Robust digital implementation of fuzzy control for uncertain systems and its application to active magnetic bearing system

Sung, Hwa Chang; Park, Jin Bae; Joo, Young Hoon; Lin, Kuo Chi

doi:10.1007/s12555-012-0318-4

Cited by 20 publications

(6 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The associate editor coordinating the review of this article and approving it for publication was Xiaodong Sun. methods such as sliding mode control [7], model-based control such as internal model control [8], and fuzzy logic control [9], along with intelligent algorithms such as neural networks [10] and genetic algorithms [11], have expanding applications in AMB control. Furthermore, hybrids of different control methods [12], [13] combine the respective advantages and improve the performance of the controllers.…”

Section: With the Development Of Modern Control Theory Nonlinearmentioning

confidence: 99%

“…Three points are made for the results. First, the term of rotor motion in (9) improves the accuracy of the model, so that the error decreases significantly, and the special inner loop controller for the current increases the response and precision effectively. Second, the use of a nonlinear equation for the magnetic force reduces the effect of the rotor position on error.…”

Section: Control Effect Comparisonmentioning

confidence: 99%

See 1 more Smart Citation

A Dual-Loop Control Approach of Active Magnetic Bearing System for Rotor Tracking Control

2019

View full text Add to dashboard Cite

Rotor tracking control, which can be implemented by active magnetic bearing (AMB) system with high precision, can realize many functions, such as attitude control and special surface processing. However, large-motion rotor tracking control is difficult to implemented, due to AMB's highly nonlinear characteristics. In this paper, a dual-loop neural network sliding mode control (DL-NNSMC) system of AMB is proposed for rotor radial tracking control. The complete model of the AMB system is established and the dual-loop control system is designed. A circuit model that considers the rotor motion is established and the model-based inner loop of current control is established, conjointly for dealing with the influence of rotor motion on the current response and the unknown characteristics of the power amplifier. In the outer loop, a nonlinear electromagnetic force model is applied and a wavelet neural network sliding mode control algorithm is designed for accurate position control. Two cases of rotor trajectory tracking are simulated, and the simulation results demonstrate the validity of the proposed control system for large-motion rotor tracking control and its far superior control performance in terms of precision compared with common approaches based on sliding mode control (SMC). INDEX TERMS Active magnetic bearing, rotor tracking control, control system design, AMB system modeling, sliding mode control.

show abstract

Section: With the Development Of Modern Control Theory Nonlinearmentioning

confidence: 99%

Section: Control Effect Comparisonmentioning

confidence: 99%

A Dual-Loop Control Approach of Active Magnetic Bearing System for Rotor Tracking Control

2019

View full text Add to dashboard Cite

show abstract

“…Nowadays, digital control systems are ubiquitous in real engineering applications, thanks to the rapid advancement of digital computer technology [1,[25][26][27][28][29][30][31][32][33][34][35]. Continuous-time (CT) systems controlled by a digital controller are referred to as sampled-data (SD) control systems, shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

LMI-based robust sampled-data stabilization of polytopic LTI systems: A truncated power series expansion approach

Lee

Joo

2015

Int. J. Control Autom. Syst.

Self Cite

View full text Add to dashboard Cite

For continuous-time linear time-invariant (LTI) systems with polytopic uncertainties, we develop a robust sampled-data state-feedback control design scheme in terms of linear matrix inequalities (LMIs). Truncated power series expansions are used to approximate a discretized model of the original continuous-time system. The system matrices obtained by using the power series approximations are then expressed as homogeneous polynomial parameter-dependent (HPPD) matrices of finite degrees, and conditions for designing the controller are formulated as a HPPD matrix inequality, which can be solved by means of a recent LMI relaxation technique to test the positivity of HPPD matrices with variables in the simplex. To take care of the errors induced by the remainder terms of the truncated power series, the terms are considered as norm bounded uncertainties and then incorporated into the proposed LMI conditions. Finally, examples are used to illustrate the approach.

show abstract

“…Such an approach consists of a set of local linear models that are smoothly connected by nonlinear fuzzy membership functions [1]. Some successful applications in controller synthesis can be found in [2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Local Stabilization of Time-Delay Nonlinear Discrete-Time Systems Using Takagi-Sugeno Models and Convex Optimization

Silva

Leite

Castelan

et al. 2014

Mathematical Problems in Engineering

View full text Add to dashboard Cite

A convex condition in terms of linear matrix inequalities (LMIs) is developed for the synthesis of stabilizing fuzzy state feedback controllers for nonlinear discrete-time systems with time-varying delays. A Takagi-Sugeno (T-S) fuzzy model is used to represent exactly the nonlinear system in a restricted domain of the state space, called region of validity. The proposed stabilization condition is based on a Lyapunov-Krasovskii (L-K) function and it takes into account the region of validity to determine a set of initial conditions for which the actual closed-loop system trajectories are asymptotically stable and do not evolve outside the region of validity. This set of allowable initial conditions is determined from the level set associated to a fuzzy L-K function as a Cartesian product of two subsets: one characterizing the set of states at the initial instant and another for the delayed state sequence necessary to characterize the initial conditions. Finally, we propose a convex programming problem to design a fuzzy controller that maximizes the set of initial conditions taking into account the shape of the region of validity of the T-S fuzzy model. Numerical simulations are given to illustrate this proposal.

show abstract

Robust digital implementation of fuzzy control for uncertain systems and its application to active magnetic bearing system

Cited by 20 publications

References 25 publications

A Dual-Loop Control Approach of Active Magnetic Bearing System for Rotor Tracking Control

A Dual-Loop Control Approach of Active Magnetic Bearing System for Rotor Tracking Control

LMI-based robust sampled-data stabilization of polytopic LTI systems: A truncated power series expansion approach

Local Stabilization of Time-Delay Nonlinear Discrete-Time Systems Using Takagi-Sugeno Models and Convex Optimization

Contact Info

Product

Resources

About