An affine combination of two LMS adaptive filters - Transient mean-square analysis

This paper studies the statistical behavior of an affine combination of the outputs of two LMS adaptive filters that simultaneously adapt using the same white Gaussian inputs. The purpose of the combination is to obtain an LMS adaptive filter with fast convergence and small steady-state mean-square deviation (MSD). The linear combination studied is a generalization of the convex combination, in which the combination factor $\lambda(n)$ is restricted to the interval $(0,1)$. The viewpoint is taken that each of the two filters produces dependent estimates of the unknown channel. Thus, there exists a sequence of optimal affine combining coefficients which minimizes the MSE. First, the optimal unrealizable affine combiner is studied and provides the best possible performance for this class. Then two new schemes are proposed for practical applications. The mean-square performances are analyzed and validated by Monte Carlo simulations. With proper design, the two practical schemes yield an overall MSD that is usually less than the MSD's of either filter

Modelling and optimisation of solar voltaic system using fuzzy logic

There is considerable increase in residential solar grid connected installations with many advantages offered by solar energy. As more solar panels are connected to grid, the Solar Inverter between solar panels and grid have to perform at optimum levels. Modern Inverters consist of DC-DC Converter and DC-AC Inverter. One problem associated with Inverter design is voltage fluctuation, this defect lies in the DC-DC converter Maximum power tracking (MPPT) algorithms responsible for extracting maximum power from the solar panels. The defect is due to large sampling number required for conventional MPPT algorithm. This thesis has proposed a new MPPT algorithm based on Mamdani Fuzzy logic. In research we use 5 parameter one diode model for solar cell modelling. The P-V/I-V characteristics curve is generated. The P-V characteristics curves sectioned and input membership and output membership functions is created. And unique fuzzy rules is used to optimize fuzzy controller output. Mamdani Fuzzy logic algorithm is compared to traditional PI controller hill climbing method. When small sampling number is used hill climbing method response is slow and good at tracking. When big sampling number is used hill climbing method response is fast and not good at tracking. The voltage also fluctuates when sampling number is big. Fuzzy logic provides a compromised solution with best response time and moderate tracking accuracy compared to hill climbing method. Fuzzy Logic based DC-DC converter together with PLL and Recursive Discrete Fourier Transform (RDFT) DC-AC inverter synchronization algorithm is employed and simulated in matlab. The MPPT simulation is conducted for a realistic 2.5KW solar panels in a 8 x 2 Matrix. In addition the MPPT algorithm is analyzed to see if it performs under power quality and voltage level tolerance of utility grid requirements. The Fuzzy Logic MPPT is excellent at tracking power. When temperature is fixed and irradiance is varied, the maximum tracking error is 5.2% in all scenarios with one exception. When irradiance is fixed and temperature varied, the maximum tracking error is 1.98%. Furthermore the Fuzzy Logic MPPT meets the power quality and voltage level tolerance requirements of utility grid for irradiance over 600 W/m2. Power quality and voltage level tolerance requirements for irradiance under 600 W/m2 is not critical as this is outside twilight conditions. Out of all the Synchronization algorithm identified in this Thesis, RDFT achieves synchronization very quickly and in addition it suppresses harmonics and noise. The possibility of future study to extend MPPT is also briefly discussed. The extension of future study is using Takagi-Sugeno fuzzy logic. Takagi-Sugeno uses more sophisticated inference and rule evaluation mathematics

An interim report of research on stochastic and adaptive systems

Interim report."March 20, 1981."Includes bibliographies.Air Force Office of Scientific Research Grant AFOSR-77-3281Cby Michael Athans, Sanjoy K. Mitter, Lena Valavani

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available