are towed by a towing cable attached to the moving boat. The role of the vehicle is to guarantee a TLA’s constant depth of navigation and the reduction of the entire system oscillations. The vehicle is also called "depressor" and its motion generates memory effects that influence the proper operation of the TLA. The dynamic of underwater towed system is affected by memory effects induced by the fluid-structure interaction, namely: vortex shedding and added damping due to the presence of a free surface in the fluid. In time domain, memory effects are represented by convolution integral between special kernel functions and the state of the system. The mathematical formulation of the underwater system, implies the use of integral-differential equations in the time domain, that requires a nonstandard optimal control strategy. The goal of this PhD work is to developed a new optimal control strategy for mechanical systems affected by memory effects and described by integral-differential equations. The innovative control method presented in this thesis, is an extension of the Pontryagin optimal solution which is normally applied to differential equations. The control is based on the variational control theory implying a feedback formulation, via model predictive control. This work introduces a novel formulation for the control of the vehicle and cable oscillations that can include in the optimal control integral terms besides the more conventional differential ones. The innovative method produces very interesting results, that show how even widely applied control methods (LQR) fail, while the present formulation exhibits the advantage of the optimal control theory based on integral-differential equations of motion

    A theory of intense-field dynamic alignment and high harmonic generation from coherently rotating molecules and interpretation of intense-field ultrafast pump-probe experiments

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    A theory of ultra-fast pump-probe experiments proposed by us earlier [F.H.M. Faisal et al., Phys. Rev. Lett. 98, 143001 (2007) and F.H.M. Faisal and A. Abdurrouf, Phys. Rev. Lett. 100, 123005 (2008)] is developed here fully and applied to investigate the phenomena of dynamic alignment and high harmonic generation (HHG) from coherently rotating linear molecules. The theory provides essentially analytical results for the signals that allow us to investigate the simultaneous dependence of the HHG signals on the two externally available control parameters, namely, the relative angle between the polarizations, and the delay-time between the two pulses. It is applied to investigate the characteristics of high harmonic emission from nitrogen and oxygen molecules that have been observed experimentally in a number of laboratories. The results obtained both in the time-domain and in the frequency-domain are compared with the observed characteristics as well as directly with the data and are found to agree remarkably well. In addition we have predicted the existence of a "magic" polarization angle at which all modulations of the harmonic emission from nitrogen molecule changes to a steady emission at the harmonic frequency. Among other things we have also shown a correlation between the existence of the "magic" or critical polarization angles and the symmetry of the active molecular orbitals, that is deemed to be useful in connection with the "inverse problem" of molecular imaging from the HHG data.Comment: 31 pages, 22 figures, and 140 equation

    Analogue neuromorphic systems.

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    This thesis addresses a new area of science and technology, that of neuromorphic systems, namely the problems and prospects of analogue neuromorphic systems. The subject is subdivided into three chapters. Chapter 1 is an introduction. It formulates the oncoming problem of the creation of highly computationally costly systems of nonlinear information processing (such as artificial neural networks and artificial intelligence systems). It shows that an analogue technology could make a vital contribution to the creation such systems. The basic principles of creation of analogue neuromorphic systems are formulated. The importance will be emphasised of the principle of orthogonality for future highly efficient complex information processing systems. Chapter 2 reviews the basics of neural and neuromorphic systems and informs on the present situation in this field of research, including both experimental and theoretical knowledge gained up-to-date. The chapter provides the necessary background for correct interpretation of the results reported in Chapter 3 and for a realistic decision on the direction for future work. Chapter 3 describes my own experimental and computational results within the framework of the subject, obtained at De Montfort University. These include: the building of (i) Analogue Polynomial Approximator/lnterpolatoriExtrapolator, (ii) Synthesiser of orthogonal functions, (iii) analogue real-time video filter (performing the homomorphic filtration), (iv) Adaptive polynomial compensator of geometrical distortions of CRT- monitors, (v) analogue parallel-learning neural network (backpropagation algorithm). Thus, this thesis makes a dual contribution to the chosen field: it summarises the present knowledge on the possibility of utilising analogue technology in up-to-date and future computational systems, and it reports new results within the framework of the subject. The main conclusion is that due to its promising power characteristics, small sizes and high tolerance to degradation, the analogue neuromorphic systems will playa more and more important role in future computational systems (in particular in systems of artificial intelligence)

    Bifurcation and Chaos in Fractional-Order Systems

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    This book presents a collection of seven technical papers on fractional-order complex systems, especially chaotic systems with hidden attractors and symmetries, in the research front of the field, which will be beneficial for scientific researchers, graduate students, and technical professionals to study and apply. It is also suitable for teaching lectures and for seminars to use as a reference on related topics
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