Abstract: Two-wheel inverted pendulum robot (TWIPR) is designed with two-hub DC motors for human riding and motion control evaluation. In order to measure the tilt angle and angular velocity of the inverted pendulum robot, accelerometer and gyroscope sensors are chosen. The mobile robot’s moving position and velocity were estimated based on DC motor built in hall sensors. The control kernel of this electric mobile robot is designed with embedded Arduino Nano microprocessor. A handle bar was designed to work as steering mechanism. The intelligent model-free fuzzy sliding mode control (FSMC) was employed as the main control algorithm for this mobile robot motion monitoring with different control purpose adjustment. The intelligent controllers were designed for balance control, and moving speed control purposes of this robot under different operation conditions and the control performance were evaluated based on experimental results.
Abstract: A two wheel inverted pendulum (TWIP) vehicle is built with two hub DC motors for motion control evaluation. Arduino Nano micro-processor is chosen as the control kernel for this electric test plant. Accelerometer and gyroscope sensors are built in to measure the tilt angle and angular velocity of the inverted pendulum vehicle. Since the TWIP has significantly hub motor dead zone and nonlinear system dynamics characteristics, the vehicle system is difficult to control by traditional model based controller. The intelligent model-free fuzzy sliding mode controller (FSMC) was employed as the main control algorithm. Then, intelligent controllers are designed for TWIP balance control, and two wheels synchronization control purposes.
Abstract: In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.
Abstract: In this paper, an magnetorheological (MR) mount with
fuzzy sliding mode controller (FSMC) is studied for vibration
suppression when the system is subject to base excitations. In recent
years, magnetorheological fluids are becoming a popular material in
the field of the semi-active control. However, the dynamic equation of
an MR mount is highly nonlinear and it is difficult to identify. FSMC
provides a simple method to achieve vibration attenuation of the
nonlinear system with uncertain disturbances. This method is capable
of handling the chattering problem of sliding mode control effectively
and the fuzzy control rules are obtained by using the Lyapunov
stability theory. The numerical simulations using one-dimension and
two-dimension FSMC show effectiveness of the proposed controller
for vibration suppression. Further, the well-known skyhook control
scheme and an adaptive sliding mode controller are also included in
the simulation for comparison with the proposed FSMC.
Abstract: The performance of a type of fuzzy sliding mode control is researched by considering the nonlinear characteristic of a missile-target interception problem to obtain a robust interception process. The variable boundary layer by using fuzzy logic is proposed to reduce the chattering around the switching surface then is applied to the interception model which was derived. The performances of the sliding mode control with constant and fuzzy boundary layer are compared at the end of the study and the results are evaluated.
Abstract: This paper proposes a Fuzzy Sliding Mode Control (FSMC) as a control strategy for Buck-Boost DC-DC converter. The proposed fuzzy controller specifies changes in the control signal based on the knowledge of the surface and the surface change to satisfy the sliding mode stability and attraction conditions. The performances of the proposed fuzzy sliding controller are compared to those obtained by a classical sliding mode controller. The satisfactory simulation results show the efficiency of the proposed control law which reduces the chattering phenomenon. Moreover, the obtained results prove the robustness of the proposed control law against variation of the load resistance and the input voltage of the studied converter.
Abstract: This paper deals with the comparison between two proposed control strategies for a DC-DC boost converter. The first control is a classical Sliding Mode Control (SMC) and the second one is a distance based Fuzzy Sliding Mode Control (FSMC). The SMC is an analytical control approach based on the boost mathematical model. However, the FSMC is a non-conventional control approach which does not need the controlled system mathematical model. It needs only the measures of the output voltage to perform the control signal. The obtained simulation results show that the two proposed control methods are robust for the case of load resistance and the input voltage variations. However, the proposed FSMC gives a better step voltage response than the one obtained by the SMC.