A training rule which guarantees finite-region stability for aclass of closed-loop neural-network control systems

A training method for a class of neural network controllers is presented which guarantees closed-loop system stability. The controllers are assumed to be nonlinear, feedforward, sampled-data, full-state regulators implemented as single hidden-layer neural networks. The controlled systems must be locally hermitian and observable. Stability of the closed-loop system is demonstrated by determining a Lyapunov function, which can be used to identify a finite stability region about the regulator point.     

Energy management of fuel cell/solar cell/supercapacitor hybrid power source

This study presents an original control algorithm for a hybrid energy system with a renewable energy source, namely, a polymer electrolyte membrane fuel cell (PEMFC) and a photovoltaic (PV) array. A single storage device, i.e., a supercapacitor (ultracapacitor) module, is in the proposed structure. The main weak point of fuel cells (FCs) is slow dynamics because the power slope is limited to prevent fuel starvation problems, improve performance and increase lifetime. The very fast power response and high specific power of a supercapacitor complements the slower power output of the main source to produce the compatibility and performance characteristics needed in a load. The energy in the system is balanced by d.c.-bus energy regulation (or indirect voltage regulation). A supercapacitor module functions by supplying energy to regulate the d.c.-bus energy. The fuel cell, as a slow dynamic source in this system, supplies energy to the supercapacitor module in order to keep it charged. The photovoltaic array assists the fuel cell during daytime. To verify the proposed principle, a hardware system is realized with analog circuits for the fuel cell, solar cell and supercapacitor current control loops, and with numerical calculation (dSPACE) for the energy control loops. Experimental results with small-scale devices, namely, a PEMFC (1200 W, 46 A) manufactured by the Ballard Power System Company, a photovoltaic array (800 W, 31 A) manufactured by the Ekarat Solar Company and a supercapacitor module (100 F, 32 V) manufactured by the Maxwell Technologies Company, illustrate the excellent energy-management scheme during load cycles.     

Photocatalytic performance of CdS nanomaterials for photodegradation of organic azo dyes under artificial visible light and natural solar light irradiation

The CdS semiconductors have been prepared at low temperature via catalyst-free chemical precipitation method without using any surfactant or capping agent. Either water or ethylene glycol, as a solvent, provides spherical CdS nanostructures with a comparable size of 117–121 nm. The molar ratio of Cd/S plays an important role in determining phase structure, morphology and photocatalytic performance of the prepared CdS nanostructures. Increasing molar ratio of S^2? results in not only mixed cubic-hexagonal phases but also low photocatalytic performance. CdS nanoparticles with good dispersibility prepared at Cd/S molar ratio of 1:1 shows high photocatytic efficiency of 95% toward photodegradation of reactive red azo dye (RR141) under visible light irradiation up to 240 min. The degradation efficiency of CdS nanoparticles also reaches 48% under natural solar light irradiation for 80 min. This work demonstrates the promising potential of CdS nanomaterials as photocatalysts for environmental remediation.     

The use of FEA and design of experiments to establish design guidelines for simple hydroformed parts

We present models to predict the protrusion height of “Tee-shaped” hydroformed parts, both because this information is of direct relevance to engineers attempting to build such parts and also to illustrate an advantageous process for developing design guidelines for tube hydroforming (THF) in general. A newly proposed design of experiments technique, Low Cost Response Surface Method (LCRSM), was utilized to facilitate the economical prediction and optimization of this height as a function of geometrical parameters subject to thinning of the wall thickness at the protrusion region. The same methodology is also proposed for the economical investigation of other geometries and conditions. As a result of this investigation, not only were known and expected trends of effect of parameters verified, but also numerical values within a practical range of parameters at certain conditions were obtained. In addition, interactions between factors were also revealed as predicted. Moreover, this information was gained from a substantially reduced number of finite element analysis (FEA) simulations via LCRSM compared to standard response surface method (RSM) or factorial techniques, avoiding costly physical experimentation.     

Performance Analysis for Asynchronous Requests in Wireless Networks with Multiple Packet Reception Capability

Wireless Personal Communications - Fifth generation (5G), the currently evolving communication standard, promises better performance in terms of capability, capacity, speed, latency, etc. than...     

Comments on "A training rule which guarantees finite-region stability for a class of closed-loop neural-network control systems" [with reply].

In the above paper by Kuntanapreeda-Fullmer (ibid., vol.7, no.3 (1996)) a training method for a neural-network control system which guarantees local closed-loop stability is proposed based on a Lyapunov function and a modified standard backpropagation training rule. In this letter, we show that the proof of Proposition 1 and the proposed stability condition as training constraints are not correct and therefore that the stability of the neural-network control system is not quite right. We suggest a modified version of the proposition with its proof and comment on another problem of the paper. In reply, Kuntanapreeda-Fullmer maintain the proof in the original paper is correct. Rather than identifying an error, they believe Park et al. have made a significant extension of the proof for application to stable online training networks.     

Crack initiation and propagation of galvanized coatings hot-dipped at 450 °C under bending loads

Crack initiation and propagation behaviors in the intermetallic layers of galvanized coatings subjected to bending loads are characterized and numerically simulated. Coating structure of galvanized steel prepared by hot dipping at 450 °C is a laminate composite consisting of δ, ζ, and η phases, with an infinitesimal layer between the coating and steel article speculatively representing a Γ phase. The specimens were deformed in a four-point bending configuration, and the evolution of cracks was investigated as a function of bending angles. Through-cracks were found to develop in the δ layer of the coatings after thermal cooling due to thermal stresses and propagate toward the outer surface under increments of bending loads. Finite element simulations of galvanized steels were subsequently developed with an initial crack tip located in the δ layer to determine the controlling parameters of the crack propagation and to assess the coatings' fracture parameter, critical far field stress, and stress distributions. The analysis highlights the enhancement of fracture resistance of the galvanized coatings owing to the presence of the ζ layer.     

Influence of Pre-Deformation on Springback Effect of Advanced High Strength Steel

In sheet metal forming process of automotive components,the springback effect is significant,in particular for Advanced High Strength Steels (AHSS),for example the Dual Phase (DP) steel.Most of construction parts of modern vehicles have very complex shapes and therefore multi-step procedures are necessary to form such a part.Steel sheets,which firstly undergo pre-deformation,can show considerable change in mechanical behavior during the forming process.However,at present there are limited sufficient data concerning pre-deformation effect on the springback available.In this work,a study of influences of different pre-strain levels on the springback of steel sheet made of AHSS materials has been carried out.The sheet specimens were firstly pre-stretched on a tensile testing machine and the pre-strain values were calculated based on the engineering strain.Furthermore,the steel sheets prepared parallel,transverse,and 45° to the rolling direction have been investigated.A modified U-shape forming was used to evaluate the degree of springback of the steel sheets under various conditions.In parallel,FE simulation of the U-shape forming was performed.Both isotropic model using stress-strain responses from tensile test of specimens with different directions and anisotropic Hill’s 48 model have been applied.The experimental results are compared with the sheet metal forming FE simulations.The primarily aim is to basically understand the springback mechanism by means of the simple models.And finally,conclusions with regard to the springback modeling will be presented.     

Robust synchronization of fractional-order unified chaotic systems via linear control

A new scheme for accomplishing synchronization between two fractional-order unified chaotic systems is proposed in this paper. The scheme does not require that the nonlinear dynamics of the synchronization error system must be eliminated. Moreover, the parameter of the systems does not have to be known. A controller is a linear feedback controller, which is simple in implementation. It is designed based on an LMI condition. The LMI condition guarantees that the synchronization between the slave system and the master system is achieved. Numerical simulations are performed to demonstrate the effectiveness of the proposed scheme.     

Output constrained IMC controllers in control systems of electromechanical actuators

Electromechanical actuators are widely used in many industrial applications. There are usually some constraints existing in a designed system. This paper proposes a simple method to design constrained controllers for electromechanical actuators. The controllers merge the ideas exploited in internal model control and model predictive control. They are designed using the standard control system structure with unity negative feedback. The structure of the controllers is relatively simple as well as the design process. The output constraint handling mechanism is based on prediction of the control plant behavior many time steps ahead. The mechanism increases control performance and safety of the control plant. The benefits offered by the proposed controllers have been demonstrated in real-life experiments carried out in control systems of two electromechanical actuators: a DC motor and an electrohydraulic actuator.