Fuzzy Integral Sliding Mode Control Research Articles

A novel cascaded trajectory tracking control for UUVs under time-varying disturbances

In this paper, a novel cascaded trajectory tracking control strategy based on the characteristics of kinematics and dynamics is proposed for unmanned underwater vehicles (UUVs) under complex disturbances. A kinematic controller based on an improved model predictive control (MPC) is designed to solve the speed jump problem by considering system constraints. Moreover, an improved whale optimizer with elite strategy (EIWOA) is used to the rolling optimization process of MPC, ensuring that the global best solution is derived by obtaining the elite individuals in the population. Besides, a dynamic controller that consists of an adaptive disturbance observer and a fuzzy integral sliding mode control (ADO-FISMC) is proposed to obtain optimal thrust force under time-varying disturbances. The benefit of ADO lies in that it can estimate time-varying disturbances without specific information about disturbances. The fuzzy logic system is introduced to alleviate the chattering of sliding mode control. The simulation results demonstrate the great tracking performance of the cascaded trajectory tracking controller. The viability of the proposed algorithm is also confirmed by trials conducted in water pools.

Observer-based fuzzy integral sliding mode control for bilateral teleoperation systems with time-varying delays

This paper aims to examine the stability and tracking performance of a bilateral teleoperation system. The Takagi–Sugeno fuzzy method is utilized, through which the nonlinear master–slave dynamics is converted as a fuzzy-based system. The state observers are designed for the linearized fuzzy teleoperation systems, and the corresponding estimation errors are formulated. Importantly, a novel observer-based fuzzy integral sliding mode control is developed by deliberately introducing the delay term into the sliding surfaces. As such, advanced delay-product type of Lyapunov–Krasovskii functionals are constructed for the augmented state vectors, in order to acquire the additional delay information. In addition, the Wirtinger-based integral inequality along with an extended reciprocally convex matrix inequality is applied to the Lyapunov derivatives to establish the delay-dependent stability conditions. Numerical results are provided to demonstrate efficacy of the developed control mechanism.

Composite Control Based on Feed-Forward and FISMC Method for Accurate Speed of Gimbal System With Harmonic Drive

In the gimbal system of single gimbal magnetically suspended control moment gyroscope (SGMSCMG), harmonic drive is usually installed to ensure the large output torque and reduce the volume and weight of the servo motor. Nevertheless, its nonlinear characteristics make the transmission torque fluctuate and decrease the performance of the gimbal system. The disturbance torque fluctuations can be divided into ‘gear wave torque’ and ‘non-gear wave torque,’ and to suppress the different types of fluctuations, a composite control method based on model-based feed-forward and fuzzy integral sliding mode control (FISMC) method is proposed. The former method is adopted to restrain the gear wave torque. Then, for the rest of the disturbance torques, the FISMC with new dynamic sliding mode surface is put forward to enhance the robustness and improve the performance of the speed. Finally, the simulation and experiments are carried out on SGMSCMG to validate the effectiveness of the composite method. The results show that the torque fluctuation can be effectively suppressed and the performance of the gimbal system can be significantly improved.

Constrained integral fuzzy sliding mode control for an electric vehicle: An LMI-based approach

This study investigates the issue of stability analysis and controller synthesis for an electric vehicle based on the Takagi–Sugeno fuzzy control approach. The proposed adaptive fuzzy integral sliding mode controller ensures that the electric vehicle system performs satisfactorily in the presence of uncertainties and exogenous disturbances, comprising low computational load, small control input amplitude, and reduced energy consumption. For efficient performance of the electric vehicle, the battery voltage (control input) and the vehicle’s speed (system output) are considered restricted. Simulations of an electric vehicle powered by a brushed direct current motor are utilized to evaluate the efficacy of the proposed controller. Ultimately, the design procedure validates the robust performance and fast stabilization of the electric vehicle speed in the presence of exogenous disturbances and parametric uncertainties.

Observer-Based Fuzzy Sliding Mode Attitude Control for Flexible Spacecraft

In this paper, the attitude stabilization of flexible spacecraft with unmeasurable states and disturbances is addressed by an observer-based fuzzy integral sliding mode control scheme. First, a Takagi–Sugeno fuzzy model of flexible spacecraft is established and an observer is proposed based on this model. The convergence conditions of the estimation errors are given by Lyapunov function and the gains of the observer are thus determined. According to the obtained estimates, a novel fuzzy sliding mode control strategy is designed to compensate the influence of disturbance. Finally, an example of flexible spacecraft is employed to verify the effectiveness of the proposed observer and control law.

T-S fuzzy sliding mode control for double-fed induction generator-based wind energy system with a membership function-dependent [formula omitted]-approach

This study is mainly concerned with fuzzy integral sliding mode control (FISMC) design for double-fed induction generator (DFIG)-based wind energy system (WES) under membership function-dependent H∞ approach. To do this, a nonlinear DFIG based WES is considered with exogenous load torque variation. Then, by utilizing Takagi–Sugeno fuzzy approach, the proposed nonlinear system can be expressed as a sum of local sub-models with the help of IF-THEN rules. A suitable FISMC is designed with a reaching law condition for the proposed DFIG-based WES with the disturbances. A new fuzzy-based Lyapunov function is constructed, and the H∞ performance index is calculated for external disturbances under membership function-dependent H∞ approach. The obtained performance index of membership function-dependent H∞ approach can be improved 10% than the conventional H∞ approach. Finally, the simulation results are given the better stable performance of the DFIG-based WES under the designed FISMC, and the comparison results verify the efficacy of the proposed method.

Fuzzy Event-Triggered Integral Sliding Mode Control of Nonlinear Continuous-Time Systems

This article investigates the design of an event-triggered-based integral sliding mode control (SMC) for a class of multiinput Takagi–Sugeno fuzzy model (TSFM)-based nonlinear systems with disturbance. Incorporating integral SMC scheme can be used along with the event-triggered control to deal with the simultaneous external disturbances and unnecessary waste of system resources. To further accommodate the characteristic of event-triggered integral SMC (ETISMC), two fuzzy integral switching surfaces are established. One is the triggered-state dependent switching surface which is proposed to obtain the ETISMC law. The other one is the conventional continuous-state dependent switching surface which is designed to ensure the robustness of the controlled system from the initial time instance. The proposed ETISMC is applicable for both single–input and multi–input, and despite the previous studies, a more reasonable ETISMC law is proposed with asynchronous premise variables. Based on Lyapunov function and adopting a decreasing time-varying triggering threshold in the event-triggered condition, the ultimately bounded stability of the closed-loop system is guaranteed. Sufficient conditions for the ultimate bounded of the trajectories of the system states are formulated in terms of new offline linear matrix inequalities. Moreover, the positive lower bound of the internal execution is ensured, which means that there is no Zeno phenomenon. To demonstrate the superiority of the proposed technique, the suggested ETISMC is applied to a two-degree freedom helicopter system and the simulation results verify the validity of the proposed control strategy.

Fuzzy Lyapunov-Based Model Predictive Sliding-Mode Control of Nonlinear Systems: An Ellipsoid Recursive Feasibility Approach

In this article, we introduce the design of an artificial fuzzy Lyapunov-based model predictive integral sliding-mode control to achieve the stability of the closed-loop Takagi–Sugeno fuzzy-model-based nonlinear systems. First, to reach the proper performance against the model uncertainties, a fuzzy integral sliding-mode controller (FISMC) is designed. Then, the fuzzy model predictive control (MPC) is developed based on a fuzzy Lyapunov function by considering a contractive constraint and an ellipsoidal terminal constraint. A systematic method is developed to reach the recursive feasibility of the MPC optimization problem based on an ellipsoidal terminal set. Also, a contractive fuzzy Lyapunov condition is imposed on the fuzzy MPC problem to guarantee the stability of closed-loop systems, which is led to a linear matrix inequality-based generalized eigenvalue minimization problem. In the proposed approach, FISMC greatly improves the robustness property of the fuzzy Lyapunov-based model predictive control and the asymptotic stability of the closed-loop system is achieved in comparison with the tube-based MPC. In addition, the proposed robust MPC has a less computational burden and improves the equilibrium point attractivity compared with the max–min MPC and the equality terminal constraint-based MPC. To illustrate the superiority of the proposed strategy, the suggested robust MPC is applied to a truck–trailer system and a numerical example. The simulation results show the capabilities of the proposed robust MPC.

Passivity-Based Fuzzy ISMC for Wind Energy Conversion Systems With PMSG

This paper investigates the fuzzy integral sliding-mode control (ISMC) for permanent magnet synchronous generator (PMSG)-based wind energy conversion systems (WECSs). To do this, by using the double orthogonal complement and Frobenius theorem, the existence condition of the fuzzy sliding surface is presented. By constructing a suitable fuzzy Lyapunov function and introducing slack matrices, the sufficient conditions are gained via linear matrix inequalities (LMIs) for the concerned model to be asymptotically stable and passive. Further, the reachability of the switching surface is ensured by the considered fuzzy sliding-mode control laws. Besides that an adaptive fuzzy ISMC is constructed to derive the passivity criterion. For the demonstration, the presented control strategy is validated with nonlinear PMSG-based WECS. Finally, the effectiveness of the derived theoretical result is established by the numerical parameter values of PMSG-based wind-turbine model.

Dissipativity-Based Fuzzy Integral Sliding Mode Control of Nonlinear Stochastic Systems

In this paper, both dissipation and stabilization of nonlinear T-S fuzzy systems with uncertain parameters are considered. By designing a new integral sliding mode control scheme, which sufficiently utilizes the special properties of T-S fuzzy membership functions, the difficulties induced by the uncertainties and external interference in T-S fuzzy systems are overcome by this new scheme. For the time delay and uncertainty, sufficient conditions are given to ensure the strict dissipation and asymptotic stability of the corresponding sliding mode dynamics. We propose a fuzzy integral sliding mode control law to drive the system trajectory to the fuzzy switching surface in the case of uncertainty and external interference. The realization of a fuzzy sliding mode controller for an inverted pendulum system proves the feasibility and superiority of our theoretical results.

Observer-Based Event-Triggered Fuzzy Integral Sliding Mode Control for Hindmarsh Rose Neuronal Model Via T-S Fuzzy systems

Observer-Based Event-Triggered Fuzzy Integral Sliding Mode Control for Hindmarsh Rose Neuronal Model Via T-S Fuzzy systems

Fuzzy Integral Sliding Mode Control Based on Microbial Fuel Cell

Microbial fuel cell (MFC) is a renewable clean energy. Microorganisms are used as catalysts to convert the chemical energy of organic matter in the sewage into electrical energy to realize sewage treatment and recover energy at the same time. It has good development prospects. However, the output power of MFC is affected by many factors, and it is difficult to achieve a stable voltage output. For the control-oriented single-chamber MFC, a fuzzy integral sliding mode control is designed. The continuous adjustment of the sliding surface ensures that the system only moves on the sliding surface, which eliminates the arrival stage and improves robustness. For chattering existing in the system, the control scheme is further optimized to obtain fuzzy integral sliding mode control, and the fuzzy module adaptively adjusts the control parameters according to the system state, which effectively reduces the system chattering. Experiments prove that the control scheme reduces chattering while ensuring the stable output of the system.

Fuzzy Functional Observer-Based Finite-Time Adaptive Sliding-Mode Control for Nonlinear Systems With Matched Uncertainties

This article is concerned with the fuzzy functional observer-based finite-time adaptive sliding-mode control for nonlinear systems with the partly unmeasurable states and some matched uncertainties. First, considering that the upper bound of the uncertain function exists but unknown, a fuzzy functional observer (FFO) with an adaptive compensator is constructed. Second, an FFO-based fuzzy integral sliding mode controller (ISMCr) is designed such that the closed-loop fuzzy systems are finite-time bounded with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance over the reaching phase, the sliding phase, and the whole finite-time interval, respectively. To reduce the conservatism and increase the solution space of linear matrix inequality conditions, the fuzzy Lyapunov functional approach and equivalent fuzzy relaxed matrices technique are developed by introducing some relaxed matrices in the derivative of the fuzzy normalized membership function. Compared with the common Luenberger-type observer-based approach, the gain matrices of ISMCr depend on the FFO designed, which also enhances the flexibility of controller design. Finally, a simulation example with some comparison is given to show the effectiveness of the proposed method.

H∞ dynamic observer-based fuzzy integral sliding mode control with input magnitude and rate constraints

This paper focuses on a systematic constrained fuzzy integral sliding mode controller design for a class of uncertain discrete-time nonlinear systems which can be represented as Takagi-Sugeno (T-S) fuzzy models. The contributions are to consider constraints on the control input amplitude and control input amplitude rate and to extend the existing pole-placement design technique for designing gain matrices of the fuzzy sliding surface. Moreover, a dynamic-gain observer along with H∞ performance is proposed for attenuating disturbance, which generalizes the existing results on the Proportional Observer (PO), the Proportional Integral Observer (PIO) and the dynamic observer (DO). Finally, the dynamic-observer-based constrained fuzzy integral sliding mode controller is designed. All the proposed design conditions are represented in terms of LMIs-based ones. The methods are studied for not only single-input single-output (SISO) but also multi-input multi-output (MIMO) systems. In the end, the proposed approaches are evaluated on practical and numerical systems to illustrate the superiority of the proposed control scheme.

Sliding-Mode Control of Fuzzy Singularly Perturbed Descriptor Systems

Due to the complicated model characteristics, only a few results focusing on stability analysis have appeared on singularly perturbed descriptor systems (SPDSs). This article instead proposes an integral sliding-mode control strategy for a kind of Takagi-Sugeno fuzzy approximation-based nonlinear SPDSs under time-varying nonlinear perturbation. An appropriate fuzzy integral switching manifold that fully accommodates the system features is designed to completely reject the matched perturbation without amplifying the unmatched one. To facilitate the synthesis of the high-level controller (HLC), the sliding-mode dynamics (SMD) is transformed into an augmented form. Thanks to the adoptions of a novel singular perturbation Lyapunov function, Finsler's lemma, as well as the fixed-point principle, the existence and uniqueness of the solution and the exponential admissibility for the augmented SMD are analyzed. A solution for the designed HLC is further provided. To guarantee the sliding motion, a fuzzy integral sliding-mode controller (FISMC) is synthesized by analyzing the sliding motion reachability. An adaptive FISMC is also given to deal with the unknown upper bounds of the matched perturbation. Finally, the applicability of the developed FISMC strategy is testified by a practical example.

Dynamic Image-Based Visual Servoing of Monocular Camera Mounted Omnidirectional Mobile Robots Considering Actuators and Target Motion via Fuzzy Integral Sliding Mode Control

In this article, an image-based visual servoing (IBVS) method for monocular camera mounted three-wheeled omnidirectional mobile robots (OMRs) is proposed using a novel fuzzy integral sliding mode control (FISMC) method. Most of the existing studies for IBVS of wheeled mobile robots (WMRs) have focused only on kinematics, even though no consideration for the OMR dynamics, actuators, and target motion can lead to much degraded performance. Accordingly, a camera mounted OMR is first modeled considering the OMR dynamics, actuator dynamics, and disturbance effects of the target object motion. On the basis of the OMR model, a dynamic IBVS method (i.e., IBVS based on kinematics, dynamics, and actuators) is then proposed to replace the kinematic IBVS method (i.e., IBVS based only on kinematics) such that the effects of the OMR dynamics, actuators, and target motion can be accommodated by using the FISMC method. In particular, the proposed FISMC method for the IBVS of OMRs can eliminate the reaching phase to make the states remain on the sliding surface all the time and improve the transient performance significantly when compared with the existing methods. The robust stability of the overall system using the proposed system is demonstrated by Lyapunov stability analysis. Simulation results are also provided to show that where the kinematic IBVS achieves much degraded performance owing to the OMR dynamics and target motion, the proposed FISMC-based dynamic IBVS method compensates for these effects and achieve the satisfactory feature point tracking performance, verifying the effectiveness of the proposed method.

New Results on Fuzzy Integral Sliding Mode Control of Nonlinear Singularly Perturbed Systems

This article focuses on the integral sliding mode control (SMC) issue for nonlinear singularly perturbed systems via T-S fuzzy models. A new sufficient criterion for the sliding surface design is attained by adopting convexification techniques, which also guarantees the asymptotic stability of the sliding motion. Then, a new dynamic SMC synthesis scheme is developed to ensure the finite-time reachability of the sliding surface. A simulation example is shown to illustrate the validity of the developed scheme.

Adaptive Fuzzy Integral Sliding-Mode Control for Robust Fault-Tolerant Control of Robot Manipulators With Disturbance Observer

This article develops a new strategy for robust fault-tolerant control (FTC) of robot manipulators using an adaptive fuzzy integral sliding-mode control (ISMC) and a disturbance observer (DO). First, an ISMC is developed for the FTC system. The major features of the approach are discussed. Then, to enhance the performance of the system, a fuzzy logic system approximation and a DO are introduced to approximate the unknown nonlinear terms, which include the model uncertainty and fault components, and to estimate the compounded disturbance and then are integrated into the ISMC. Next, a switching term based on an adaptive two-layer supertwisting algorithm is designed to compensate the disturbance estimated error and guarantee stability and convergence of the whole system. The nominal controller of the ISMC is reconstructed using a backstepping control technique to achieve the stability for the nominal system based on the Lyapunov criterion. The computer simulation results demonstrate the effectiveness of the proposed approach.

Soft computing-based fuzzy integral sliding mode control: a real-time investigation on a conical tank process

In this work, a fuzzy integral sliding mode controller (FISMC) for level control in a conical tank process is demonstrated in real time. In traditional sliding mode controller (SMC) algorithm, the robustness with respect to parameter variations and external disturbances can be achieved only after the reach of sliding phase. However, robustness is not guaranteed during the reaching phase. But integral sliding mode controller (ISMC) hunts to eliminate the reaching phase by imposing sliding mode throughout the system response. ISMC also mitigates chattering caused by discontinuity of controller. Hence, integral of error term is used in the sliding surface. A modified power rate reaching law is proposed to describe the dynamics of the switching function. The fuzzy logic system is integrated to approximate the sliding variable, and control law is formulated so as to alleviate the chattering effect of the control signal. In this paper, Takagi and Sugeno fuzzy logic is integrated with ISMC to achieve smoother sliding surface. Genetic algorithm (GA) is used to tune the membership functions of fuzzy logic and the parameters of the control law. GA-tuned FISMC integrates the features of fuzzy logic control, SMC and soft computing techniques. The effectiveness of algorithm is demonstrated in an experimental setup. The reported results confirm the superiority of GAFISMC compared with proportional integral controller and ISMC algorithm. The real-time implementation ensures the robustness of GAFISMC in terms of operating-level variations, parameter variations and disturbance rejection.

Robust Decentralized Adaptive Fuzzy Integral Sliding Mode Control of Mismatched Uncertain Large-scale Systems

Robust Decentralized Adaptive Fuzzy Integral Sliding Mode Control of Mismatched Uncertain Large-scale Systems