Cooperative control problem of Takagi-Sugeno fuzzy multiagent systems via observer based distributed adaptive sliding mode control

In this paper, the consensus control problem of Takagi-Sugeno (T-S) fuzzy multiagent systems (MASs) is investigated by using an observer based distributed adaptive sliding mode control. A distributed nonfragile observer is put forward to estimate the unmeasured state of agents. Based on such an observer, a novel distributed integral sliding surface is designed to suppress the disturbance and uncertainty of T-S fuzzy MASs. In order to achieve the consensus objective, a nominal distributed protocol and an adaptive sliding mode controller are separately designed. Futhermore, the nominal distributed protocol solves the consensus control problem of T-S fuzzy MASs in the absence of disturbance and uncertainty by using the information of adjacent agents obtained by the observer, while the adaptive sliding mode controller suppresses the disturbance and uncertainty. Finally, the proposed method is applied to two examples. Example 1 verifies the superiority of the method by comparing with the fuzzy-based dynamic sliding mode controller. Example 2 is used to illustrate that our control scheme can effectively solve the consensus control problem of T-S fuzzy MASs.     

Fractional-order adaptive neuro-fuzzy sliding mode H∞ control for fuzzy singularly perturbed systems

This paper investigates the fractional-order (FO) adaptive neuro-fuzzy sliding mode control issue for a class of fuzzy singularly perturbed systems subject to the matched uncertainties and external disturbances. Firstly, a novel FO fuzzy sliding mode surface is presented. Secondly, by introducing an appropriate ε-dependent Lyapunov function, some H_∞ performance analysis criteria are given, which also ensure the robust stability of the sliding mode dynamics. Furthermore, a hybrid neuro-fuzzy network system (HNFNS) is introduced to estimate the matched uncertainty. Moreover, an FO adaptive fuzzy sliding mode controller is designed to drive the state trajectories of fuzzy singularly perturbed systems to the predefined FO sliding mode surface within a finite-time. Finally, two verification examples are presented to illustrate the validity of the proposed FO control scheme.     

Direct adaptive control for nonlinear systems using a TSK fuzzy echo state network based on fractional-order learning algorithm

This paper presents a new Takagi-Sugeno-Kang fuzzy Echo State Neural Network (TSKFESN) structure to design a direct adaptive control for uncertain SISO nonlinear systems. The proposed TSKFESN structure is based on the echo state neural network framework containing multiple sub-reservoirs. Each sub-reservoir is weighted with a TSK fuzzy rule. The adaptive law of the TSKFESN-based direct adaptive controller is derived by using a fractional-order sliding mode learning algorithm. Moreover, the Lyapunov stability criterion is employed to verify the convergence of the fractional-order adaptive law of the controller parameters. The evaluation of the proposed direct adaptive control scheme is verified using two case studies, the regulation problem of a torsional pendulum and the speed control of a direct current (DC) machine as a real-time application. The simulation and the experimental results show the effectiveness of the proposed control scheme.     

Finite-time inter-layer projective synchronization of Caputo fractional-order two-layer networks by sliding mode control

Finite-time inter-layer projective synchronization (FIPS) of Caputo fractional-order two-layer networks (FTN) based on sliding mode control (SMC) technique is investigated in this article. Firstly, in order to realize the FIPS of FTN, a fractional-order integral sliding mode surface (SMS) is established. Then, through the theory of SMC, we design a sliding mode controller (SMCr) to ensure the appearance of sliding mode motion. According to the fractional Lyapunov direct method, the trajectories of the system are driven to the proposed SMS, and some novel sufficient conditions for FIPS of FTN are derived. Furthermore, as two special cases of FIPS, finite-time inter-layer synchronization and finite-time inter-layer anti-synchronization for the FTN are studied. Finally, this paper takes the fractional-order chaotic Lü’s system and the fractional-order chaotic Chen’s system as the isolated node of the first layer system and the second layer system, respectively. And the numerical simulations are given to demonstrate the feasibility and validity of the proposed theoretical results.     

Fractional-order sliding mode control for a bearingless induction motor based on improved load torque observer

In order to improve the anti-disturbance performance of a bearingless induction motor (BIM) control system, a fractional-order sliding mode control (FOSMC) strategy based on improved load torque observer is proposed on the basis of the sliding mode speed regulation system. Using the information memory and genetic characteristics of the fractional calculus operator, the fractional integral term of the speed error is introduced in the design of the traditional sliding surface, which reduces the influence of disturbance on the speed regulation system. The fractional-order sliding mode control law is derived based on the BIM mathematical model, and the stability of the control law is proved by Lyapunov theorem. An improved observer is constructed based on the BIM state equations, and the real-time observed load torque is introduced into the fractional-order sliding mode controller. To improve the observer's convergence speed, the proportional integral form is used to replace the integral form in the traditional reduced order load observer. And the state error feedback coefficients of the improved load observer are calculated. Both simulation and experimental results verified the effectiveness of the proposed control strategy.     

Event-based control for networked T-S fuzzy cascade control systems with quantization and cyber attacks

This paper investigates the event-based control for networked T-S fuzzy cascade control systems with quantization and cyber attacks. In order to solve the problem of limited communication resources, an event-triggered scheme and a quantization mechanism are adopted, which can effectively reduce the burden of communication and save the network resources of the system. By considering the influence of cyber attacks, a newly quantized T-S fuzzy model for networked cascade control systems (NCCSs) under the event-triggered scheme is established. By using the Lyapunov stability theory, sufficient conditions guaranteeing the asymptotical stability of networked T-S fuzzy cascade control systems are obtained. In addition, the controller gains are derived by solving a set of linear matrix inequalities. Finally, a numerical example is presented to verify the validity 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 ${\mathit{H}}_{\infty }$ 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.     

Distributed fuzzy learning sliding mode cooperative control for non-affine nonlinear multi-missile guidance systems via a prescribed performance observer

This paper focuses on the distributed fuzzy learning sliding mode cooperative control issue for non-affine nonlinear multi-missile guidance systems. The dynamics of each follower is non-affine form with unknown lumped factor. To estimate the unknown lumped factor, a generalized fuzzy hyperbolic model (GFHM) based prescribed performance observer (PPO) is proposed. Different from the traditional disturbance observers, a residual set of error transient behavior is incorporated additionally so that the peak phenomenon can be avoided. Meanwhile, an auxiliary system is employed to convert the system of each follower to augmented affine form. Then, a distributed fuzzy learning sliding mode cooperative control approach is designed which consists of two parts. The adaptive sliding mode control (SMC) part is designed to force the states to move along the predefined integral sliding surface. For the equivalent sliding dynamics, the distributed optimal control part with GFHM is developed to minimize the cooperative performance function. Thus, the stability and the optimality of the closed-loop system are guaranteed synchronously. Finally, all signals of closed-loop system are rigorously proved bounded and the multi-missile cooperative guidance scenario is applied to verify the effectiveness of proposed method.     

Fault-tolerant adaptive control for uncertain switched systems with time-varying delay and actuator faults based on sliding mode technique

This paper utilizes the sliding mode approach to tackle the issue of adaptive control for uncertain switched systems with time-varying delay and actuator faults. Firstly, a kind of mathematical model of switched time-varying delay systems under sudden actuator faults is defined. Then, a linear sliding manifold is constructed, followed by some adequate conditions for exponential stability of the switched systems running on the sliding phase. Furthermore, an adaptive fault-tolerant controller for handling the actuator degradation is designed and the reachability of the established sliding manifold is proved. At last, a series of simulation examples are provided to demonstrate the efficiency of the proposed solution.     

Quantized asynchronous extended dissipative observer-based sliding mode control for Markovian jump TS fuzzy systems

This article is dedicated to the issue of asynchronous adaptive observer-based sliding mode control for a class of nonlinear stochastic switching systems with Markovian switching. The system under examination is subject to matched uncertainties, external disturbances, and quantized outputs and is described by a TS fuzzy stochastic switching model with a Markovian process. A quantized sliding mode observer is designed, as are two modes-dependent fuzzy switching surfaces for the error and estimated systems, based on a mode dependent logarithmic quantizer. The Lyapunov approach is employed to establish sufficient conditions for sliding mode dynamics to be robust mean square stable with extended dissipativity. Moreover, with the decoupling matrix procedure, a new linear matrix inequality-based criterion is investigated to synthesize the controller and observer gains. The adaptive control technique is used to synthesize asynchronous sliding mode controllers for error and SMO systems, respectively, so as to ensure that the pre-designed sliding surfaces can be reached, and the closed-loop system can perform robustly despite uncertainties and signal quantization error.Finally, simulation results on a one-link arm robot system are provided to show potential applications as well as validate the effectiveness of the proposed scheme.     

Sliding mode output-feedback control of discrete-time Markov jump systems using singular system method

The issue of adaptive sliding mode controller design via output knowledge is studied for discrete-time Markov jump systems in this paper by means of using singular system scheme. To force the system state onto the sliding motion, an appropriate switching surface depended on the system output is established. Meanwhile, the reachability of the sliding manifold is guaranteed by synthesizing the robust sliding mode controller and adaptive sliding mode controller for the accessible and inaccessible upper bounds of sliding patch, respectively. By using Lyapunov functional technique, sufficient criteria to guarantee the sliding motion to be stochastically admissible are proposed. Then the reachability conditions of the predesigned switching surface are developed. Finally, simulation results are provided to illustrate the effectiveness of the proposed approach.     

Adaptive sliding mode control for persistent dwell-time switched nonlinear systems with matched/mismatched uncertainties and its application

In this paper, the adaptive sliding mode control issue for switched nonlinear systems with matched and mismatched uncertainties is addressed, where the persistent dwell-time switching rule is introduced to describe the switching of parameters. Besides, considering the case that the upper bound of the matched uncertainty is unknown, the purpose of this paper is to utilize an adaptive control method to estimate its upper bound parameters. To begin with, a linear sliding surface is constructed, and then the reduced-order sliding mode dynamics can be obtained through a reduced-order method. Next, sufficient conditions can be derived based on the Lyapunov stability and the persistent dwell-time switching analysis techniques ensuring that the reduced-order sliding mode dynamics is globally uniformly exponentially stable. Moreover, a switched adaptive sliding mode control law is designed, which can not only ensure the reachability of the sliding surface but also estimate the upper bound parameters of the matched uncertainty. Finally, a numerical example and a circuit model are introduced to verify the effectiveness of the proposed method.     

Fuzzy sliding mode control design of Markovian jump systems with time-varying delay

This paper studies the robust stochastic stabilization problem for a class of fuzzy Markovian jump systems with time-varying delay and external disturbances via sliding mode control scheme. Based on the equivalent-input-disturbance (EID) approach, an online disturbance estimator is implemented to reject the unknown disturbance effect on the considered system. Specifically, to obtain exact EID estimation Luenberger fuzzy state observer and a low-pass filter incorporated to the closed-loop system. Moreover, novel fuzzy EID-based sliding mode control law is constructed to ensure the stability of the closed-loop system with satisfactory disturbance rejection performance. By employing Lyapunov stability theory and some integral inequalities, a new set of delay-dependent robust stability conditions is derived in terms of linear matrix inequalities (LMIs). The resulting LMI is used to find the gains of the state-feedback controller and the state observer a for the resulting closed-loop system. At last, numerical simulations based on the single-link arm robot model are provided to illustrate the proposed design technique.     

Robust sliding mode control for stochastic singular Markovian jump systems with unmatched one-sided Lipschitz nonlinearities

This paper investigates sliding mode control of stochastic singular Markovian jump systems with nonlinearity. The unmatched nonlinearity satisfies one-sided Lipschitz condition and quadratically inner-boundedness. In term of a new technical variable transformation, sufficient conditions are developed for nonlinear stochastic singular Markovian jump systems constrained on sliding manifold to guarantee stochastic admissibility and uniqueness of solution based on implicit function theorem. The sliding mode control law by which the trajectories of system can be compelled to the predefined sliding surface in finite time no matter what initial state value is, is synthesized. The derivative singular matrix is fully considered in the whole design process such that the derived conditions can be checked easily.The technical treatment of the nonlinear matrix term avoids the classification discussion of sliding mode controller design. Convex optimization problems subject to linear matrix inequalities are formulated to optimize the desired indexes of interest. Finally, the effectiveness of the proposed approach is illustrated by a numerical example and a practical example.     

Finite-time stabilization of nonlinear time delay systems using LQR based sliding mode control

In this paper, we discussed the robust finite-time stability of conic type nonlinear systems with time varying delays. Some novel conditions are derived to design a linear quadratic regulator (LQR) based sliding mode control (SMC) by proposing an integral switching surface. The sufficient conditions are derived for the considered nonlinear system using Lyapunov–Krasovskii stability theory and linear matrix inequality (LMI) approach. The proposed conditions can be solved using some standard numerical packages. Finally, a practical example is provided to validate the advantages and effectiveness of the proposed results.     

Advanced controller synthesis for fuzzy parameter varying systems

A novel nonlinear time-varying model termed as the fuzzy parameter varying (FPV) system is proposed in this research, which inherits both advantages of the conventional T-S fuzzy system in dealing with nonlinear plants and strengths of the linear parameter varying (LPV) system in handling time-varying features. It is, therefore, an attractive mathematical model to efficiently approximate a nonlinear time-varying plant or to serve as a type of time-varying controller. Using the full block S-procedure, sufficient stability conditions have been derived in the form of linear matrix inequalities (LMIs) to test quadratic stability of the open-loop FPV system. Moreover, sufficient conditions have been derived on synthesizing both state feedback and dynamical output feedback fuzzy gain-scheduling controllers that can stabilize the FPV system. An inverted pendulum with a variable length pole is utilized to demonstrate advantages of the FPV system compared to the conventional T-S fuzzy system in representing a practical time-varying nonlinear plant and to validate the controller synthesis conditions.     

Asynchronous output feedback control for fuzzy Markovian jump systems via sliding mode

This paper investigates the design problem of asynchronous output feedback controller via sliding mode for a class of discrete-time fuzzy Markovian jump systems. Considering the non-synchronization phenomenon between the Markovian jump systems and the sliding controller, an asynchronous control method with a stochastic variable is adopted to describe the connections of the systems and controller. On the other hand, not full of states are accessible for the controller since it is impossible or very expensive to estimate all of states, while the output information can be acquired to the controller all the time. Based on the above aspects, the asynchronous output feedback controller via sliding mode for fuzzy Markovian jump systems is investigated to ensure the sliding mode dynamics to be stochastically stable, besides, several sufficient conditions are given to find a set of feasible solutions of the controller parameters. The asynchronous sliding mode control law is synthesized to guarantee the reachability of the trajectories of the closed-loop systems. Finally, a simulation example is to verify the effectiveness of the control strategy.     

Event-based sliding mode control for fuzzy singular systems with semi-Markovian switching parameters

This paper addresses the observer-based dynamic event-triggered (DET) sliding mode control (SMC) problem for fuzzy singular semi-Markovian jump systems (FSS-MJSs) subject to generalized dissipative performance, in which a novel double-quantized structure is reasonably merged into a unified model. The main aim of this paper is to develop a mode-dependent adaptive sliding mode control (ASMC) law through the DET rule, which not only makes the closed-loop systems mean-square admissibility and generalized dissipative, but also the finite-time reachability around the predefined sliding mode surface (SMS) can be achieved. Firstly, in order to improve the data transmission efficiency and save network bandwidth resources, DET and doubled-quantized-based control protocol are introduced, in which the event-based threshold function is dynamically regulated and the data of input and output are both quantized; Secondly, due to the sensor information constraints, system state information is not always obtained in practice, hence, a suitable observer design can make up for this defect. Meantime, in terms of elegant linearization technique and implicit function theorem, the uniqueness of the solution for FSS-MJSs is also established; Additionally, by making use of the Lyapunov functional and linear matrix inequality (LMI) technique, both the desired SMC gains, observer gains and triggering parameter matrices are co-designed, more than that the derivative singular matrix is also integrated into the whole design process such that the derived conditions are much more easily to be checked; Finally, a numerical example and a practical application example are co-given to verify the effectiveness of our design mentality.     

Security control for Markov jump system with adversarial attacks and unknown transition rates via adaptive sliding mode technique

This paper is concerned with the security control problem for a class of Markov jump systems subject to false data injection attack and incomplete transition rates. An on-line estimation strategy is provided for the time-variant and unknown cyber-attack modes. And then, an adaptive sliding mode controller is synthesized with different robust terms for different modes to guarantee the reachability of the specified sliding surface. Moreover, the sufficient conditions for the stability of the closed-loop systems are derived. Finally, it is shown from simulation results that the effect of both false data injection attack and incomplete TRs can be effectively attenuated by the present adaptive SMC method.