Hybrid Mode Control in Improvement to Magnetic Suspension Ball and Beam System

Abstract

The development of magnetic suspension (MS) technology has been widely applied in high-tech industry. MS actuator has features of contact-free, friction-free, low contamination and low noise. This paper describes the design and examination of the hybrid MS actuator referring to our previous works with different analysis aspect to improve the overall performance of actuator and system. The redesigned MS actuator is analyzed and controlled by deriving its magnetic force and system state equations. This paper uses commercial products for design process and simulations about the stability and robustness of system. After deriving the dynamic equation of ball and beam system, the sliding mode control (SMC) is applied in the balance and stabilize the ball and beam system. The drive circuit and MS actuators are controlled by the microcontroller in ball and beam system. The combined SMC and Fuzzy Logic Control (FLC) are also introduced to control the adjustable stable position. Different situations are tested separately with conformed results to desired responses. Finally, comparison and analyses of the results in laboratory have presented good improvements on the proposed system.

Control of a Modified Ball and Beam System Using Tracking System in Real Time with a DC Motor as an Actuator

“…2 shows the cart. The adoption of a linear encoder embedded in the cart, rather than analog sensors, such as resistive, infrared or ultrasonic, which are usually used to determine the position of the ball, in the "tradicional system", is due to the greater accuracy in position measurement and elimination of some commom problems of these sensors, such as presented in [6], in which it is necessary to use a filter to reduce the noise of the resistive sensor that increases the processing time, and [9] presents difficulties in the positioning of the ultrasonic sensor. The location of the encoder sensor coupled to the cart can be seen in Fig.…”

“…Therefore, the (4) can be ignoredand the dynamic of the system is summarized to (5). ̈= …………………….……………...……………(5) The system equation can be represented throughstate space (6) and (7). Where A is the state matrix, B is the input matrix, C is output matrix and Dis the direct transmission matrix, x is the input vector, y is the system output and u is the control action vector.…”

“…The eigenvalues of ( − )are usually selected so that they are to the left of the eigenvalues of .Thus, the observer states rapidly approach the plant states. The physical plant represented by (6) and (12) and the observer by (19) and (20) is shown in Fig. 8.…”

“…In [3] was used a pole placement control in the ball and beam system, in [4]was implemented a fuzzy approach and [5]presented PID (proportional, integral and derivative) and LQR (Linearquadratic regulator) technics. Another important fact about the ball and beam is that due to the simplicity of the plant, several authors present some changes in the model, e.g.in [6] the actuation system is changed,in [7], [8], [9] different types of sensors are used, as well as this work, that presents a change in the plant. This paper presents a continuation of the studies seen in [10] and [11], which the objective is to control a modified ball and beam using atracking control with entire eigenstructure assignment in real time using a DC motor as actuator.…”