Modeling the Combining Site of the Human Asialoglycoprotein Receptor

A model for the carbohydrate recognition domain (CRD) and combining site of the human asialoglycoprotein (ASGP) receptor has been computed on the basis of the close sequence homology with the mannose-binding lectin (MBP), whose three-dimensional structure in complex with a ligand has been determined by crystallographic methods (Weis, W.I.; Drickamer, K.; Hendrickson, W.A. Nature 1992, 360: 127). Within the limitations of modeling methods, the model is compatible with data on ligand binding of the family C-type lectins, of which the MBP and the ASGP receptor are members. The model derived can serve as a guide for designing site-directed mutagenesis experiments in order to further elucidate the origins of specificity of the ASGP receptor toward galactose. In particular, the model focuses attention on the possible role of position 207 (MBP sequence numbering) in promoting galactose binding.     

A Two-Layer Robot Controller Design Using Evolutionary Algorithms

The results obtained by a rule-based proportional, integral, derivative (PID) precompensator controller applied to a two-joint manipulator are discussed. The end effector is made to follow a specified trajectory obtained from the inverse kinematics by an appropriate design of a fuzzy control law. The desired trajectory is determined by the values of the joint variables and the structural kinematics parameters of the manipulator. The performance of the PID controller is exploited here to build a fuzzy precompensator that will enhance the conventional PID and to obtain better performances and results. The fuzzy rule base of the precompensator designed is found by associating two evolutionary algorithms that search for the optimal solution.     

State observer based robust adaptive fuzzy controller for nonlinear uncertain and perturbed systems

A robust adaptive fuzzy controller, based on a state observer, for a nonlinear uncertain and perturbed system is presented. The state observer is introduced to resolve the problem of the unavailability of the state variables. Two control signals are added to a basic state feedback control law, deduced from a nominal model, to guarantee the tracking performance in the presence of structural uncertainties and external disturbances. The first control signal is computed from an adaptive fuzzy system and eliminates the effect of structural uncertainties and estimation errors. Updating the adjustable parameters is ensured by a PID law to obtain a fast convergence. Robustness of the closed-loop system is guaranteed by an H infinity supervisor computed from a Riccati type equation. Simulation example is presented to show the efficiency of the proposed method.     

Partial Fraction Decomposition and Correlation Sequence in 2D Systems

In this paper, results of the one-dimensional (1D) digital filtering are extended to the two-dimensional (2D) case. It introduces a technique and an algorithm for the computation of the product H(z₁,z₂)H(z₁⁻¹,z₂⁻¹). The technique is used to find a minimum phase transfer function of a 2D system such that the previous product matches a given correlation sequence. The algorithm requires less arithmetic operations than the traditional methods. The former is based on a matrix formulation of the product, which is used to investigate the 2D partial fraction decomposition (PFD) and stability.     

Control for Underactuated Systems Using Sliding Mode Observer

In this work, first we estimate all the system’s state vector, with guarantied precision, for a category of second order underactuated mechanical systems (UMS), exploiting the triangular observer (TO) model that suits to the structure of these systems. Then we propose a sliding mode controller (SMC). The latter uses the estimated states given by the observer. The underactuated system is decomposed into two subsystems, where the sliding surface is constructed in two levels for each subsystem. The proposed controller guaranties the tracking performances, with minimization of chattering phenomenon, due to the constructed observer, even for system with uncertainties. Simulation results show the effectiveness of this strategy of control.

     

Author Index

Authors Index

Author Index     

Investigations into the copper chromite particle size effect on the combustion characteristics of poly(vinyl-chloride) plastisol propellants

Journal of Mechanical Science and Technology - The investigation of the possibility to optimize ballistic behavior and consequently to obtain better performance without affecting the cost and...     

Fuzzy model reference adaptive control

This paper investigates a fuzzy model reference adaptive controller (FMRAC) for continuous-time multiple-input-multiple-output (MIMO) nonlinear systems. The proposed adaptive scheme uses a Takagi-Seguno (TS) fuzzy adaptive system, which allows for the inclusion of a priori information in terms of qualitative knowledge about the plant operating points or analytical regulators (e.g., state feedback) for those operating points. A proportional-integral update law is used to obtain a fast parameters adaptation. Stability and robustness of this adaptive scheme are established using Lyapunov stability tools. The simulation results, for a two-link robot, confirm the performance of the proposed approach.     

Interval Arithmetic and Its Application to Electrical Circuits

Interval arithmetic is an elegant tool for practical work with inequalities, approximate numbers, error bounds, and more generally with certain convex and bounded sets. In this section we give a number of simple examples showing where intervals and ranges of functions over intervals arise naturally. Interval mathematics is a generalization in which interval numbers replace real numbers, interval arithmetic replaces real arithmetic, and interval analysis replaces real analysis. Interval is limited by two bounds： lower bound and upper bound. The present paper introduces some of the basic notions and techniques from interval analysis needed in the sequel for presenting various uses of interval analysis in electric circuit theory and its applications. In this article we address the representation of uncertain and imprecise information, the interval arithmetic and its application to electrical circuits.