Unknown Input Observer Design for Interval Type-2 T-S Fuzzy Systems With Immeasurable Premise Variables

Observer-based model predictive control for uncertain NCS subject to hybrid attacks via interval type-2 T-S fuzzy model

In this study, an observer-based model predictive control (MPC) algorithm is addressed for an uncertain discrete-time nonlinear networked control system (NCS) subject to hybrid malicious attacks by using interval type-2 Takagi-Sugeno (IT2 T-S) fuzzy theory. Hybrid malicious attacks, including two typical attacks, i.e., denial-of-service (DoS) attacks and false data injection (FDI) attacks, are considered in the communication networks. Under DoS attacks, the control signals will be interfered, which cause the degradation of signal-to-interference-plus-noise ratio, then lead to packets loss. Under FDI attacks, the false signals are injected and output signals are modified so that the system performance is deteriorated. For the NCS subject to hybrid attacks, a secure observer that can resist FDI attacks is devised and a fuzzy MPC algorithm that can solve the controller gains is proposed. Besides, by updating the bound of augmented estimation error, the recursive feasibility can be guaranteed. Finally, illustrative examples are given to show the effectiveness of proposed scheme.

Fault Identification for a Class of Nonlinear Systems of Canonical Form via Deterministic Learning

In this article, through a combination of the deterministic learning (DL) method and the adaptive high gain observer (AHGO) technology, a fault identification approach for a class of nonlinear systems in canonical form is proposed. By using the DL method, the partial persistent excitation condition of the identification system is satisfied, and then, the AHGO technology is exploited to estimate the states and the neural network weights simultaneously. To analyze the convergence of the proposed method, we first analyze the uniformed completely observability (UCO) property of the linear part of the nonlinear identification system. Then, by using the Lipschitz property of the nonlinear item and the Bellman-Gronwall lemma, we show that the UCO property of the nonlinear identification system is depended on the UCO property of the linear part when the observer gain is chosen large. Therefore, by using the UCO property of the nonlinear identification system and the Lyapunov stability theorem, the convergence of the proposed learning observer is proven. The attraction of this article is based on the analysis of the UCO property of the identification system, and the convergence of the proposed learning observer can be directly proven. The simulation example is given to demonstrate the effectiveness of the proposed method.

Dissipativity-Based Fault-Tolerant Control for Stochastic Switched Systems With Time-Varying Delay and Uncertainties

This article investigates the fault-tolerant control problem for stochastic switched interval type-2 (IT2) fuzzy time-delayed uncertain systems based on unknown input observer synthesis, which can avoid uneasy measurement on the time derivative of output, and estimate unavailable or partially measurable states, including sensor and actuator faults accurately. First, a desired fuzzy observer is designed to ensure the observer-based dynamic error system mean-square exponentially stable with sufficient condition of a strict (l,ħ,℘) - [Formula: see text]-dissipative performance, which is a unified framework of passivity, and H_∞ provides results with less conservativeness. Then, we concentrate on stability analyses on dissipativity-based switched IT2 fuzzy systems with stochastic perturbation through linear matrix inequalities, Lyapunov function, free-weighting matrices, and average dwell time, discussing it according to different values of disturbance. Finally, simulation examples are listed to account for availability and effectiveness of the research methodology.

Quantized Interval Type-2 Fuzzy Control for Persistent Dwell-Time Switched Nonlinear Systems With Singular Perturbations

This article investigates the problem of quantized fuzzy control for discrete-time switched nonlinear singularly perturbed systems, where the singularly perturbed parameter (SPP) is employed to represent the degree of separation between the fast and slow states. Taking a full account of features in such switched nonlinear systems, the persistent dwell-time switching rule, the technique of singular perturbation and the interval type-2 Takagi-Sugeno fuzzy model are introduced. Then, by means of constructing SPP-dependent multiple Lyapunov-like functions, some sufficient conditions with the ability to ensure the stability and an expected H_∞ performance of the closed-loop system are deduced. Afterward, through solving a convex optimization problem, the gains of the controller are obtained. Finally, the correctness of the proposed method and the effectiveness of the designed controller are demonstrated by an explained example.

ℓ₂-ℓ∞ Control of Discrete-Time State-Delay Interval Type-2 Fuzzy Systems via Dynamic Output Feedback

This article investigates the design of the l₂-l_∞ dynamic output-feedback (DOF) controller for interval type-2 (IT2) T-S fuzzy systems with state delay. For nonlinear systems, the IT2 fuzzy model is an efficient modeling method which can better express uncertainties than the (type-1) fuzzy model. In addition, state delay is also a general factor that affects system performance. After analyzing the stability of the system, based on convex linearization and the projection theorem, this article proposes a delay-dependent output-feedback controller design method. The IT2 membership functions (MFs) of the fuzzy controller are chosen to be different from those of the model so as to increase the freedom of controller selection. A membership-function-dependent (MFD) method based on the staircase MFs is applied to relax the stability analysis results. Finally, a numerical simulation example is given to illustrate the effectiveness of the results.

Line Integral Approach to Extended Dissipative Filtering for Interval Type-2 Fuzzy Systems

This article is concerned with the problems of extended dissipativity analysis and filter design for interval type-2 (IT2) fuzzy systems. Based on the line integral Lyapunov function, a sufficient condition of asymptotic stability and extended dissipativity of the systems under consideration is established. A LMI-based equivalent condition to the obtained one in a nonlinear form is provided by combining congruence transformation with change of variables. This LMI condition obtained is more general than the one which is based on the common quadratic Lyapunov function. Meanwhile, in terms of parameterization, the extended dissipative filter is developed which guarantees the asymptotic stability and extended dissipativity for the filtering error system. Furthermore, our filter obtained by the parameterization method includes the one obtained by the equivalent transformation method as a special case. Two simulation examples are provided to show the merits and effectiveness of the proposed approach.

Fault-Tolerant Control for Stochastic Switched IT2 Fuzzy Uncertain Time-Delayed Nonlinear Systems

This article devotes to solve the fault-tolerant control problem based on interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy stochastic switched uncertain time-delayed systems with signal quantization. Stochastic switched systems can model a dynamic structure susceptible to abrupt faults, making it more practically significant in power systems or economic systems. The core design is an observer-based fault-tolerant control scheme that can estimate incomplete measurable variables and eliminate the influence of fault dynamically well and enhancing the robust stability of the systems subject to quantization effects. A novel method in seeking the upper bound solution of time-varying delay efficiently decreases conservativeness, especially for the proposed time-delayed system. The simulated analysis is specified to verify the availability and validity of the obtained design method.

Large-Angle Velocity-Free Attitude Tracking Control of Satellites: An Observer-Free Framework

The challenging problem on the design of a large-angle attitude tracking controller for rigid satellites without angular velocity measurements is investigated in this article. An efficient and practical angular velocity-free control strategy with a simple, yet efficient structure is proposed. The attitude tracking maneuver is accomplished with the desired attitude pointing accuracy ensured despite disturbances. Compared with the existing observer-based velocity-free schemes, no observer is embedded into the control scheme. The developed approach can be implemented online and in real time. It does not require expensive online computation, enabling its convenient application to practical large-angle attitude tracking maneuvers. The presented control solution is numerically and experimentally validated on a rigid satellite testbed.

Convergent Estimation Mechanism Design for Nonlinear Fuzzy Systems With Faults

The convergent estimation for a class of nonlinear Takagi-Sugeno fuzzy systems is concerned, where time-varying process faults and input disturbances are both involved. A convergent estimation mechanism (CEM) based on a set of fuzzy iterative estimation observers is constructed for the nonlinear fuzzy system; meanwhile, the convergence of the mean sequence of estimation errors (for both states and faults) to zero (vector) is proved. However, in the existing literature, the estimation errors can only be proved to be uniformly ultimately bounded when the fault is time varying. In the design procedure, the disturbances on systems in consideration can be isolated effectively in the obtained fuzzy iterative error dynamics through introducing a suitable isolation technique. Numerical examples give the simulation results to show the effectiveness and merits of the proposed CEM.

Experimental Validation of Total Energy Control System for UAVs

This paper presents an analysis of a Total Energy Control System (TECS) introduced by Lambregts to control unmanned aerial vehicle (UAV) velocity and altitude by using the total energy distribution. Furthermore, an extended Kalman filter (EKF) approach was used to predict aircraft response in terms of angular rates and linear acceleration during a test flight campaign. From both approaches, state equations were obtained to model the aircraft using Matlab-Simulink. From an aerodynamic study, airplane characteristics were obtained in terms of non-dimensional derivatives and compared to those obtained from the experimental methods. It was determined that TECS approach was very accurate; however, disturbance errors could be decreased by adjusting some model parameters. On the other hand, it was difficult to obtain a real estimation from the EKF method due to the presence of turbulence during flight and the relatively low inertia of the scale model. Dynamic characteristics were validated using a low-cost inertial sensor that cab be easily integrated in UAV platforms. The gathered data can be used to predict model characteristics by integrating the information into flight simulators for future design development.

Chatter Mitigation in Milling Process Using Discrete Time Sliding Mode Control with Type 2-Fuzzy Logic System

In order to achieve a high-quality machining process with superior productivity, it is very important to tackle the phenomenon of chatter in an effective manner. The problems like tool wear and improper surface finish affect the milling process and are caused by self-induced vibration termed as chatter. A strategy to control chatter vibration actively in the milling process is presented. The mathematical modeling of the process is carried out initially. In this paper, an innovative technique of discrete time sliding mode control (DSMC) is blended with the type-2 fuzzy logic system. The proposed active controller results in a significantly high mitigation of vibration. The DSMC is linked to the time-varying gain which is an innovative approach to mitigate chattering. The theorem is laid down which validates that the system states are bounded in the case of DSMC-type-2 fuzzy. Stability analysis is carried out using Lyapunov candidate. The nonlinearities linked with the cutting forces and damper friction are handled effectively by using the type-2 fuzzy logic system. The performance of the DSMC-type-2 fuzzy concept is compared with the discrete time PID (D-PID) and discrete time sliding mode control for validating the effectiveness of the controller. The better performance of DSMC-type-2 fuzzy over D-PID and DSMC-T1 fuzzy in the minimization of milling chatter are validated by a numerical analysis approach.

Transmission-Dependent Fault Detection and Isolation Strategy for Networked Systems Under Finite Capacity Channels

This paper addresses a novel transmission-dependent fault detection and isolation (FDI) scheme in finite frequency domain for networked control systems with consideration of limited communication capacity, which includes multiple transmission intervals and delays, media accessing constraints as well as packet losses. By focusing on these phenomena, a switched stochastic system with multistochastic parameters is first modeled to represent the network-induced features. Then, with the aid of finite frequency stochastic performance index and geometric analysis method, a novel FDI scheme is proposed in finite frequency domain. The FDI filters are designed corresponding to the different transmission intervals and complete the task of detection and isolation only by partially available measurements. A novel lemma is investigated subsequently to capture the desired finite frequent stochastic performance for derived systems. Based on this lemma, sufficient conditions are developed to characterize the filter gains. Finally, an application to the VTOL aircraft is presented to show the effectiveness of the proposed approach.