Fuzzy Sliding Mode Control Approach Research Articles

Chaotic vibration control of an axially moving string of multidimensional nonlinear dynamic system with an improved FSMC

A new control approach based on fuzzy sliding mode control (FSMC) is proposed to regulate the chaotic vibration of an axial string. Hamilton’s principle is used to formulate the nonlinear equation of motion of the axial translation string, and the von Kármán equations are used to analyse the geometric nonlinearity. The governing equations are nondimensionalized as partial differential equations and transformed into a nonlinear 3-dimensional system via the third-order Galerkin approach. An active control technique based on the FSMC approach is suggested for the derived dynamic system. By using a recurrent neural network model, we can accurately predict and effectively apply a control strategy to suppress chaotic movements. The necessity of the suggested active control method in the regulation of the nonlinear axial translation string system is proven using different chaotic vibrations. The results show that the study of the chaotic vibrations of axially translating strings requires nonlinear multidimensional dynamic systems of axially moving strings; the validity of the proposed control strategy in controlling the chaotic vibration of axially moving strings in a multidimensional form is demonstrated.

Performance of Robust Type-2 Fuzzy Sliding Mode Control Compared to Various Conventional Controls of Doubly-Fed Induction Generator for Wind Power Conversion Systems

This paper presents a novel hybrid type-2 fuzzy sliding mode control approach for regulating active and reactive power exchanged with the utility grid by a doubly-fed induction generator in a wind energy conversion system. The main objective of this hybridization is to eliminate the steady-state chattering phenomenon inherent in sliding mode control while improving the transient delays caused by type-2 fuzzy controllers. In addition, the proposed control approach has proven to be successful in coping with varying generator parameters and exhibited good reference tracking. An in-depth comparative study with state-of-the-art advanced control techniques is also the focus of the present paper. The comparative study has three objectives, namely: a qualitative comparative study that aims to compare response times and reference tracking capabilities; a quantitative evaluation that takes into account time-integrated performance criteria; and finally, robustness capabilities. The simulation results, carried out in the Matlab/Simulink environment, have demonstrated the effectiveness and best performance of the proposed hybrid type-2 fuzzy sliding mode control with respect to other advanced techniques included in the comparison study.

A novel impedance-based robust fuzzy sliding mode compliance control for the dexterous robot finger with uncertainties

To promote the precision and flexibility of the dexterous robot finger, a novel impedance-based robust fuzzy sliding mode control approach is developed. In the proposed scheme, an impedance control part constructed aims to regulate the contact force; while the robust fuzzy sliding mode controller proposed accounts for enhancing the anti-interference of this uncertain robotic system. Specifically, by analyzing the forward and inverse kinematics of the finger, its dynamical model with unknown and uncertain force disturbances can be established, and based on this model, a novel robust sliding mode impedance force controller has been designed, also, several critical impedance control parameters can be quickly optimized by invoking the fuzzy logic system. Ultimately, the Lyapunov stability of the proposed control is strictly demonstrated in mathematics. The simulations present the efficacy of the proposed scheme in both constrained and unconstrained spaces.

Integration of sEMG-Based Learning and Adaptive Fuzzy Sliding Mode Control for an Exoskeleton Assist-as-Needed Support System

This paper presents an adaptive Fuzzy Sliding Mode Control approach for an Assist-as-Needed (AAN) strategy to achieve effective human–exoskeleton synergy. The proposed strategy employs an adaptive instance-based learning algorithm to estimate muscle effort, based on surface Electromyography (sEMG) signals. To determine and control the inverse dynamics of a highly nonlinear 4-degrees-of-freedom exoskeleton designed for upper-limb therapeutic exercises, a modified Recursive Newton-Euler Algorithm (RNEA) with Sliding Mode Control (SMC) was used. The exoskeleton position error and raw sEMG signal from the bicep’s brachii muscle were used as inputs for a fuzzy inference system to produce an output to adjust the sliding mode control law parameters. The proposed robust control law was simulated using MATLAB-Simulink, and the results showed that it could instantly adjust the necessary support, based on the combined motion of the human–exoskeleton system’s muscle engagement, while keeping the state trajectory errors and input torque bounded within ±5×10−2 rads and ±5 N.m, respectively.

A novel fuzzy sliding mode control approach for chaotic systems

The purpose of this paper is to study the stabilization problem for a class of uncertain chaotic systems against unknown dynamics and disturbances, based on fuzzy sliding mode controller approaches. To fulfill this aim, the first- and the second-orders sliding mode controllers and an adaptive variable universe fuzzy sliding mode controller are combined to a set of linguistic rules, to design some novel approaches for improving the performance of the control action and eliminating the chattering issue. The stability analysis of the closed-loop system is proved via the Lyapunov stability theorem, and also the convergence of the tracking error to zero in finite-time is guaranteed. The new proposed control laws contribute the control actions to outperform the conventional one in terms of chattering reduction and elimination, along with lessening in the reaching time. Moreover, some numerical simulations are provided to depict that the proposed control laws are not only robust with respect to uncertainties and external disturbances, which lead the system to the desired state, but also can significantly eliminate the chattering effect.

(2008-6132) A novel fuzzy sliding mode control approach for chaotic systems

The purpose of this paper is to study the stabilization problem for a class of uncertain chaotic systems against unknown dynamics and disturbances, based on fuzzy sliding mode controller approaches. To fulfill this aim, the first- and the second-orders sliding mode controllers and an adaptive variable universe fuzzy sliding mode controller are combined to a set of linguistic rules, to design some novel approaches for improving the performance of the control action and eliminating the chattering issue. The stability analysis of the closed-loop system is proved via the Lyapunov stability theorem, and also the convergence of the tracking error to zero in finite-time is guaranteed. The new proposed control laws contribute the control actions to outperform the conventional one in terms of chattering reduction and elimination, along with lessening in the reaching time. Moreover, some numerical simulations are provided to depict that the proposed control laws are not only robust with respect to uncertainties and external disturbances, which lead the system to the desired state, but also can significantly eliminate the chattering effect.

The effect of liquid medium on vibration and control of the AFM piezoelectric microcantilever.

This article investigates the vibration motion and control of the piezoelectric microcantilever (MC) of the atomic force microscope in the amplitude mode in a liquid environment for both free and forced vibrations. The modeled MC includes two electrode layers, a piezoelectric layer, and the geometric discontinuities as a result of these layers and the change in the MC cross section at the probe-MC contact point is modeled. The equations of motion are derived using Hamilton's principle and then discretized with the aid of the finite element method. The system frequency and time response in the free vibration mode when placed in a liquid medium are compared with experimental results. Also, the sample surface topography in the noncontact mode, when passing through the surface roughness, has been modeled as rectangular and wedge-shaped. Furthermore, the control of piezoelectric MC in two cases of near and far from the sample surface is examined. In the case of far from the surface, the system is controlled using the piezoelectric layer installed on the beam, whereas in the case of near the surface, the piezo is turned off due to the existence of nonlinear forces such as Van der Waals and Derjaguin, Muller, and Toporov contact forces and the control is achieved through the base excitation. For system control modeling, the robust fuzzy sliding mode control (FSMC) approach is utilized and the results are compared with those of the simple sliding mode control (SMC) as well as proportional, integral, and derivative control. The presented FSMC approach can remarkably reduce the chattering phenomenon at the SMC input in the liquid medium and accordingly improve the results compared to the other two methods.

Robust stabilisation for a class of stochastic T–S fuzzy descriptor systems via dynamic sliding‐mode control

In this study, the authors research the problem of robust stabilisation for a class of stochastic Takagi–Sugeno (T–S) fuzzy descriptor systems via dynamic sliding mode control technique. In the majority of stochastic T–S fuzzy sliding-mode control approaches, two restrictive assumptions are required, one is every subsystem's input matrix is identical, the other is the product of the sliding-mode gain and the stochastic perturbation matrix must be zero. In order to eliminate two restrictive assumptions, we put forward a dynamic sliding-mode control technique for a class of stochastic T–S fuzzy descriptor systems. A criterion is established according to linear matrix inequalities, it guarantees that the stochastic T–S fuzzy descriptor systems with the mismatched uncertainty and disturbance are stochastically admissible and strictly robust dissipative. Moreover, a dynamic sliding-mode controller ensures the reachability of the system trajectories to the predefined sliding surface in finite time. In the end, the technique is applied to an inverted pendulum model to demonstrate the merit and effectiveness of the proposed methods.

An optimized fuzzy continuous sliding mode controller combined with an adaptive proportional‐integral‐derivative control for uncertain systems

SummaryThis article discusses the design of a hybrid fuzzy variable structure control algorithm combined with genetic algorithm (GA) optimization technique to improve the adaptive proportional‐integral‐derivative (PID) continuous second‐order sliding mode control approach (APID2SMC), recently published in our previous article in the literature. In this article, first, as an improved extension to APID2SMC published recently in the literature, an adaptive proportional‐integral‐derivative fuzzy sliding mode scheme (APIDFSMC) is presented in which a fuzzy logic controller is added. Second, a GA‐based adaptive PID fuzzy sliding mode control approach (APIDFSMC‐GA) is introduced to obtain the optimal control parameters of the fuzzy controller in APIDFSMC. The proposed control algorithms are derived based on Lyapunov stability criterion. Simulations results show that the proposed approaches provide robustness for trajectory tracking performance under the occurrence of uncertainties. These simulation results, compared with the results of conventional sliding mode controller, APID2SMC, and standalone classical PID controller, indicate that the proposed control methods yield superior and favorable tracking control performance over the other conventional controllers.

Fuzzy Sliding Mode Control for Systems With Matched and Mismatched Uncertainties/Disturbances Based on ENDOB

An extended nonlinear disturbance observer (ENDOB)-based fuzzy sliding mode control approach is proposed for single-input and single-output systems with matched and mismatched uncertainties/disturbances, and it is extended to the general $n$ th order systems. By integrating the mismatched disturbance estimation and its derivative into the sliding mode surface, an ENDOB-based SMC method is developed for these systems. A fuzzy control system is designed to adjust the gain of the sliding mode dynamically. Compared with the nominal SMC method, the proposed method has a stronger anti-disturbance ability in the presence of matched and mismatched uncertainties/disturbances. It can ensure a satisfactory system performance and reduce the chattering. The stability of the system is proved by using Lyapunov theory. The final simulation results of two examples are provided to verify the effectiveness of the proposed control method.

Adaptive Fuzzy Sliding Mode Control for a Class of Uncertain Nonaffine Nonlinear Strict-Feedback Systems

In this paper, an adaptive fuzzy sliding mode scheme is proposed for a class of single-input, single-output (SISO) unknown uncertain nonaffine nonlinear systems in strict-feedback form. In this scheme, the backstepping algorithm is used to obtain the virtual controllers. The real control law is designed by using sliding mode approach. The both matched and mismatched unknown uncertainties are counteracted by using adaptive robust terms. The unknown nonlinear functions are approximated by employing adaptive fuzzy logic systems. The adaptation laws of the adjustable parameters are deduced from the stability analysis of the closed-loop system in the sense of Lyapunov. The derived adaptive fuzzy sliding mode control approach guarantees the global boundedness property for all the signals and states, and at the same time, steers the tracking error to a very small neighborhood of the origin. Numerical simulation results are provided to show the effectiveness of the proposed control scheme.

Reentry attitude control for a reusable launch vehicle with aeroservoelastic model using type‐2 adaptive fuzzy sliding mode control

SummaryUsing a type‐2 adaptive fuzzy sliding mode control approach, a nonlinear reentry attitude control scheme is presented in this paper for a reusable launch vehicle (RLV) with aeroservoelastic model that assures reliable tracking of guidance commands. The mutual interactions between aerodynamics, structural dynamics, and the flight control system may lead to the aeroservoelasticity problem. Thus, based on the six‐degree‐of‐freedom geometry model of a RLV, the aeroservoelastic model is firstly established via hypothetical modal method and Galerkin method. Then, the overall attitude control strategy is carried out in two‐loop subsystem controller by using backstepping method. For each loop subsystem, a sliding mode controller is developed to assure tracking of guidance commands, and the interval type‐2 fuzzy logic systems combined with adaptive technique are employed to approximate the nonlinear parts to improve the reentry attitude tracking performance. Furthermore, the virtual control is introduced to the control strategy to attenuate the effect of control saltation. Theoretical analysis based on Lyapunov approach illustrates that the closed‐loop system under the designed control method is uniformly stable, and the attitude tracking error converges to a small neighborhood around origin. Finally, the six‐degree‐of‐freedom flight simulation results are provided to demonstrate the effectiveness of the proposed control scheme and aeroservoelastic characteristic of reentry RLV.

New approach of sliding mode control for nonlinear uncertain pneumatic artificial muscle manipulator enhanced with adaptive fuzzy estimator

A new enhanced adaptive fuzzy sliding mode control approach is proposed in this article with its good availability for application in control of a highly uncertain nonlinear two-link pneumatic artificial muscle manipulator. Stability demonstration of the robust convergence of the closed-loop pneumatic artificial muscle manipulator system based on a novel enhanced adaptive fuzzy sliding mode control is experimentally proved using Lyapunov stability theorem. Obtained result confirms that the new enhanced adaptive fuzzy sliding mode control method, applied to the two-link uncertain nonlinear pneumatic artificial muscle manipulator system, is fully investigated with better robustness and precision than the standard sliding mode control and fuzzy sliding mode control techniques.

Direct Yaw-Moment Control of All-Wheel-Independent-Drive Electric Vehicles with Network-Induced Delays through Parameter-Dependent Fuzzy SMC Approach

This paper investigates the robust direct yaw-moment control (DYC) through parameter-dependent fuzzy sliding mode control (SMC) approach for all-wheel-independent-drive electric vehicles (AWID-EVs) subject to network-induced delays. AWID-EVs have obvious advantages in terms of DYC over the traditional centralized-drive vehicles. However it is one of the most principal issues for AWID-EVs to ensure the robustness of DYC. Furthermore, the network-induced delays would also reduce control performance of DYC and even deteriorate the EV system. To ensure robustness of DYC and deal with network-induced delays, a parameter-dependent fuzzy sliding mode control (FSMC) method based on the real-time information of vehicle states and delays is proposed in this paper. The results of cosimulations with Simulink® and CarSim® demonstrate the effectiveness of the proposed controller. Moreover, the results of comparison with a conventional FSMC controller illustrate the strength of explicitly dealing with network-induced delays.

Self-constructing wavelet neural network algorithm for nonlinear control of large structures

An adaptive control algorithm is presented for nonlinear vibration control of large structures subjected to dynamic loading. It is based on integration of a self-constructing wavelet neural network (SCWNN) developed specifically for structural system identification with an adaptive fuzzy sliding mode control approach. The algorithm is particularly suitable when the physical properties such as the stiffnesses and damping ratios of the structural system are unknown or partially known which is the case when a structure is subjected to an extreme dynamic event such as an earthquake as the structural properties change during the event. SCWNN is developed for functional approximation of the nonlinear behavior of large structures using neural networks and wavelets. In contrast to earlier work, the identification and control are processed simultaneously which makes the resulting adaptive control more applicable to real life situations. A two-part growing and pruning criterion is developed to construct the hidden layer in the neural network automatically. A fuzzy compensation controller is developed to reduce the chattering phenomenon. The robustness of the proposed algorithm is achieved by deriving a set of adaptive laws for determining the unknown parameters of wavelet neural networks using two Lyapunov functions. No offline training of neural network is necessary for the system identification process. In addition, the earthquake signals are considered as unidentified. This is particularly important for on-line vibration control of large civil structures since the external dynamic loading due to earthquake is not available in advance. The model is applied to vibration control of a continuous cast-in-place prestressed concrete box-girder bridge benchmark problem seismically excited highway.

Field-programmable Gate Array Based Fuzzy Sliding-mode Controller for a Permanent Magnet Synchronous Motor Drive

—In this article, a field-programmable gate array based fuzzy sliding-mode controller is proposed to control a permanent magnet synchronous motor drive. First, the dynamics of a permanent magnet synchronous motor is derived, and the vector control scheme is introduced in the current loop. Next, to improve the performance of the permanent magnet synchronous motor drive, a fuzzy sliding-mode controller with an integral-operation switching surface is proposed and applied to the speed loop, in which a fuzzy inference mechanism is adopted to generate the reaching control signal. Further, an integrated hardware design method is developed to implement the field-oriented vector current controller and the proposed fuzzy sliding-mode speed controller on a single field programmable gate array chip. Finally, a prototyping platform based on an Altera field-programmable gate array is established to evaluate the ability of the proposed fully integrated solution in terms of control quality and time/area performances. The preferable performance of the proposed field-programmable gate array-based fuzzy sliding-mode control approach for permanent magnet synchronous motor drive is verified by the experimental results compared with the conventional proportional-integral control and sliding mode control schemes.

Robust ${\mathscr H}_{\infty }$ Control of T–S Fuzzy Time-Delay Systems via a New Sliding-Mode Control Scheme

This paper addresses the sliding-mode control (SMC) design problem for a class of uncertain nonlinear systems that can be represented by Takagi-Sugeno (T-S) fuzzy models. We propose a novel dynamic sliding-mode control scheme for T-S fuzzy models, aiming to eliminate the restrictive assumption that all subsystems share a common input matrix, which is required in most existing fuzzy SMC approaches. Sufficient conditions for the reachability of the sliding surface and asymptotic stability of the sliding motion are formulated in the form of linear matrix inequalities. Finally, simulation results that illustrate the advantages and effectiveness of the proposed approaches are provided.

Stabilization Controller Design for a class of Inverted Pendulums via Adaptive Fuzzy Sliding Mode Control

X–Z inverted pendulum is a new kind of inverted pendulum and it can move with the combination of the vertical and horizontal forces. This paper addresses the control problem of X-Z inverted pendulum in the presents of system uncertainties and external disturbances, and an adaptive fuzzy sliding mode control approach is proposed. The fuzzy system is used to approximate the system uncertainties and the complicated intermediate control functions in the backstepping control design. To update the parameters of the fuzzy system, a proper proportional-integral adaptation law is introduced. Finally, simulation studies are done to show the stabilization of the X-Z inverted pendulum under the proposed method. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.2985

Sliding Mode Control for Mass Moment Aerospace Vehicles Using Dynamic Inversion Approach

The moving mass actuation technique offers significant advantages over conventional aerodynamic control surfaces and reaction control systems, because the actuators are contained entirely within the airframe geometrical envelope. Modeling, control, and simulation of Mass Moment Aerospace Vehicles (MMAV) utilizing moving mass actuators are discussed. Dynamics of the MMAV are separated into two parts on the basis of the two time-scale separation theory: the dynamics of fast state and the dynamics of slow state. And then, in order to restrain the system chattering and keep the track performance of the system by considering aerodynamic parameter perturbation, the flight control system is designed for the two subsystems, respectively, utilizing fuzzy sliding mode control approach. The simulation results describe the effectiveness of the proposed autopilot design approach. Meanwhile, the chattering phenomenon that frequently appears in the conventional variable structure systems is also eliminated without deteriorating the system robustness.

Fuzzy Sliding Mode Control of Rigid-Flexible Multibody Systems With Bounded Inputs

Abstract This paper presents the dynamic modeling and fuzzy sliding mode control for rigid-flexible multibody systems. To investigate the dynamic stiffening of rigid-flexible systems, a first-order approximate model of a flexible spacecraft system is formulated by using Hamilton’s principles and assumed mode method, taking into account the second-order term of the coupling deformation field. For highly flexible structural models, ideal surface sliding that produces pure rigid body motion may not be achievable. In this paper, the discontinuity in the sliding mode controller is smoothed inside a thin boundary layer using fuzzy logic technique to reduce the chattering phenomenon efficiently. Sliding mode control is insensitive to parameter variations and provides complete rejection of disturbances, but these advantages only hold in the sliding mode domain. However, when the actuators’ amplitude is limited by their physical constraints, the sliding mode domain will be restricted to some local domain near zero on the switching surface. Control input saturation is also considered in the fuzzy sliding mode control approach. The new features and advantages of the proposed approach are the use of new dynamic equations for the motion of flexible spacecraft systems and the design of fuzzy sliding mode control by taking into account the control input saturation. The classical sliding mode control case is also developed for comparison. Numerical simulations are performed to validate the proposed methods and to demonstrate that rotational maneuvers and vibration suppression are accomplished in spite of the presence of model uncertainty and control saturation nonlinearity.