Sharif Digital Repository

This paper discusses a novel and detailed approach for dynamic modeling and control design of a coupled hydraulic dynamometer/turbine-engine system. This study presents a comprehensive model to reveal the coupling effects and an adaptive multiobjective controller to ensure a safe and reliable operation. A fuzzy-based strategy is employed to dynamically adjust the controller gains to keep the state variables and power loading within the desirable operational limits. This approach uses the dynamometer inlet, outlet, and trim valves as well as the turbine fuel flow rate and bleed valve in order to control the system performance during the engine testing process. The proposed fuzzy control... 

In this paper, an optimized control strategy is proposed for a split parallel hydraulic hybrid truck. The model of the vehicle was simulated in Simulink. According to a global optimization technique, a fuzzy control strategy is developed for the vehicle. This strategy shows flexibility for different drive cycles and a desirable fuel consumption reduction, especially for a low speed drive cycle, which is extracted according to an urban utility vehicle mission  

In this paper a fuzzy control strategy of autonomous multiagent systems is presented. The main purpose is to obtain an improvement on the results of designed sliding mode controllers in previous articles using supervisory fuzzy controller. Similarly, a quasi-static swarm model in ndimensional space is introduced wherein the inter-individual interactions are based on artificial potential functions; and the motions of members are in direction with the negative gradient of the combined potentials which are the result of a balance between inter-individual interactions and the simultaneous interactions of the swarm members with their environment. Then a general model for vehicle dynamics of each... 

Magnetorheological (MR) damper is a prominent semi-active control device to vibrate mitigation of structures. Due to the inherent non-linear nature of MR damper, an intelligent non-linear neuro-fuzzy control strategy is designed to control wave-induced vibration of an offshore steel jacket platform equipped with MR dampers. In the proposed control system, a dynamic-feedback neural network is adapted to model non-linear dynamic system, and the fuzzy logic controller is used to determine the control forces of MR dampers. By use of two feedforward neural networks required voltages and actual MR damper forces are obtained, in which the first neural network and the second one acts as the inverse...