Fuzzy control of a semi-active multiple degree-of-freedom vibration isolation system

Abstract

Semi-active isolation systems fill the gap between passive and active systems, delivering the versatility and adaptability of fully active systems, by expending a small amount of energy to change system parameters such as stiffness and damping. Magnetic suspension vibration isolation provides an excellent active isolation technology, and has shown useful characteristics including noncontact isolation, fast response, high reliability and long lifespan. However, because it is highly nonlinear and time variant, the control of magnetic suspension vibration isolation is an area that still requires further exploration. This paper presents a fuzzy control algorithm for a semi-active multi-degree-of-freedom vibration system. The fuzzy control is based on the minimization of the weighted sum of squared output forces. The output force response of the fuzzy, PID control semi-active vibration isolation system and passive system under the same excitation are simulated. The simulation results show that the fuzzy control system has much better performance in vibration isolation. An experimental platform is developed to test the performance of the magnetic suspension vibration isolation system and the proposed fuzzy control algorithm. The experimental results are found to be in good agreement with simulation.

Novel Sliding Mode Vibration Controller With Simple Model-Free Design and Compensation for Actuator’s Uncertainty

“…Herein the Lyapunov function technique is employed [36][42] [43]. The Lyapunov candidate function of the dynamics of is defined as (31). Note that is a scalar.…”

“…Fuzzy control provides if-then-type control rules obtained by fuzzy sets, which express ambiguous information about the plant such as empirical knowledge. Because this approach does not require accurate mathematical models of plants, model-free controller design can be established [28]- [31]. For example, vibration control of a building structure using a PI/PID controller combined with a fuzzy controller to compensate for the nonlinear restoring force was proposed [32].…”

Modeling and H∞ Control of Active-Passive Vibration Isolation for Floating Raft System

“…A fuzzy controller based on minimization of force transmissibility is proposed to reduce the vibration of floating raft system. The results show that the proposed fuzzy controller has much better performance in vibration isolation than PID controller and passive system [35]. In this paper, in order to verify the validity of the proposed improvements, mathematical models of the system are identified by OKID from input-output measured data of floating raft system.…”

PID Control of Multisources Complex Excitations Active Vibration Isolation System: An Improved Particle Swarm Optimization Algorithm

“…Thus, it is difficult to build a mathematical model which meets the requirements with the analysis method. Experimental data include all information of the model and the use of model identification method in the experimental data is an effective way to solve such issues [16,17]. The least-squares method is the method which determines the parameter of system model by minimizing square and function of the generalized error.…”

“…Thus, this paper adopts this method to complete model identification of multisources complex excitations active vibration isolation system. The control is the core link of the active vibration isolation system and the feedback control is especially suitable for complex systems and systems with uncertain parameters [17]. With simple structure, good stability, reliable operation, and strong robustness, PID feedback controller is mainly subject to three parameters, namely, P, I, and D. Determination of control parameters is the core of control system design.…”