Application of adaptive control to the fluctuation of engine speed at idle

Air management in a diesel engine using fuzzy control techniques

“…The VAF index reference is used to define the degree of accuracy obtained by the model, which is defined by Eq. (20). When the validation step determines a poor value of index VAF, or an unbalanced result for the different outputs, the designer should reject this model and return to the structure model selection step.…”

“…VAF, which is defined in Eq. (20), is widely used in the field of identifying dynamic systems -as can be seen in [40]. The closer to 100%, the better the performance of the model as an approximation of the real system.…”

“…There are two other variables that have an important effect on engine performance. One is the speed of the engine (N) [27,20], which depends on several variables such as ngine torque, load torque, vehicle inertial moment, etc. The other variable, obviously, is the flow of fuel injected ð _ m f Þ [14] and this determines the AFR.…”

EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots

“…In this subsection, we first examine the adaptive control [13,16,17,20,29,35] for the WMR and then prove the convergence of the trajectory-tracking errors under the EPKC and AFSMDC. The system block diagram of the WMR under AFSMDC is shown in the broken line portion of Fig.…”

Development of an idle speed engine model using in-cylinder pressure data and an idle speed controller for a small capacity port fuel injected SI engine

“…e-mail: pvm@iitm.ac.in ratio is included along with spark time control. In such cases, non-linear control techniques like fuzzy logic (Thornhill et al, 2000), adaptive fuzzy logic (Thornhill and Thompson, 1999), the sliding mode method (Srail et al, 2002), genetic algorithms (Kim and Park, 2007), the nonlinear autoregressive exogenous (NARX) model (De Nicolao et al, 1999), and on-line adaptive Proportional Integral Derivative (PID) tuning and the Continuous Action Reinforcement Learning Automata (CARLA) algorithm (Howell and Best, 2000), have been used to achieve superior performance in terms of improved controller robustness and reduction in speed fluctuations, fuel consumption, and noise vibration and harshness.…”