In this paper, the enhancement of vehicle stability and handling is investigated by control of the active geometry suspension system (AGS). This system could be changed through control of suspension mounting point’s position in the perpendicular direction to wishbone therefore the dynamic is alternative and characteristics need to change. For this purpose, suitable controller needs to change...

The paper proposed a new fuzzy-neural recurrent multi-model for systems identification and states estimation of complex nonlinear mechanical plants with backlash. The parameters and states of the local recurrent neural network models are used for a local direct and indirect adaptive control systems design. The designed local control laws are coordinated by a fuzzy rule based control system. Sim...

This paper develops a new direct model reference fuzzy adaptive control of SISO continuous-time nonlinear systems. The model following conditions are assured by using an adaptive Takagi-Sugeno (TS) fuzzy system as nonlinear state feedback controller. Both full state information and observer-based control schemes are investigated. It is shown, that the proposed control algorithm guarantees the s...

in this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.based on the backstepping technique, the adaptive fuzzy controller is constructed. the main contributions of the paper...

in this paper, an adaptive neuro fuzzy sliding mode based genetic algorithm (anfsga) controlsystem is proposed for a ph neutralization system. in ph reactors, determination and control of ph isa common problem concerning chemical-based industrial processes due to the non-linearity observedin the titration curve. an anfsga control system is designed to overcome the complexity of precisecontrol o...

This paper presents a novel hybrid adaptive fuzzy controller for the regulation of speed on induction machines with direct torque control. The controller is based on a fuzzy system and PID control with decoupled gains. Genetic programming techniques are used for offline optimizations of the normalization constants of fuzzy membership function ranges. Fuzzy cluster means is introduced for online...

In this paper, an observer-based direct adaptive fuzzy-neural controller (ODAFNC) for an anti-lock braking system (ABS) is developed under the constraint that only the system output, i.e., the wheel slip ratio, is measurable. The main control strategy is to force the wheel slip ratio to well track the optimal value, which may vary with the environment. The observer-based output feedback control...