In this paper, the position of a pulse width modulation (PWM)-driven pneumatic actuator has been controlled using a dynamic neural network (DNN) and Proportional Integral Derivative (PID) controller. The harmony search algorithm (HSA) has been used to unravel the optimization problem. The DNN controller is optimally designed to control the position of the actuator. As to the performance of the PID controller, it can assist the DNN controller to give better results. Therefore, an optimal hybrid scheme with both DNN and PID controllers based on HSA is suggested. A pneumatic circuit containing a fast-switching valve is used to reduce the complexity of the PWM-driven servo pneumatic system along with its cost price.

No abstract

No abstract

No abstract

In this paper, a new robust fault diagnosis approach based on the combination of Bond Graph (BG) method and a robust observer is proposed. Different criteria including disturbance attenuation level, enhanced fault sensitivity and robustness against parametric uncertainties are considered in the proposed fault diagnosis system. A new form of analytical redundancy relations (ARRs), which is called error-based analytical redundancy relations (EARRs), is introduced and is used as the residuals for fault diagnosis purposes in considered uncertain linear systems. This form of the residuals is obtained using the output estimation error of the observer and satisfies considered criteria of the fault diagnosis system. The ARRs and state space representation of the system can be derived based on the BG model. The robust observer design is defined as an LMI problem in which the region of robustness against parametric uncertainty is achieved by the feasibility constraint of the obtained LMI. Finally, in order to show the performance of the proposed method, a quarter-car model is considered and different criteria are compared with the conventional ARRs method.