Observer-based Controller Design Research Articles

Memory-based consensus control for multi-agent systems with time-varying topology and communication constraints

This paper focuses on the design of event-triggered observer-based heterogeneous memory controllers for leader-following multi-agent systems with time-varying topology. In order to save limited on-board resources, a novel adaptive event-triggered strategy based on the nonlinear transformation law of the estimation error is proposed in this paper, which can effectively reduce some unnecessary data transmission due to small fluctuations after the estimation error converges. Then, a more general topology structure described by an interval type-2 fuzzy model is adopted, which contains both nonlinear time-varying law and uncertain parameters. Taking into account the differences in the interactions between various agents, the heterogeneous fuzzy-dependent controllers with past state measurements are constructed to further improve consensus performance. Moreover, some sufficient conditions are derived to solve the designed observers and controllers while ensuring that the desired consensus of the multi-agent systems can be achieved. Finally, two examples are given to illustrate the superiority and effectiveness of the proposed event-triggered strategy, and also to verify that introducing past state measurements into the controller helps enhance the consensus control performance.

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).

State and Disturbance Observer-Based Controller Design for Fully Actuated Systems

State and Disturbance Observer-Based Controller Design for Fully Actuated Systems

On Observer and Controller Design for Nonlinear Hadamard Fractional-Order One-Sided Lipschitz Systems

This paper presents an extensive investigation into the state feedback stabilization, observer design, and observer-based controller design for a specific category of nonlinear Hadamard fractional-order systems. The research extends the conventional integer-order derivative to the Hadamard fractional-order derivative, offering a more universally applicable method for system analysis. Furthermore, the traditional Lipschitz condition is adapted to a one-sided Lipschitz condition, broadening the range of systems amenable to analysis using these techniques. The efficacy of the proposed theoretical findings is illustrated through several numerical examples. For instance, in Example 1, we select an order of derivative r = 0.8; in Example 2, r is set to 0.9; and in Example 3, r = 0.95. This study enhances the comprehension and regulation of nonlinear Hadamard fractional-order systems, setting the stage for future explorations in this domain.

Observer-based control for time-delayed quasi-one-sided Lipschitz nonlinear systems under input saturation

This paper addresses the observer-based controller design problem for nonlinear time-delayed systems under input saturation. The nonlinearities are supposed to satisfy the quasi-one-sided Lipschitz condition, which is less conservative than the one-sided Lipschitz condition. Based on the nonlinear matrix inequalities, control law for nonlinear systems subject to input saturation, time delays, and unavailable states, some sufficient conditions have been developed for an augmented system containing the system state vector and the error vector to ensure the convergence of all states to zero. The paper used a decoupling approach to reduce the complexity of the corresponding observer and controller gain computations. Finally, the effectiveness of the developed results is validated using suitable examples.

Design and Experimental Validation of an Adaptive Multi-Layer Neural Network Observer-Based Fast Terminal Sliding Mode Control for Quadrotor System

This study considers the numerical design and practical implementation of a new multi-layer neural network observer-based control design technique for unmanned aerial vehicles systems. Initially, an adaptive multi-layer neural network-based Luenberger observer is designed for state estimation by employing a modified back-propagation algorithm. The proposed observer’s adaptive nature aids in mitigating the impact of noise, disturbance, and parameter variations, which are usually not considered by conventional observers. Based on the observed states, a nonlinear dynamic inversion-based fast terminal sliding mode controller is designed to attain the desired attitude and position tracking control. This is done by employing a two-loop control structure. Numerical simulations are conducted to demonstrate the effectiveness of the proposed scheme in the presence of disturbance, parameter uncertainty, and noise. The numerical results are compared with current approaches, demonstrating the superiority of the proposed method. In order to assess the practical effectiveness of the proposed method, hardware-in-loop simulations are conducted by utilizing a Pixhawk 6X flight controller that interfaces with the mission planner software. Finally, experiments are conducted on a real F450 quadrotor in a secured laboratory environment, demonstrating stability and good tracking performance of the proposed MLNN observer-based SMC control scheme.

Generalized proportional–integral extended state observer-based controller design for fully actuated systems

In this paper, a feedback controller based on the extended state observer is proposed for fully actuated systems. First, a generalized proportional–integral observer is designed to estimate states and disturbances simultaneously. Using the linear parameter varying approach and the convexity principle, a linear matrix inequality condition is given to obtain the observer gains. Second, on the basis of the full-actuation property and the estimated states, a feedback controller, utilizing estimated disturbances to compensate for system disturbances, is designed to make all the states of the closed-loop system uniformly ultimately bounded. In addition, if disturbances are constant or slow time-varying, the observation errors and the states of closed-loop system are all exponentially convergent. Two illustrations are provided to show the validity and practicality of the proposed approach. Simulation results show that the estimated disturbances can follow the true values with relatively small errors, so compensating the system disturbances with estimated values can effectively reduce the ultimate bounds of states of the closed-loop system.

A Design of Model Predictive Control and Nonlinear Disturbance Observer-based Backstepping Sliding Mode Control for Terrain Following

In this study, we propose the terrain following algorithm using model predictive control and nonlinear disturbance observer-based backstepping sliding mode controller for an aircraft system. Terrain following is important for military missions because it helps the aircraft avoid detection by the enemy radar. The model predictive control is used to replace the generating trajectory and guidance with the flight path angle constraint. In addition, the aircraft is affected to the parameter uncertainty and unknown disturbance such as wind near the mountainous terrain. Therefore, we suggest the nonlinear disturbance-based backstepping sliding mode control method for the aircraft that has highly nonlinearity to enhance flight path angle tracking performance. Through the numerical simulation, the proposed method showed the better tracking performance than the traditional backstepping method. Furthermore, the proposed method presented the terrain following maneuver maintaining the desired altitude.

State Observer-Based Iterative Learning Control Design for Discrete Systems Using the Heavy Ball Method

The paper considers a state observer-based iterative learning control design problem for discrete linear systems. To accelerate the convergence of the learning error, a combination of the heavy ball method from optimization theory and the vector Lyapunov function method for a class of two-dimensional systems known as repetitive processes is used to develop a new design. A supporting numerical example is given, including a comparison with an existing design.

State Observer-Based Iterative Learning Control Design for Discrete Systems Using the Heavy Ball Method

State Observer-Based Iterative Learning Control Design for Discrete Systems Using the Heavy Ball Method

Disturbance Observer-Based Feedback Linearized Controller for Grid-Forming Four-Leg VSI Supplying Unbalanced and Nonlinear Loads

This paper presents the design of a disturbance observer-based controller that regulates the output voltage of three-phase four-leg voltage source inverters (VSIs) deployed for grid-forming operation in Renewable Energy-based Distributed Generation (REDG) Systems. The primary objective of the controller is to provide a symmetric and sinusoidal voltage at the output of the VSI when supplying highly unbalanced and nonlinear loads. The controller employs the feedback linearization (FL) technique and incorporates a disturbance observer (DO) to address a range of disturbances that include oscillations resulting from unbalanced loads, harmonics generated by nonlinear loads, and non-oscillatory disturbances. Notably, the controller adopts a direct control scheme without the need for nested current control loops and does not use any transformation frames. Simulation studies and experimental investigations were conducted to assess the controller’s performance under various load conditions, including both linear and nonlinear types, as well as load transients. The findings demonstrate the controller’s capability to accurately track references while complying with the IEEE power quality standards for the tested conditions.

Observer-based adaptive neural network control design for nonlinear systems under cyber-attacks through sensor networks

This paper considers the adaptive neural tracking control for uncertain nonlinear strict-feedback systems under state-dependent cyber-attacks through sensor networks. As a distinctive feature, by constructing a novel adaptive neural observer, the estimates of system states are used for feedback control instead of the compromised system states corrupted by sensor attacks, such that the assumption on the derivative of attack weight can be removed from the adaptive controller design process. Then, an observer-based control scheme is developed such that all the system signals are bounded and the tracking error converges to a small neighborhood of zero. During the procedure of control design, adaptive backstepping technique is combined with radial basis function neural networks (RBFNNs) to construct controllers. Finally, two examples validate the efficacy of the proposed control scheme.

Dynamic Output Feedback of Second-Order Systems: An Observer-Based Controller with Linear Matrix Inequality Design

This paper presents an observer-based dynamic output-feedback controller design procedure using linear matrix inequality (LMI) optimization for second-order systems with uncertainty and persistent perturbation in the states. Using linear-quadratic criteria, cost functions are minimized in a two-stage procedure to compute optimal state-feedback gains, and observer gains are coupled into a dynamic output-feedback optimal controller. The LMI set used in the two stages is matrix inversion free, a key issue for polytope formulation when uncertainty is present. The approach is tested in a mobile inverted pendulum robotic platform, and the effectiveness is verified in this underactuated and undesensed case.

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

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.

Combined Observer-Based State Feedback and Optimized P/PI Control for a Robust Operation of Quadrotors

This paper deals with a discrete-time observer-based state feedback control design by taking into consideration bounded parameter uncertainty, actuator faults, and stochastic noise in an inner control loop which is extended in a cascaded manner by outer PI- and P-control loops for velocity and position regulation. The aim of the corresponding subdivision of the quadrotor model is the treatment of the control design in a systematic manner. In the inner loop, linear matrix inequality techniques are employed for the placement of poles into a desired area within the complex z-plane. A robustification of the design towards noise is achieved by optimizing both control and observer gains simultaneously guaranteeing stability in a predefined bounded state domain. This procedure helps to reduce the sensitivity of the inner control loop towards changes induced by the outer one. Finally, a model-based optimization process is employed to tune the parameters of the outer P/PI controllers. To allow for the validation of accurate trajectory tracking, a comparison of the novel approach with the use of a standard extended Kalman filter-based linear-quadratic regulator synthesis is presented to demonstrate the superiority of the new design.

Passive observer-based controller design for a class of Lipschitz nonlinear time-varying systems with application to Hepatitis B disease

In this paper, a novel passive formulation has been developed based on LMI to design passive state-observer for a wide range of Lipschitz nonlinear systems. During this formulation, a stable and strictly passive state-observer is provided in order to have passive closed-loop system. A new interconnection between passivity of subsystems and passivity/stability of the total closed-loop system has been presented. In this regard, some theorems are defined based on virtually Euler-Lagrange form of passivation. Due to using this form and the proposed theorems, the design process will simplify and speed up. A passivity-based control based on passive state-observer has been proposed to control the hepatitis B virus infection disease. The reliability of the proposed controller/observer has been examined using MATLAB/SIMULINK, where the simulation results and the sensitivity analysis demonstrate the capability of this novel approach.

Robust Observer-Based Controller Design for Constrained Takagi-Sugeno Systems

This work concerns a descriptor Takagi-Sugeno (T-S) fuzzy system. The system is subject to disturbances, sensor faults, the presence of unmeasurable premise variables, and input saturation which the latter are considered uncertainties of the system. First, the considered system is transformed into the polytopic representation, and then, a robust Proportional-Integral (PI) observer-based controller is designed. This observer-based controller, can estimate both the system states, and the faults, and stabilize closed-loop state trajectories. An integrated robust controller strategy is adopted by a novel structure of non-Parallel Distributed Compensation (non-PDC) control law. furthermore, the proposed approach expresses the stability conditions of controller design are expressed in terms of Linear Matrix Inequalities (LMIs) constrained optimization problem. Using LMI TOOLBOX in MATLAB, we can easily design the type PI observer for efficient robust state/fault estimation and solve the observer-based controller design problem of discrete-time T-S fuzzy systems. Finally, an application to a rolling disc process is given to illustrate the effectiveness of the proposed method.

Robust H∞ observer-based model predictive controller for uncertain linear discrete-time systems due to external disturbances

This article investigates an observer-based robust model predictive control (RMPC) design to control the uncertain discrete-time linear systems with disturbances. To make a more practical scheme, it is supposed that the uncertain system has been faced with unknown disturbance and input constraints. The proposed RMPC approach is based on a state feedback control design that ensures the [Formula: see text] performance criterion to attenuate disturbance affections. Furthermore, in view of practical application, the control law is constructed based on the estimated states obtained from the Luenberger observer. Based on Lyapunov’s theory, the input to state practically stability (ISPS) of the closed-loop system is ensured. Appropriate conditions for the ISPS of the closed-loop system and the estimation error are obtained in terms of online linear matrix inequalities (LMIs) which lead to obtaining the time-varying gain matrices of both controller and observer. Finally, to validate the obtained results, the proposed approach is applied to a numerical example and it is compared with the existing control scheme and the superiority is proved.

Enhanced disturbance observer-based hybrid cascade active disturbance rejection control design for high-precise tracking system in application to aerospace satellite

In the control issue of the detection system for aerospace satellites, a strategy that can effectively ensure line-of-sight (LOS) stabilization of the detection system under complex environments is essential. As the essential detection part of aerospace satellites, the high-precise tracking system (HTS) can be limited in practice by disturbances and system uncertainties and usually needs to solve a disturbance suppression problem. Motivated by successful applications of the active disturbance rejection control (ADRC) in HTS, this article investigates the LOS stabilization problem for the HTS with disturbances and system nonlinearity utilizing enhanced disturbance observer-based hybrid cascade active disturbance rejection control (CADRC). A novel enhanced disturbance observer (EDOB) together with CADRC is initially designed to estimate the disturbances of the HTS, where EDOB is mainly used to compensate for the impacts of external disturbances, and the disturbances that are difficult to model are estimated by CADRC. A set of simulations and experiments, performed on an HTS, compared with the traditional method, shows that the proposed method can effectively suppress the time-varying uncertainties and non-linear friction.