Development of Novel Compound Controllers to Reduce Chattering of Sliding Mode Control

The robotics and dynamic systems constantly encountered with disturbances such as micro electro mechanical systems (MEMS) gyroscope under disturbances result in mechanical coupling terms between two axes, friction forces in exoskeleton robot joints, and unmodelled dynamics of robot manipulator. Sliding mode control (SMC) is a robust controller. The main drawback of the sliding mode controller is that it produces high-frequency control signals, which leads to chattering. The research objective is to reduce chattering, improve robustness, and increase trajectory tracking of SMC. In this research, we developed controllers for three different dynamic systems: (i) MEMS, (ii) an Exoskeleton type robot, and (iii) a 2 DOF robot manipulator. We proposed three sliding mode control methods such as robust sliding mode control (RSMC), new sliding mode control (NSMC), and fractional sliding mode control (FSMC). These controllers were applied on MEMS gyroscope, Exoskeleton robot, and robot manipulator. The performance of the three proposed sliding mode controllers was compared with conventional sliding mode control (CSMC). The simulation results verified that FSMC exhibits better performance in chattering reduction, faster convergence, finite-time convergence, robustness, and trajectory tracking compared to RSMC, CSMC, and NSFC. Also, the tracking performance of NSMC was compared with CSMC experimentally, which demonstrated better performance of the NSMC controller

Modeling Of Structural And Environmental Effects On Microelectromechanical (Mems) Vibratory Gyroscopes

In this paper we investigate the effects of stiffness, damping and temperature on the performance of a MEMS vibratory gyroscope. The stiffness and damping parameters are chosen because they can be appropriately designed to synchronize the drive and sense mode resonance to enhance the sensitivity and stability of MEMS gyroscope. Our results show that increasing the drive axis stiffness by 50% reduces the sense mode amplitude by ~27% and augments the resonance frequency by ~21%. The stiffness and damping are mildly sensitive to typical variations in operating temperature. The stiffness increases by 1.25%, while the damping decreases by 3.81%, when the temperature is raised from 0C to 45C. Doubling the damping reduces the oscillation amplitude by 80%, but ~1% change in the frequency. The predicted effects of stiffness, damping and temperature can be utilized to design a gyroscope for the desired operating condition

Adaptive Sliding Mode Control Based on Fuzzy Logic and Low Pass Filter for Two-Tank Interacting System

An adaptive sliding mode control (SMC) based on fuzzy logic and low pass filter is designed in this research. The SMC is one of the most widely accepted robust control techniques. However, the main disadvantage of the SMC is chattering phenomena, which inhibits its usage in many practical applications. Fuzzy logic control has supplanted conventional techniques in many applications. A major feature of fuzzy logic is the ability to express the amount of ambiguity in individual perception and human thinking. In this study, a fuzzy inference system is applied to approximate the function in the SMC law. A low pass filter is used to reduce chattering phenomena around the sliding surface. The stability of the control system is proved by the Lyapunov theory. The proposed controller is tested to position tracking control for two-tank interacting system. This system has been applied in process industries like petroleum refineries, chemical, paper industries, water treatment industries. Simulation results in MATLAB/Simulink show that the proposed algorithm is more effective than the sliding mode control, sliding mode control using conditional integrators and fuzzy control without steady-state error, the overshoot is 0 (%), the rising time achieves 2.187 (s) and the settling time is about 3.9133(s)