Observer-based Control Research Articles

Observer-based Attitude Maneuver Control of Flexible Spacecraft: A Parametric Approach

Observer-based Attitude Maneuver Control of Flexible Spacecraft: A Parametric Approach

Observer-based fault-tolerant control design for a class of sampled-data nonlinear systems with bounded disturbances

Observer-based fault-tolerant control design for a class of sampled-data nonlinear systems with bounded disturbances

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.

A nonlinear disturbance observer for sliding mode control of surge in centrifugal compressors via TCV actuator

Surge is a form of dynamic instability created as an unstable pattern in the flow of fluid and can severely affect centrifugal compressor performance by causing fluctuations in flow and pressure parameters. Due to the heavy and costly damage that the surge may cause in various industrial processes such as petrochemical plants, it is necessary to design an appropriate control system to reduce the effect of this phenomenon. The problem of active surge control of a centrifugal compressor using the throttle control valve (TCV) in the presence of compressor parametric uncertainties as well as large demands on upstream and downstream loads is investigated in this work. The control objective was to design a robust control system that can stabilize the compressor over a wide operating range without knowing the upper bound for the uncertainties and load demand. The controller should also react quickly by generating a smooth control signal without saturating the control input. These objectives are achieved by designing a sliding mode controller along with a nonlinear disturbance observer. The performance of the proposed disturbance observer-based controller is evaluated under various operational and load conditions and the results are compared against fuzzy type 1, conventional sliding mode, and wavelet-based neural network robust adaptive controllers. The results show that the proposed method can tolerate large disturbances without any knowledge on the upper bound of the incident disturbance, both on the downstream pressure and upstream mass flow which is highly desirable in practice. The comparative study proves the efficacy of the proposed method using various performance measures. The study also confirms the superior robust performance and stability of the proposed method in front of matched and mismatched disturbances as well as model uncertainties especially close to the instability boundary. Although choosing a TCV actuator has made the control system design easier, the sensitivity of the control valve to flow coefficient and zero calibration under different operating ranges of the compression system is studied carefully and some recommendations for the users are provided.

Observer-based resilient dynamic event-triggering control for switched systems under DoS and FDI attacks

This article investigates the problem of the observer-based dynamic event-triggering control for networked switched systems under denial-of-service (DoS) attacks and false data injection (FDI) attacks. The considered DoS attack model is limited by duration and frequency, and the FDI attack signal is generated by an exogenous system. First, an extended observer is constructed to estimate both the system state and the FDI attack signal. Subsequently, an observer-based resilient dynamic event-triggered mechanism is designed to reduce communication resource costs and eliminate the limitation of maximum asynchronous times less than dwell time such that the system can frequently switch in the event interval. Furthermore, by employing Lyapunov stability theory and average dwell time method to guarantee the switched system is exponentially stable. Meanwhile, a co-design scheme of controller gains, observer gains, and triggering parameters is developed. Finally, a switched circuit system is used to substantiate the feasibility of the proposed approach.

Observer-Based Adaptive Control for Uncertain Fractional-Order T-S Fuzzy Systems with Output Disturbances

Observer-Based Adaptive Control for Uncertain Fractional-Order T-S Fuzzy Systems with Output Disturbances

Neural network-based prescribed performance tracking control for a class of nonlinear systems with mismatched disturbances

This paper addresses the prescribed performance tracking control problem for a class of nonlinear systems subject to mismatched uncertainties. A novel disturbance observer-based control (DOBC) scheme is proposed through combining radial basis function neural network (RBFNN) and prescribed performance function (PPF). In contrast to traditional DOBC, the proposed approach employs RBFNN technology to approximate unknown nonlinear functions in the system, instead of treating them as part of lumped disturbances. A novel disturbance observer is developed to estimate disturbances characterised by a nonlinear exogenous system. To enhance control performance, a PPF that characterises both transient and steady-state behaviour is used for the transformation of tracking errors. It can be proved that all the states of the closed-loop system can be guaranteed to be uniformly ultimately bounded (UUB), and that the tracking error evolves within the prespecified boundaries. Theoretical results are validated and supported by two simulation examples.

Finite-time disturbance observer-based levitation control for vehicle-guideway coupling systems

In this study, a novel composite control scheme for the vehicle-guideway coupling systems is proposed, consisting of FTDOs and a FTC, aiming to address the challenges of unknown disturbances and vibration suppression. Specifically, this method adopts a single magnet-track coupling model and introduces a finite-time disturbance observer (FTDO) that utilizes only measured electromagnet-side signals to estimate unmeasurable states and unknown disturbances. Based on the estimated information provided by the FTDO, a finite-time control (FTC) scheme is developed, which simultaneously handles the problems of disturbance compensation and finite-time tracking control. Additionally, the finite-time stability of the levitation system is analyzed and proven. Finally, simulation and experimental results are given to demonstrate the feasibility and superiority of the proposed control approach.

Adaptive observer-based integral event-triggered antivibration control of a full aircraft active landing gear system with irregular runway excitations

Adaptive observer-based integral event-triggered antivibration control of a full aircraft active landing gear system with irregular runway excitations

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.

Observer-based event-triggered time-varying formation control of linear multi-agent systems with distributed infinite delays

Compared with bounded delays, distributed infinite delays are more general in practical systems. Event-triggered control can effectively reduce energy consumption and communication costs. This paper addresses time-varying formation control of general linear multi-agent systems with distributed infinite delays in both of their inputs and outputs. An observer-based event-triggered formation control protocol considering distributed infinite delays is proposed, which is related to the combined observed information and some formation compensation signals at triggering time instants. By utilizing inequality techniques, the desired time-varying formation can be implemented while Zeno-behavior is excluded. Some numerical simulations are carried out for demonstrating the validity of theoretical results.

Extended state observer-based continuous finite time control for a fixed-wing vertical take-off and landing unmanned aerial vehicle

Dual system Vertical Take-Off and Landing (VTOL) fixed-wing Unmanned Aerial Vehicles (UAVs) combine the advantages of both the rotorcraft and fixed-wing UAV, characterizing horizontal and vertical flight capabilities. However, they face challenges such as aerodynamic coupling between propulsion systems, model uncertainty, and external disturbances, significantly deteriorating the tracking accuracy and robustness. This paper proposes an Extended State Observer based Continuous Finite-Time Control (ESO-CFTC) scheme to solve the attitude and trajectory tracking problem of such a VTOL fixed-wing UAV. Initially, the Nonsingular Fast Terminal Sliding Mode (NFTSM) controller guarantees the tracking errors reach a prescribed manifold in finite time with a continuous reaching law, then converge to the origin in finite time while avoiding singularities. To suppress the inherent chattering problem of the sliding mode control, an ESO technique is incorporated into the ESO-CFTC scheme, which is completely decoupled with the basic NFTSM controller. The supremum of the estimation residual set is derivated theoretically. The scheme forces the tracking errors to converge into the neighborhood of the origin in finite time without requiring prior knowledge of lumped disturbance supremum values. Finally, the numerical simulation results in a Matlab/Simulink environment demonstrate that the presented method outperforms existing benchmark in terms of disturbance estimation, tracking accuracy, convergence rate, and robustness.

Observer-based model-free controller for the perturbations estimation and attenuation in robotic plants

The model-free controller is a powerful method because it does not require the knowledge of the robotic plant dynamic equation. Since most of the model-free controllers consider variants of the adaptive or reinforcement learning, one observer-based model-free controller could be a different alternative of interest in the researching community. In this study, an observer-based model-free controller is suggested for the perturbations estimation and attenuation in robotic plants, it contains the model-free observer and the model-free controller. The model-free observer based on the high gain method uses the bounds of the perturbations. The model-free controller based on the sliding mode method uses the bounds of the perturbations and gravity terms. The observer-based model-free controller is applied for the perturbations estimation and attenuation in a cylindrical robotic plant, and a scalar robotic plant.

Coding–decoding-based synchronization of Markov jump neural networks with PDT switched topologies

This paper investigates the observer-based synchronization control issue for a class of discrete-time switched neural networks under the constraint that information exchange between the observer and controller is subject to coding–decoding communication protocol. The variation of network parameters is governed by a Markov chain while a set of pre-known persistent dwell-time switching sequence is introduced to describe the variation of communication topologies among neurons. To ensure the efficient and secure of information transmission, data received from the observer is encoded into a particular set of codewords before sending to the communication channel. Then, these codewords are transformed into corresponding decoded form via the designed decoder after transmission. The main attention is focused on devising a feasible coding–decoding procedure such that the coding–decoding-based controller can be established efficiently. By constructing suitable Lyapunov function that can reveal the variation characteristic of the network parameters and topologies properly, sufficient conditions which ensure the exponential mean-square boundedness of the closed-loop synchronization error systems are presented. Finally, the validity of the proposed control scheme is illustrated by a numerical example.

Observer-based control for plasma glucose regulation in type 1 diabetes mellitus patients with unknown input delay.

This article introduces an observer-based control strategy tailored for regulating plasma glucose in type 1 diabetes mellitus patients, addressing challenges like unknown time-varying delays and meal disturbances. This control strategy is based on an extended Bergman minimal model, a nonlinear glucose-insulin model to encompass unknown inputs, such as unplanned meals, exercise disturbances, or delays. The primary contribution lies in the design of an observer-based state feedback control in the presence of unknown long delays, which seeks to support and enhance the performance of the traditional artificial pancreas by considering realistic scenarios. The observer and control gains for the observer-based control are computed through linear matrix inequalities formulated from Lyapunov conditions that guarantee closed-loop stability. This design deploys a soft and gentle dynamic response, similar to a natural pancreas, despite meal disturbances and input delays. Numerical tests demonstrate the scheme's effectiveness in glycemic level regulation and hypoglycemic episode avoidance.

Observer-based adaptive neutral network inverse optimal containment control for nonlinear multiagent systems with input quantization

This article focuses on the issue of addressing an adaptive neural network (NN) inverse optimal containment control for nonlinear multiagent systems (MASs), which are subject to immeasurable states and quantized input signals simultaneously. To tackle this problem, we utilize a NN to model unknown agents and design a NN observer to estimate the immeasurable states. Additionally, we decompose the hysteretic quantized input into two bounded nonlinear functions. By employing the adaptive backstepping approach and inverse optimal principle, we formulate an adaptive NN inverse optimal containment control method. The developed inverse optimal containment control scheme guarantees that the controlled system is input-to-state stabilizable (ISS). Finally, we validate the effectiveness of our proposed control scheme through simulation results.

Disturbance Observer-Based Tracking Controller for n-Link Flexible-Joint Robots Subject to Time-Varying State Constraints

This paper addresses the tracking control for an n-link flexible-joint robot system with full-state constraints and external disturbances. First, a nonlinear disturbance observer (NDO) is introduced to asymptotically estimate and suppress the influence of the related disturbances. Next, the constrained system under consideration is transformed into a new unconstrained system using state-dependent function (SDF) transformations. Subsequently, a NDO-based tracking controller that combines the backstepping method and filter technique is proposed in this work. Based on stability analysis, it can be proven that the tracking error converges to a predefined compact set, which can be arbitrarily small without violating the full-state constraints. Finally, simulation results are presented to demonstrate the validity of the suggested control algorithm.

Output feedback control for hypersonic flight vehicles via distributed high-gain observer

During the hypersonic flight process of rigid hypersonic flight vehicles (HFVs), the flight-path angle and angle of attack are usually small and sensitive to flight condition variation, the accurate measurements are difficult, subsequently the formulation of states observers is an urgent issue. A distributed high-gain observer is proposed to reconstruct the admissible system state dynamics based on limited measured output. First, a distributed observer is proposed for the cascade strict-feedback system to ensure the global convergence of the state estimation errors between the estimated state in each local observer and system states, for the prescribed system initial values. Second, the distributed high-gain observer-based nonlinear control is investigated on the longitudinal dynamics of HFVs with partial measurable states. The rigid body system dynamic is divided into the altitude subsystem and the velocity subsystem. In the altitude subsystem, the proposed distributed high-gain observer is formulated to exact estimate the flight-path angle and angle of attack, and then the back-stepping design is proposed for constructing the controllers. The nonlinear dynamic inversion controller is introduced to accomplish the velocity tracking. Finally, simulation examples are served to verify that the proposed output feedback control possesses the superior properties of high tracking performance, fast convergence of state estimation error and easy-implementation.

Full state observer-based pole placement controller for pulse width modulation switched mode voltage-controlled buck Converter

Switched mode DC-DC converters play an important role in today's renewable energy systems, electric Vehicles, consumer electrical appliances, and many more. While many researchers have designed controllers for DC-DC converters, achieving low implementation cost remains a significant hurdle. This paper proposes a cost-effective observer-based pole placement controller for a PWM voltage-controlled Buck converter with clear step by step design approach. The state space averaged model of the DC-DC power converter is used to design pole placement with integrator compensator and full state observer. Pole placement is employed to improve the transient and steady state behavior of Voltage reference tracking response and full state observer is applied to extract the inductor current with the aim of removing the actual current sensor. Design specifications are set to a settling time of less than 5 msec and an overshoot of less than 5 %. While designing Observer-Controller combination, the separation principle, designing the controller and observer independently, is utilized by placing the observer poles far to the left of the controller poles for the Observer to converge faster. The designed controller and observer is verified with simulation in MATLAB/SIMULINK software and design of developed controller and observer are realized using low-cost analog electronics circuit components The results shows that the proposed system's strength in tracking the reference output voltage even in the presence of input voltage disturbance and the mean value of inductor current is well extracted having only the output voltage and MOSFET gate signal.

Concurrent Learning Robust Adaptive Fault Tolerant Boundary Regulation of Hyperbolic Distributed Parameter Systems.

This article develops a robust adaptive boundary output regulation approach for a class of complex anticollocated hyperbolic partial differential equations subjected to multiplicative unknown faults in both the boundary sensor and actuator. The regulator design is based on the internal model principle, which amounts to stabilize a coupled cascade system, which consists of a finite-dimensional internal model driven by a hyperbolic distributed parameter system (DPS). To this end, a systematic sliding mode equipped with a backstepping approach is developed such that the robust state feedback control can be realized. Moreover, since the available information is a faulty boundary measurement at the right side point, state estimation is required. However, due to the presence of boundary unknown faults, we need to solve an issue of joint fault-state estimation. Restrictive persistent excitation conditions are usually required to guarantee the exact estimation of faults but are unrealistic in practice. To this end, a novel concurrent learning (CL) adaptive observer is proposed so that exponential convergence is obtained. It is the first time that the spirit of CL is introduced to the field of DPSs. Consequently, the observer-based adaptive boundary fault tolerant control scheme is developed, and rigorous theoretical analysis is given such that the exponential output regulation can be achieved. Finally, the effectiveness of the proposed methodology is demonstrated via comparative simulations.