Predictive functional control based on an adaptive fuzzy model of a hybrid semi-batch reactor

In this paper a new approach to the control of a nonlinear, time-varying process is proposed. It is based on a recursive version of the fuzzy identification method and predictive functional control. First, the recursive fuzzy identification method is derived, after which it is used in connection with fuzzy predictive functional control to construct an adaptive fuzzy predictive functional controller. The adaptive FPFC is then tested on a nonlinear, time-varying, semi-batch reactor process and compared with the standard FPFC, which uses non-adaptive fuzzy model. The simulation results are promising; they indicate that the control of time-varying, nonlinear processes with the FPFC can be improved with the use of an adaptive fuzzy model. An improvement in reference tracking and disturbance rejection can be observed, but the main advantage is the reduced number of switchings between hot and cold water. This is an important improvement in the case of real applications.     

Two-way D algorithm for path planning and replanning

Inspired by the Witkowski’s algorithm, we introduce a novel path planning and replanning algorithm — the two-way D^∗ (TWD^∗) algorithm — based on a two-dimensional occupancy grid map of the environment. Unlike the Witkowski’s algorithm, which finds optimal paths only in binary occupancy grid maps, the TWD^∗ algorithm can find optimal paths in weighted occupancy grid maps. The optimal path found by the TWD^∗ algorithm is the shortest possible path for a given occupancy grid map of the environment. This path is more natural than the path found by the standard D^∗ algorithm as it consists of straight line segments with continuous headings. The TWD^∗ algorithm is tested and compared to the D^∗ and Witkowski’s algorithms by extensive simulations and experimentally on a Pioneer 3DX mobile robot equipped with a laser range finder.     

Aerodynamic optimization via multi-objective micro-genetic algorithm with range adaptation,knowledge-based reinitialization,crowding and ε-dominance

In this study, an optimization of the airfoil of a sailplane is carried out by a recently developed multi-objective genetic algorithm based on microevolution, containing crowding, range adaptation, knowledge-based reinitialization and ε-dominance. Its efficiency was tested on a set of test problems. The results are encouraging, suggesting that very small populations can be used effectively to solve real-world multi-objective optimization problems in many cases of interest.     

Convergence with a fixed regulator in lattice ordered groups and applications to MV-algebras

A convergence with a fixed regulator v in lattice ordered groups is applied to MV-algebras. For each Archimedean MV-algebra A there exists a v-Cauchy completion A ^* and it is uniquely determined up to isomorphisms over A. The relation between the Dedekind completion A ^∧ of A and A ^* is established. There is solved a question of the existence of the greatest v-Cauchy complete ideal of A.     

Estimation and setting starting values in ARMA algorithms

For the given observations set of the ARMA (autoregressive moving average) process, the likelihood function depends, not only on model parameters, but on the starting values of the input and output. Therefore, it is called theconditional likelihood function. Theunconditional likelihood function can be obtained in two ways. The first is to set the starting values to zero, as is often done, and the second is to set them to the properly estimated values. The difference between these two types of likelihood functions is significant when the given data sequence is short, and any of the zeros of the moving average part is close to the boundary of the unit circle.In this paper the direct method of starting value estimation and its application to two off-line ARMA estimation algorithms, the maximum likelihood (ML) algorithm and the iterative inverse filtering (ITIF) algorithm, is proposed. Experimental results prove both increased efficiency and stability of these algorithms.The importance of setting the starting values properly is also significant when the recursive algorithm, with previously estimated parameters, has to be restarted. The advantage of the proposed reinitialization method is shown on the recursive lattice algorithm working in the block mode.     

Conversion electron Mössbauer spectroscopy of the surface crystallization of the Fe75Co9B16 amorphous alloy

Using a new design of helium-methane gas-flow detector of conversion electrons for Mössbauer spectroscopy, non-uniform nucleation of the primary -Fe-Co phase on both contact and free surfaces of the Ar(+H₂) annealed amorphous Fe₇₅Co₉B₁₆ alloy was observed in its early crystallization stage. In this state the amount of crystalline phase on the contact ribbon side surpasses that on the free one by a factor of three, whereas no traces of volume crystallization were observed in the transmission spectra. By applying ion implantation to both ribbon surfaces, a slight reduction of the crystalline phase contribution was found. Magnetic domain structure observations were performed in order to evaluate the influence of surface crystallization on magnetic properties.     

Brooksʼ Theorem for generalized dart graphs

The well-known Brooks? Theorem says that each graph G of maximum degree $k?3$ is k-colorable unless $G=K_{k+1}$. We generalize this theorem by allowing higher degree vertices with prescribed types of neighborhood.     

Simulation of Fuzzy-Logic-Based Intelligent Wheelchair Control System

Fuzzy logic control system for an intelligent wheelchair aimed for assistance by the severely handicapped persons is presented in the paper. It is based on a computer simulation of wheelchair navigation, in which fuzzy logic enables control priority to smoothly alternate between manual and automatic control of the wheelchair in the vicinity of obstacles. The main purpose of designing and simulating this control approach is to improve the safety of a wheelchair in the presence of obstacles. To analyze the success of the wheelchair control, a dynamic model of the wheelchair, together with the models of distance sensors, has been developed using Lagrange analysis.