This paper investigates the problem of adaptive integral sliding mode control for general Takagi–Sugeno fuzzy systems with matched uncertainties and its applications. Different control input matrices are allowed in fuzzy systems. The matched uncertainty is modeled in a unified form, which can be handled by the adaptive methodology. A fuzzy integral-type sliding surface is utilized and the parameter matrices can be determined according to user's requirement. Based on the designed sliding surface, a new sliding mode controller is proposed, and the structure of the controller depends on the difference between the disturbance input matrices and the control input matrices. It is shown that under the proposed sliding mode controller, the resulting closed-loop system can achieve the uniformly ultimate boundedness. Furthermore, simulation examples are presented to show the merit and applicability of the proposed fuzzy sliding mode control method.

Adaptive Sliding Mode Control for Takagi–Sugeno Fuzzy Systems and Its Applications

This paper is concerned with the problem of nonfragile H∞ filtering for continuous-time Takagi-Sugeno (T-S) fuzzy systems. The filter to be designed is assumed to have two types of multiplicative gain variations. First, two relaxed H∞ filtering analysis conditions are proposed based on useful linear matrix inequality preliminaries. Whereafter, the results are exploited to derive sufficient conditions for designing a nonfragile H∞ filter, which guarantees a prescribed H∞ performance of the filtering error system. Compared with the existing results, the proposed design methods not only suit for a standard form of the fuzzy filter but also give more relaxed design conditions. Finally, simulation examples will be given to show the efficiency of the proposed design methods.

Nonfragile $H_{\infty}$ Filter Design for T–S Fuzzy Systems in Standard Form

This paper addresses the problems of observer-based fault reconstruction and fault-tolerant control for Takagi–Sugeno fuzzy descriptor systems subject to time delays and external disturbances. A novel fuzzy descriptor learning observer is constructed to achieve simultaneous reconstruction of system states and actuator faults. Sufficient conditions for the existence of the proposed observer are explicitly provided. Utilizing the reconstructed fault information, a reconfigurable fuzzy fault-tolerant controller based on the separation property is designed to compensate for the impact of actuator faults on system performance by stabilizing the closed-loop system. In addition, the design of the fault reconstruction observer and the fault-tolerant controller is formulated in terms of linear matrix inequalities that can be conveniently solved using convex optimization techniques. Finally, simulation results on a truck–trailer system are presented to verify the effectiveness of the proposed approaches.

Fault Reconstruction and Fault-Tolerant Control via Learning Observers in Takagi–Sugeno Fuzzy Descriptor Systems With Time Delays

This paper is concerned with the problems of state and output feedback control for interval type-2 (IT2) fuzzy systems with mismatched membership functions. The IT2 fuzzy model and the IT2 state and output feedback controllers do not share the same membership functions. A novel performance index, which is expressed as an extended dissipativity performance, is introduced to be a generalization of $H_{\infty }$ , $L_{2}$ – $L_{\infty }$ , passive, and dissipativity performances indexes. First, the IT2 Takagi–Sugeno fuzzy model and the controllers are constructed by considering the mismatched membership functions. Second, on the basis of Lyapunov stability theory, the IT2 fuzzy state and output feedback controllers are designed, respectively, to guarantee that the closed-loop system is asymptotically stable with extended dissipativity performance. The existence conditions of the two kinds of controllers are obtained in terms of convex optimization problems, which can be solved by standard software. Finally, simulation results are provided to illustrate the effectiveness of the proposed methods.

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State and Output Feedback Control of Interval Type-2 Fuzzy Systems With Mismatched Membership Functions

Underactuated robotics is an emerging research direction in the field of robotics. The control input of the underactuated robot is less than the degree of freedom of the system. It has the advantag...

https://journals.sagepub.com/doi/pdf/10.1177/1729881419862164

Underactuated robotics: A review:

This paper explores the influence of bending stresses on the magnetic characteristics of three-phase transformers with amorphous cores. Different types of core structures, including C-cores and toroidal cores, and their magnetic properties are compared using VSM and XRD. The losses in the magnetic core of the three-phase transformer are analyzed using the finite element analysis for both design and measurement. In addition, experimental results indicated that amorphous-core transformers with rectangular corners had higher audible noise and vibration intensities. This is because the condensed distribution of magnetic flux lines in the corners of the core may create high magnetic inductions associated with high magnetostriction. Finally, experiments with three-phase amorphous-core transformers were performed to study the effects of magnetism and magnetostriction on their performance in terms of core loss, vibration, and audible noise.

Effects of magnetomechanical vibrations and bending stresses on three-phase three-leg transformers with amorphous cores

An interval type-2 fuzzy neural network (IT2FNN) is developed for the position control of ball-and-beam systems to confront the noise. A T2FNN consists of a type-2 fuzzy linguistic process as the antecedent part and multi-layer neural network as the consequent part. The developed IT2FNN combines the merits of an interval type-2 fuzzy logic system and a neural network. Furthermore, the parameter-learning of the IT2FNN, which is based on the gradient decent method using adaptation law, is performed on line. Simulation results show that the dynamic behaviors of the proposed IT2FNN control system are more effective and robust with regard to uncertainties than the interval type-2 fuzzy logic control scheme.

Interval type-2 fuzzy neural network for ball and beam systems

This study reports the preparation of soft magnetic ribbons of Fe-based amorphous alloys using the single-roller melt-spinning technique. Ribbon width varied from 142 mm to 213 mm and, with a thickness of approximately 22 μm ± 2 μm. The microstructure and magnetic properties of the ribbons were characterized by differential scanning calorimeter (DSC), X-ray diffraction (XRD), vibrating sample magnetometer (VSM), and electrical resistivity measurements (ERM). The amorphous material properties dependence of the cooling rate and nozzle pressure have uneven surface in ribbon thicknesses are investigated. Magnetic measurement results indicate that some region of the ribbon exhibits good magnetic properties, higher saturation induction and lower coercivity. However, due to the uneven surface of 213 mm wide ribbon, the magnetic responses are not uniformly distributed. To understand the transformer magnetic performances, this study analyzes the measurements of a three-phase 2 MVA amorphous-cored transformer. Experimental results confirm that the transformer with a ribbon width of 142 mm has better magnetic properties in terms of lower core loss, exciting power, and audible noise. Keywords—Amorphous ribbon, uneven surface, magnetic properties, and rapid solidification

/pdf/effect-of-uneven-surface-on-magnetic-properties-of-fe-based-1ygx5r0uv5.pdf

Effect of Uneven Surface on Magnetic Properties of Fe-based Amorphous Power Transformer

In this paper, an adaptive robust dynamic surface controller (ARDSC) is designed to position the steel ball of a magnetic levitation system. The proposed dynamic surface controller is utilized to overcome the problem of explosion of terms associated with the backstepping method. The presence of modeling errors that are uncertainties of physical parameters is considered in this paper. The adaptive mechanism can deal with the model uncertainties and the analysis of the control stability is given. Simulation results are included to indicate the effectiveness and robustness of the provided controller.

Adaptive robust dynamic surface control of magnetic levitation systems

This paper mainly investigates the fuzzy stabilizing control for an under-actuated ball and beam system. In order to achieve the tracking performance of each state, the tracking error between each state variable and the virtual tracking command is minimized. The integrating of the tracking errors is considered as the fuzzy input. In addition, the parameters of the fuzzy controller are optimized with an adaptive mechanism to improve the control performance. The closed-loop stability of the presented control scheme is also analyzed using the Lyapunov theorem. Simulations results indicate that the proposed adaptive fuzzy virtual tracking control scheme can provide better tracking responses than the counterparts of conventional fuzzy controls.

Wei-Shou Chan

Papers

Effects of magnetomechanical vibrations and bending stresses on three-phase three-leg transformers with amorphous cores

Interval type-2 fuzzy neural network for ball and beam systems

Effect of Uneven Surface on Magnetic Properties of Fe-based Amorphous Power Transformer

Adaptive robust dynamic surface control of magnetic levitation systems

Adaptive fuzzy control for under-actuated ball and beam system with virtual state following