This paper addresses the main steps in model-based control: the identification of the model and the design of the controller. A series of recent research results is aggregated to present a complete approach. A fuzzy model of the system is identified from sampled data using supervised fuzzy clustering for rule extraction. This model is applied in model predictive control (MPC) of the process. Th...

Cell-level analog circuit design is a very challenging task for several reasons: the design problem is usually underconstrained with many degrees of freedom, most analog modules require a custom optimized design, the performance requirements must be traded off as they usually are competing design objectives, to encounter the most important ones. This paper presents some applications of fuzzy te...

in the process of milk production, the highest cost relates to animal feed. based on reports provided by the experts, around seventy percent of dairy livestock costs included feed costs. in order to minimize the total price of livestock feed, according to the limits of feed sources in each region or season, and also the transportation and maintenance costs and ultimately milk price reduction, o...

e-learning model is examined of three major dimensions. and each dimension has a range of indicators that is effective in optimization and modeling, in many optimization problems in the modeling, target function or constraints may change over time that as a result optimization of these problems can also be changed. if any of these undetermined events be considered in the optimization process, t...

transport route planning is one of the most important and frequent activities in supply chain management. the design of information systems for route planning in real contexts faces two relevant challenges: the complexity of the planning and the lack of complete and precise information. the purpose of this paper is to nd methods for the development of transport route planning in uncertainty dec...

in this paper a novel direct adaptive fuzzy system is proposed to control flexible-joints robot including actuator dynamics. the design includes two interior loops: the inner loop controls the motor position using proposed approach while the outer loop controls the joint angle of the robot using a pid control law. one novelty of this paper is the use of a pso algorithm for optimizing the contro...

the ball and beam system is one of the most popular laboratory setups for control education. in this paper, we design a fuzzy pd cascade controller for a ball and beam system using asexual reproduction optimization (aro) technique. the ball & beam system consists of a servo motor, a grooved beam, and a rolling ball. this system utilizes a servo motor to control ball’s position on the beam. chan...

this study is focused on developing an integrated optimization-simulation based genetic algorithm model (iosga) to develop the operational policies for a multi-purpose reservoir system. the objective function of the optimization model is considered to be a linear function of reliability (rel), resiliency (res), and vulnerability (vul) of the river-reservoir system. genetic algorithm (ga) is emp...

In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters (FLP). Then by using the concept of comparison of fuzzy numbers we transform FLP problem into a multiobjective linear programming (MOLP) problem. T...