Sharif Digital Repository

This paper addresses the effect of different optimization criteria for the control purpose of vehicle suspension. In the present study, active vibration control system for a 5 degree-of-freedom (DoF) pitch-plane suspension model with bounce and pitch motions is investigated. In the proposed vehicle model, the impact of the wheel-axle-brake assemblies' masses is also considered. The developed model is controlled using a fuzzy logic controller (FLC) to minimize the vibration of the driver's seat. The controller is designed to control the applied force to the seat. Furthermore, in order to determine the optimal value of fuzzy system parameters, genetic algorithm (GA) optimization search is used... 

A Magneto rheological (MR) rotary brake as a prosthesis knee is addressed here. To the gait of the amputee, the brake, automatically adapts knee damping coefficient using only local sensing of the knee torque and position. It is difficult to design a model-based controller, since the MR knee system has nonlinear and very complicated governing mathematical equations. Hence, a Hybrid self-organizing fuzzy controller and multidimensional wavelet neural network (HSFCMWNN) is proposed here to control the knee damping coefficient using of the inverse dynamics of the MR rotary damper. A Self-organizing fuzzy controller (SOFC) is also proposed and during the control process, the SOFC continually... 

In this paper, the development of a controller for autonomous lateral alignment of fixed-wing Unmanned Aerial Vehicles (UAVs) with runway centerline in landing phase is presented. Fuzzy Logic Control (FLC) is used in order to enable the vehicle to mimic the decision making procedure that a pilot follow in the same situation. Also, for longitudinal motion controller design for the UAV to follow a pre-defined trajectory, the pole-placement technique is used. It is assumed that the runway relative position and orientation are provided by a built in vision system and its associated image processing unit. The performance of the controller in the presence of the Gaussian noises is investigated by... 

Fuzzy sliding mode control (FSMC) as a robust and intelligent nonlinear control technique is proposed to control processes with severe nonlinearity and unknown models. The performance of the proposed method has been evaluated for both single input single output (SISO) and MIMO nonlinear systems through its application in three severely nonlinear processes that are frequently used as benchmarks of nonlinear process control strategies. The evaluation shows that, despite its lack of dependence on the process model, the proposed method performs almost the same as conventional sliding mode control alternatives that utilize all the information that exists in the mathematical model of the process.... 

Doubly-fed induction generator (DFIG) is the most commonly used technology for wind power generation due to the variable speed performance, decoupled control of active and reactive powers, and high efficiency. However, the DFIG originally cannot participate in damping of power system oscillations since it is not synchronously connected to the power system. This paper proposes an optimal and robust additional damping controller for the DFIG wind turbine to contribute it to damp power system oscillations. It is a fuzzy logic controller that its parameters are optimally tuned using the genetic algorithm (GA). The proposed controller modifies the DFIG active power output by using feedback from... 

This paper presents the application of a fuzzy logic controlled Static Compensator (STATCOM) to improve stability of power system. The nonlinear fuzzy logic controller is used to overcome the problems generated by different uncertainties exist in power systems. Different input variables are used to design the controller. Parameters of the proposed controller are adjusted by means of Neural Network techniques to improve performance of the system. Proposed controller is implemented on a single machine infinite bus system to confirm the performance of the controller through simulation results  

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...