Observer-based Fuzzy Control Research Articles

T–S Fuzzy Observer-Based Output Feedback Lateral Control of UGVs Using a Disturbance Observer

This paper introduces a novel observer-based fuzzy tracking controller that integrates disturbance estimation to improve state estimation and path tracking in the lateral control systems of Unmanned Ground Vehicles (UGVs). The design of the controller is based on linear matrix inequality (LMI) conditions derived from a Takagi–Sugeno fuzzy model and a relaxation technique that incorporates additional null terms. The state observer is developed to estimate both the vehicle’s state and external disturbances, such as road curvature. By incorporating the disturbance observer, the proposed approach effectively mitigates performance degradation caused by discrepancies between the system and observer dynamics. The simulation results, conducted in MATLAB and a commercial autonomous driving simulator, demonstrate that the proposed control method substantially enhances state estimation accuracy and improves the robustness of path tracking under varying conditions.

Fuzzy Observer-Based Finite-Time Adaptive Formation Control for Multiple QUAVs With Malicious Attacks

Fuzzy Observer-Based Finite-Time Adaptive Formation Control for Multiple QUAVs With Malicious Attacks

Observer-based fuzzy T–S control with an estimation error guarantee for MPPT of a photovoltaic battery charger in partial shade conditions

To improve the efficiency and performance of a photovoltaic system (PV) an observer-based fuzzy controller design methodology is provided in the study. The desired controller is achieved by employing a combination of linear matrix inequalities (LMIs). The system consists of a photovoltaic generator (PVG) connected to a boost converter. A battery is linked to the boost converter to stock additional energy for further use. A fuzzy controller based on a T–S fuzzy type observer that guarantees a predefined L2 performance is suggested to achieve maximum power point tracking (MPPT) even under changing weather conditions. An optimal trajectory should be tracked to ensure maximum power operation. For this aim, a specific reference fuzzy model is proposed to create the aimed trajectories. Using this method, the system dynamics are precisely reproduced over a large range of operations. The whole T–S fuzzy methodology, suggested in this paper, aims to ensure the most efficient energy recovery to recharge a battery under partially shaded conditions, resulting in high system efficiency. The proposed method is simulated with MATLAB/SIMULINK and the simulation results, with realistic reference trajectories, are driven while taking into account climate variations. The analysis of these simulations, along with a comparison with two other commonly used approaches, led to the conclusion that the suggested strategy succeeded in reducing the tracking time, as well as eliminating the oscillation that often occurs around maximum power point (MPP).

Practical consensus of T-S fuzzy positive multi-agent systems using linear programming

This paper presents the practical consensus of T-S fuzzy positive multi-agent systems with interval type-1 and type-2 fuzzy sets using observer-based control protocols. A fuzzy positive observer is first constructed for the systems. An observer-based fuzzy control protocol is designed, where an additional constant term is introduced. Some linear programming conditions are established to achieve the positivity of the original system and its observer. Then, the practical consensus of the original system is transformed into the stability of a dynamic system, where a set of new variables is defined by combining the constant term and the states of the agents. In the first step, the positivity of the new variables is guaranteed. In the second step, the stability of the dynamic system consisting new variables is addressed by using a fuzzy copositive Lyapunov function. The gain matrices of observer and control protocols are formulated based on a matrix decomposition approach. All positive and consensus conditions are described via linear programming. Finally, two examples are provided to verify the validity of the obtained results.

Observer-Based Fuzzy Control for Nonlinear Networked Systems Under Multichannel Attacks With Indirectly Accessible Mode Information

Observer-Based Fuzzy Control for Nonlinear Networked Systems Under Multichannel Attacks With Indirectly Accessible Mode Information

Polynomial Fuzzy Observer-Based Feedback Control for Nonlinear Hyperbolic PDEs Systems.

This article explores the observer-based feedback control problem for a nonlinear hyperbolic partial differential equations (PDEs) system. Initially, the polynomial fuzzy hyperbolic PDEs (PFHPDEs) model is established through the utilization of the fuzzy identification approach, derived from the nonlinear hyperbolic PDEs model. Various types of state estimation and controller design problems for the polynomial fuzzy PDEs system are discussed concerning the state estimation problem. To investigate the relaxed stability problem, Euler's homogeneous theorem, Lyapunov-Krasovskii functional with polynomial matrices (LKFPM), and the sum-of-squares (SOSs) approach are adopted. The exponential stabilization condition is formulated in terms of the spatial-derivative-SOSs (SD-SOSs). Additionally, a segmental algorithm is developed to find the feasible solution for the SD-SOS condition. Finally, a hyperbolic PDEs system and several numerical examples are provided to illustrate the validity and effectiveness of the proposed results.

Fuzzy disturbance observer-based fuzzy swing suppression control of a ‘mooring-heavy lift crane-cargo’ coupled system

In this paper, an adaptive fuzzy disturbance observer (FDO)-based control is proposed for the swing suppression of the mooring-heavy lift crane (HLC)-cargo system in the presence of a wave disturbance. First, the dynamic model of the HLC system is determined by employing the Lagrangian method, and the wave force is modeled as an exosystem with unknown terms based on the Jonswap spectrum. Then, based on the HLC model and the wave force exosystem, an FDO is established to determine the wave disturbances, and a fuzzy approximator is developed to estimate the unknown terms. A novel disturbance estimation error observer is first developed to facilitate the parameter adaptive updating law. Subsequently, by augmenting the HLC system and disturbance estimation error system, an FDO-based fuzzy antiswing control method is proposed in terms of the linear matrix inequality technique to suppress the swing. The closed-loop system stability is examined by using the Lyapunov method. Finally, the effectiveness of the proposed method is validated by numerical simulation.

A novel robust and fuzzy observer-based speed control method for permanent magnet synchronous motor drive systems

A novel robust and fuzzy observer-based speed control method for permanent magnet synchronous motor drive systems

Observer-based fuzzy control for fractional order PMSG wind turbine systems with adaptive quantized-mechanism

This study aims to present an observer-based fuzzy control approach for a wind turbine system (WTS) equipped with a fractional-order permanent magnet synchronous generator (PMSG) by utilizing an adaptive quantized-mechanism. To do this, firstly, the fractional order control is introduced into the nonlinear PMSG model to improve the convergence rate beyond the existing integer order control techniques. In the next step, the nonlinear PMSG model is converted into linear sub-models using Takagi–Sugeno (T–S) fuzzy models. Using a fractional order Lyapunov function, an adaptive quantization mechanism, and a linear matrix inequality (LMI), we then obtain the necessary conditions for global stabilization of the PMSG-based WTS. Finally, the method proposed in this study demonstrates its superiority and efficiency through comparison with existing methods.

Observer-based fuzzy tracking control of nonlinear systems with intermittent output constraints

This paper pays attention to the output tracking control problem of nonlinear systems where the output is uniquely measurable and subject to an intermittent constraint. A multiplicative transformation based on the shifting-replaying function is introduced together with barrier Lyapunov function to solve the intermittent output constraint. A state observer independent of the matching condition of control gains is designed via the non-uniform state transformation to relax the assumption of full-state measurability. By virtue of the estimated states, we propose an output feedback controller that only involves one fuzzy adaptive parameter to restrain the effect of unknown system nonlinearities. Through Lyapunov stability analysis, it is proved that the proposed controller can make all signals in the closed-loop system remain semi-globally uniformly ultimately bounded. Two simulation examples are provided to verify the effectiveness of the proposed method, and also the superiority over the existing ones.

Outlier-resistant non-fragile observer-based fuzzy boundary control for interconnected nonlinear PDE systems

This paper investigates an observer-based boundary controller design for interconnected nonlinear partial differential equation (PDE) systems. First, the Takagi–Sugeno (T–S) fuzzy model is adopted to accurately describe the target systems. Then, boundary measurements are employed to reduce the number of sensors. Next, considering the phenomenon of abnormal interference that may lead to measurement outliers and observer parameters’ uncertainties, an outlier-resistant non-fragile observer expressed by a saturation function is designed to guarantee the desired control objectives. Moreover, the boundary control approach is employed to trade-off the cost of system design and system performance. Furthermore, utilizing the membership function-dependent Lyapunov functions and free-weight matrixes, sufficient conditions ensuring the closed-loop systems’ exponential stability are obtained while decreasing the conservativeness of the system stability analysis. Finally, the proposed method’s feasibility and effectiveness are validated by an example.

Observer-based fuzzy trajectory-tracking controller for wheeled mobile robots with kinematic disturbances

Wheeled mobile robots (WMRs) have become essential in civilian and industrial applications. Making the WMR accomplish a trajectory-tracking task is essential for several purposes, including autonomous navigation and transportation. Nevertheless, the performance of the closed-loop system may be affected due to unavoidable disturbances. Hence, this manuscript develops a new observer-based fuzzy logic controller that accomplishes the trajectory-tracking task despite disturbances. The controller is split into two elements. The first one consists of an observer compensating for matched disturbances. The second control part employs the fuzzy logic theory to develop a new controller, making the WMR follow a desired reference. Via the Lyapunov formalism, it is theoretically demonstrated that all the tracking errors converge to zero asymptotically. The new control scheme is compared against a proportional integral derivative controller, a feedback methodology, and a finite-time controller that employs a sliding mode controller combined with the backstepping technique. A detailed numerical analysis proves that the novel controller exhibits the lowest tracking errors when the system is affected by kinematic disturbances and noisy measurements, demonstrating its efficiency in a real scenario.

Outlier-resistant observer-based fuzzy sampled-data boundary control for the hot strip mill cooling process

Outlier-resistant observer-based fuzzy sampled-data boundary control for the hot strip mill cooling process

Observer-based preview control for T-S fuzzy systems

PurposeConsidering the unmeasurable states of the systems and the previewed reference signal, a novel fuzzy observer-based preview controller, which is a mixed controller of the fuzzy observer-based controller, fuzzy integrator and preview controller, is considered to address the tracking control problem.Design/methodology/approachThe authors employ an augmentation technique to construct an augmented error system for uncertain T-S fuzzy discrete-time systems with time-varying uncertainties. Additionally, the authors obtain the corresponding linear matrix inequality (LMI) conditions for designing the preview controller.FindingsThis paper discusses the preview tracking problem for nonlinear systems. First, considering the unmeasurable states of the systems and the previewed reference signal, a novel fuzzy observer-based preview controller, which is a mixed controller of the fuzzy observer-based controller, fuzzy integrator, and preview controller, is considered to address the tracking control problem. Then, using the fuzzy Lyapunov functional with the linear matrix inequality (LMI) technique, new sufficient conditions for the asymptotic stability of the augmented system are derived by applying the LMI technique. The preview controller and fuzzy observer can be designed in one step. Finally, a numerical example is used to illustrate the effectiveness of the results.Originality/valueAn augmented error system is successfully constructed by the state augmentation approach. A novel preview controller is designed to address the tracking control problem. The preview controller and fuzzy observer can be designed in one step.

Nonfragile [formula omitted] observer-based fuzzy control for nonlinear networked control systems with multipath packet dropouts

This work considers the design of nonfragile H∞ observer-based controller for nonlinear networked control systems (NCSs) subject to multipath packet dropouts. The nonlinear NCSs are modeled through the Takagi–Sugeno (T–S) fuzzy model. The occurrences of packet dropouts in the measurable output and the control input indicate the multipath packet dropouts. Two random sequences which are mutually independent and obey the Bernoulli distribution are adopted to represent the multipath packet dropouts. Unlike most existing works about the observer-based controller design, a novel observer design scheme is developed in this paper for the T–S fuzzy NCSs with packet dropouts, which does not require the observer to be designed to share the same local system parameters “Al” as the fuzzy plant. Then, by means of the Lyapunov function approach, sufficient conditions are developed to make certain that the controlled T–S fuzzy NCSs are stochastically stable with a H∞ performance index. Through adopting a two-step design method, the search for the local system parameters and gains of the observer and the controller gains is formulated as a feasibility problem of linear matrix inequalities (LMIs). Eventually, the effectiveness of the derived results is verified by an example.

Observer-Based Fuzzy PID Control for Nonlinear Systems With Degraded Measurements: Dealing With Randomly Perturbed Sampling Periods

Observer-Based Fuzzy PID Control for Nonlinear Systems With Degraded Measurements: Dealing With Randomly Perturbed Sampling Periods

Further Results on Asynchronous Fuzzy Observer-Based Output Feedback Control for Networked Nonlinear Systems Using Quantized Measurements

Further Results on Asynchronous Fuzzy Observer-Based Output Feedback Control for Networked Nonlinear Systems Using Quantized Measurements

Observer-based fuzzy adaptive event-triggered control for strictly uncertain nonlinear systems with partial state constraints and output dead-zones

This paper delves into the fuzzy adaptive event-triggered tracking control for a certain class of strictly uncertain nonlinear systems subject to partial state constraints as well as output dead-zones. First of all, fuzzy logic systems (FLSs) are utilised to approximate the unpredictable items, a fuzzy adaptive observer is intended to enable state estimation. Subsequently, a type of smooth approximate model is introduced to settle the nondifferentiable phenomenon of output dead-zones. To reduce the computational overhead of the communication operation effectively, an improved event-triggered control strategy including a decreasing hyperbolic tangent function related to dead-zone, is applied to determine the actual control input. In addition, the barrier Lyapunov function (BLF) is fabricated to address the issue of partial state constraint. By theoretical analysis, the reference signal can be precisely tracked by the system output and all closed-loop signals remain uniformly ultimately bounded (UUB). Finally, the constructed controller's effectiveness is validated with two illustrative examples.

Fuzzy Observer Based Constraint Control for Switched Systems With Actuator Failures and Partially Unstable Subsystems

This paper investigates the adaptive fuzzy observer-based tracking control problem for switched nonlinear systems with full state constraints and actuator failures under the switching law with average dwell time. Since the states in the system are not measurable, a nonlinear fuzzy observer is designed to estimate the immeasurable states. At the same time, the Tangent Barrier-Lyapunov functions are selected to solve the full-state constraint problem. In addition, because of the existence of unknown parameter in actuator failures, the adaptive approach is used. Further, owing to actuator failures in controller, which may lead to some subsystems to be unstable, the switching law under average dwell time is adopted. Thus, even if there exist the actuator failures and partially unstable subsystems, the proposed method can guarantee that all signals in the closed-loop system are bounded, the system output can track the desired signal, and all system states satisfy their corresponding constrained conditions. Moreover, the observer states can well estimate the immeasurable states. Finally, the effectiveness of the presented control scheme is verified by a simulation example.

Disturbance observer-based fuzzy fault-tolerant control for high-speed trains with multiple disturbances

Abstract The fault-tolerant control problem is investigated for high-speed trains with actuator faults and multiple disturbances in this paper. Based on the novel train model resulting from Takagi and Sugeno fuzzy theory, a sliding-mode fault-tolerant control strategy is proposed. The norm bounded disturbances which are composed of interactive forces among adjacent carriages and basis running resistances are rearranged by the fuzzy linearity technique. The modeled disturbances described as an exogenous system are compensated by a disturbance observer. Moreover, a sliding mode surface is constructed, which can transform the stabilization problem of position and velocity into the stabilization problem of position errors and velocity errors, i.e., the tracking problem of position and velocity. Based on the parallel distributed compensation method and the disturbance observer, the fault-tolerant controller is solved. Lyapunov theory is used to prove the stability of the closed-loop system. The feasibility and effectiveness of the proposed fault-tolerant control strategy are illustrated by simulation results.