Volume 09

This paper addresses a new method of generalized genarating sequences (GGS) in reliability-cost optimization problem. The GGS is an extension based on some modifications of the standard universal genarating function (UGF). This method is convenient for computerized calculation of enumeration combinatorial problems thst arise in discrete optimization problem as encountred in parallel-series power systems. This method will be convenient to the complex combinatorial optimization problem as described below in the context of optimal redundancy-investment allocation problems (PRIOP).

This paper presents the intelligent control system design via the combination of the predictive and the neural-fuzzy controller type of ANFIS. The ANFIS operates in parallel with the neural predictive controller. ANFIS adjusts the output of the predictive controller in order to enhance the predicted inputs. The performance of our proposal is demonstrated on the chemical reactor control problem. Experimental results demonstrate the feasibility of the proposed intelligent control system.

Speeds control of the multi-machines system (MMS) takes a great interest of the scientists in the relevant industry, the real time industrial control systems usually are multidimensional structure, according to the artificial intelligent many researches on the industrial control was carried. The aim of this work is to develop a novel fuzzy logic controller called multi-input multi-output fuzzy logic controller (MIMO-FLC) affect on a winding-unwinding system (Rolling-Unrolling) forming MMS process.

Systems with delay terms at the left (and the right) side of differential equations are addressed. Analysis and synthesis of delay systems can be conveniently studied through a special ring of RQ-meromorphic functions. The control methodology is based on the solution of Diophantine equations in this ring. Final controllers result in the Smith predictor like structure. A scalar parameter is defined as a „tuning knob“ for controller parameters and control behaviour. A simple pole-assignmentlike tuning idea is utilized.

This work deals with the problem of dynamic optimization of an emulsion polymerization reaction in batch reactor. This process can be described as a hybrid system, i.e. dynamic system with both continuous and discrete character. We obtain optimal trajectories of control variable using control vector parameterization (CVP) method. This method translates infinite dynamic optimization problem into finite non–linear programming (NLP) problem. The NLP computation requires gradient information which we provide using method of adjoint variables.

Among optimizations of reactive power are minimization of total active power losses and control of voltage in the real-time. This can be achieved by placing the optimal value of capacitor at proper locations in electrical distribution systems. The proposed methodology is an intelligent fuzzy-ant approach of critical buses detection for optimal placement and sizing of capacitor banks in electrical distribution systems the critical nodal is determiner using fuzzy controller and the sizing of capacitor banks is obtained based on ant colony system.

In this paper the comparison of using simple genetic algorithm and parallel genetic algorithm is presented. As the optimization problems the parameter setting of the heat transfer model of a building and the building’s model calibration were chosen. The model simulation requires huge computing capacity and it is time consuming. Therefore the pressure of simulation evaluations number is concerned and the use of parallelism is desirable.

In this paper we use bilevel programming to find the maximum difference between a model predictive controller (MPC) using a full model and an MPC using a reduced model. The results apply to MPC with quadratic cost function and linear model with linear constraints.