many factors affect yield loss in wheat harvesting with a grain combine harvester and there is no mathematical model to describe the behavior of this complex system. thus in this study, a fuzzy logic controller (flc) was designed, implemented and tested for the automatic settings of cylinder speed, concave clearance, fan speed and forward speed of a model 955 john deere combine. first, the mech...

This paper presents a novel hybridization of the fuzzy logic, the neural network and the coevolutionary algorithm for building a fuzzy-neural system (or a Mamdani fuzzy system) from data. The novel hybridization uses the coevolution of many species, and proposes the coevolution of groups of similar species, both for the optimization of the structure of the fuzzy-neural network. In the fuzzy-neu...

This research paper presents a mobile robot based on the MAMDANI fuzzy inference system. The is equipped with three pairs of HC-SR04 ultrasonic sensors to detect distance between and obstacles. A logic controller built into STM32F4 microcontroller platform generate actuation signal for DC motor mounted each wheel. To perform obstacle avoidance, sensor capable detecting must be installed so that...

This paper addresses the problem of adaptive fuzzy tracking control for aclass of nonlinearly parameterized systems with unknown control directions.In this paper, the nonlinearly parameterized functions are lumped into the unknown continuous functionswhich can be approximated by using the fuzzy logic systems (FLS) in Mamdani type. Then, the Nussbaum-type function is used to de...

In any of the control application, controller design is the most important part. There are different types of controller architectures available in control literature. The controller can be conventional in nature or can be intelligent in nature. The conventional controller doesn’t posses the human intelligence; where in the intelligent controller human intelligence is embed with the help of cer...

Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System). This L-System models the plants growth by following the production rules, which are the combination of grammar and mathematic formulae. In this paper, we propose the use of fuzzy mamdani, to model the plant growth based on the current environment condition. The varied amount of fertilizer, both o...

Mamdani systems can incorporate expert knowledge about an input-output relation in the form of IF-THEN rules expressed in natural language. This is a particularly attractive feature for modeling and simulation, but is also one that can be easily misused. Focusing on applied modeling and simulation, this paper discusses why Mamdani systems are not a useful tool to explore the logical consequence...

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that ...