An agent-based system for bilateral contracts of energy

In this paper, an agent-based system for bilateral contracts of energy is proposed. The generating companies submit their offers to the demand companies. The demand companies also submit their bids to the generators. Each load or generator’s agent wants to match with an opponent, which offers the most valuable proposal. However, the problem of simultaneous decision-making causes decision conflicts among the agents. To overcome this conflict, we assume loads as the leaders and generators as the followers. We use Stackelberg game to match the seller and buyer agents. The negotiation process between a buyer and its potential seller will determine the power price between them. This process is carried out through a proposed combined time-behavioral protocol (TBP). With negligible changes in around the agreed price, this protocol can reduce the negotiation time considerably. After successful negotiation, the seller and buyer agents could sign a bilateral contract of energy if the market conditions allow it. The applicability of the proposed method is illustrated through a case study.     

A Nonlinear Adaptive Resilient Observer Design for a Class of Lipschitz Systems Using LMI

This paper addresses the parameter and state estimation problem in the presence of the observer gain perturbations for Lipschitz systems that are linear in the unknown parameters and nonlinear in the states. A nonlinear adaptive resilient observer is designed, and its stability conditions based on the Lyapunov technique are derived. The gain for this observer is derived systematically using the linear matrix inequality approach. A numerical example and a physical setup are provided to show the effectiveness of the proposed method.     

Building a production planning process with an approach based on CIMOSA and workflow management systems

Nowadays, one of the major challenges for enterprises is to stay competitive in today's changing market environment. This can be supported by business process models which on one hand are consistent and adequate (requirement #1), and on the other hand can be enacted and operated in an easy, fast, straightforward and integrated way (requirement #2). The CIMOSA architecture provides the basis for business process modelling to fulfil both of the above requirements. It supports the creation of consistent process models and allows to identify almost all the information required for the development of a workflow model. These models can be implemented using one of the commercial workflow management systems. In this paper we present the methodology based on the CIMOSA architecture that we have developed to build a workflow model in ©Lotus Notes for the forecasting and production planning processes in a tiles manufacturing enterprise. The CIMOSA approach has also been used to design the necessary software applications for processing the information of the resulting workflow system.     

Curing behavior,thermal, and mechanical properties of epoxy/polyamic acid based on 4,4′-biphtalic dianhydride and 3,3′-dihydroxybenzidine

Different synthesis routes were studied to obtain 4,4′-biphtalic dianhydride/3,3′-dihydroxybenzidine polyimide precursors (polyamic acids [PAAs]) with different inherent viscosities (IVs) and imidization degrees. The synthesized PAAs were introduced as a thermoplastic modifier into an epoxy (EP) resin. Different loadings of PAA were used to investigate the curing behavior, heat resistance, and mechanical properties. The onset curing temperature of the EP by adding 20 wt% PAA diminished by around 15°C. Thermogravimetric analysis revealed that the initial and 10 wt% weight loss temperature for EP with 5 wt% PAA improved by 13°C and 7.7%, respectively. Further, the results of tensile and plane-strain fracture toughness tests indicated that as the amount of PAA increased, the strength and toughness of EP decreased. These improvements were due to the high heat resistance and mechanical properties of PI precursor introduced into the EP, which formed a three-dimensional structure together. The interlaminar shear strength (ILSS) of the system experienced a reduction; however, after adding 2 phr nanosilica to the system containing PAA with average IV and imidization degree, ILSS showed 4.4% increment.     

Optimized and decentralized pulse control of seismically excited steel structures

The idea of decomposing a centralized complicated system into several synchronous decentralized subsystems has been resulted into the development of decentralized control methods. In this study, a decentralized pulse control scheme is presented based on the theory of Inclusion Principle for steel systems comprising a multi-overlapping structure. The proposed control algorithm is basically an active control system that generates corrective pulses at each moment when the displacement or acceleration exceeds the predefined threshold. In order to evaluate the performance of proposed control system, a numerical study is conducted. The control system is implemented for two linear structural models of five- and twenty-story steel buildings. An optimization algorithm (PSO) is also used to determine the locations of required control inputs in the 20-story building. The results show that the proposed algorithm can substantially mitigate the structural response under different earthquake records (for 5-story model) and different subsystem configurations (for 20-story model).     

Fuzzy Sarsa Learning and the proof of existence of its stationary points

This paper provides a new Fuzzy Reinforcement Learning (FRL) algorithm based on critic‐only architecture. The proposed algorithm, called Fuzzy Sarsa Learning (FSL), tunes the parameters of conclusion parts of the Fuzzy Inference System (FIS) online. Our FSL is based on Sarsa, which approximates the Action Value Function (AVF) and is an on‐policy method. In each rule, actions are selected according to the proposed modified Softmax action selection so that the final inferred action selection probability in FSL is equivalent to the standard Softmax formula. We prove the existence of fixed points for the proposed Approximate Action Value Iteration (AAVI). Then, we show that FSL satisfies the necessary conditions that guarantee the existence of stationary points for it, which coincide with the fixed points of the AAVI. We prove that the weight vector of FSL with stationary action selection policy converges to a unique value. We also compare by simulation the performance of FSL and Fuzzy Q‐Learning (FQL) in terms of learning speed, and action quality. Moreover, we show by another example the convergence of FSL and the divergence of FQL when both algorithms use a stationary policy. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Cournot games with linear regression expectations in oligopolistic markets

In this paper, a Cournot game in an oligopolistic market with incomplete information is considered. The market consists of some producers that compete for getting higher payoffs. For optimal decision making, each player needs to estimate its rivals’ behaviors. This estimation is carried out using linear regression and recursive weighted least-squares method. As the information of each player about its rivals increases during the game, its estimation of their reaction functions becomes more accurate. Here, it is shown that by choosing appropriate regressors for estimating the strategies of other players at each time-step of the market and using them for making the next step decision, the game will converge to its Nash equilibrium point. The simulation results for an oligopolistic market show the effectiveness of the proposed method.