Observer-based Control Research Articles

Observer-based adaptive neural network control: the convergence properties analysis under the influence of persistent excitation level

Observer-based adaptive neural network control: the convergence properties analysis under the influence of persistent excitation level

Adaptive Event-Triggered Consensus Control of Nonlinear Multi-Agent Systems via Output Feedback Methodology: An Application to Energy Efficient Consensus of AUVs

For dealing with the energy consumption in multi-agent systems (MASs), an event-triggered (ET) methodology is promising, which relies on the activation of communication devices only when communication of data is needed. This paper explores the leaderless consensus for nonlinear MASs using an adaptive ET approach via an output feedback methodology. This adaptive ET scheme is preferred as it can adapt to the environment through setting a communication threshold. The proposed approach renders the observed states of agents by use of nonlinear observers in an output feedback control dilemma, making it more practical. Simple Luenberger observers are developed to avoid the problem of always measuring agents’ states. The strategy of adaptive ET-based control is employed to minimize resource use and information transmission. Design conditions for the observer-based adaptive ET consensus control of nonlinear MASs have been derived via a Lyapunov function, containing state estimation error, consensus error, adaptation term, and nonlinearity bounds. In contrast to the existing methods, the present approach applies a more practical output feedback schema, uses adaptive ET proficiency, and deals with nonlinear agents. An example of a formation of autonomous underwater vehicles achieving the basic consensus realization between displacement and velocity is included to illustrate the viability of the resultant approach.

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.

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.

Event-triggered bipartite consensus to heterogeneous multiagent systems under DoS attacks: A fully distributed method

This paper studies event-triggered bipartite output consensus problem of heterogeneous multiagent systems under denial-of-service (DoS) attacks. A novel dynamic event-triggered scheme (DETS) is proposed, which, by introducing an extra dynamic function with time-varying coefficients into triggering conditions, can guarantee strictly positive minimum inter-event intervals no matter DoS attacks occur or not. An event-based resilient compensator with adaptive coupling coefficients is then designed to estimate leader's state, and a hybrid model with jump dynamics is constructed that can incorporate the estimation error, DETS, and DoS attacks, and is useful for convergence analysis. Then, a fully distributed observer-based control protocol is designed to regulate the bipartite output consensus. The main advantages of the proposed method include: 1) global information is not needed to implement the event-based control protocol; 2) strictly positive inter-event intervals are guaranteed even under DoS attacks. Finally, a numerical example is presented to testify the main results.

Design of extended dissipative-based composite anti-disturbance reliable tracking control for stochastic Takagi–Sugeno fuzzy systems

This study focuses on examining the issues of extended dissipative-based composite anti-disturbance reliable tracking control for stochastic Takagi–Sugeno fuzzy systems afflicted by sensor faults and multiple disturbances. Explicitly, the multiple disturbances include the autonomous Wiener process and non random noises with partly known information that are generated by an exogenous plant. To address the difficulty of estimating the non random disturbance while considering the partially known information, the study incorporates a fuzzy stochastic disturbance observer. Furthermore, to solve the output tracking issue of the system under consideration, a modified repetitive tracking control is implemented. Then, combining the methodologies of disturbance observer-based control technique with modified repetitive control, a composite anti-disturbance reliable tracking control strategy is developed for achieving the intended tracking goal despite the multiple disturbances and sensor faults encountered. Additionally, the proposed approach involves extended dissipativity scheme, which includes H ∞ , passivity, dissipativity, and L 2 − L ∞ performances in a unified framework. In particular, by employing Lyapunov–Krasovskii functional approach, the essential stability criteria for the proposed closed-loop system are articulated in the form of linear matrix inequalities. Additionally, numerical illustrations are presented to exemplify the application and efficiency of the developed control protocol.

Reduced-Order Sliding Mode Observer-Based Backstepping Integral Logarithmic Sliding Mode Control: Application to Wing Aeroelastic System

Reduced-Order Sliding Mode Observer-Based Backstepping Integral Logarithmic Sliding Mode Control: Application to Wing Aeroelastic System

Compensation Function Observer-Based Backstepping Sliding-Mode Control of Uncertain Electro-Hydraulic Servo System

Observer-based control is the most commonly used method in the control of electro-hydraulic servo system (EHSS) with uncertainties, but it suffers from the drawback of low accuracy under the influence of large external load forces and disturbances. To address this problem, this paper proposes a novel compensation function observer-based backstepping sliding-mode control (BSMC) approach to achieve high-accuracy tracking control. In particular, the model uncertainties, including nonlinearities, parameter perturbations and external disturbances are analyzed and treated together as a lumped disturbance. Then, a fourth-order compensation function observer (CFO) is constructed, which fully utilizes the system state information to accurately estimate the lumped disturbance. On this basis, the estimate of the lumped disturbance is incorporated into the design of a backstepping sliding-mode controller, allowing the control system to compensate for the disturbance effect. The stability of the closed-loop control system under the CFO and BSMC is rigorously proven through the use of the Lyapunov theory, which guarantees that all the tracking error signals converge exponentially to the origin. Comparative simulations are carried out to show the effectiveness and efficiency of the proposed approach, i.e., compared with PID and ESO-based BSMC methods, the tracking accuracy is respectively improved by 94.86% and 88.19% under the influence of large external load forces and disturbances.

Multi-bandwidth observer-based adaptive robust pressure control for electro-hydraulic brake system with uncertainties and measurement noise

Accurate pressure regulation of electro-hydraulic brake system (EHB) is essential for enhancing braking performance in automobiles. However, component wear and pressure measurement noise can cause model parameters and controlled states to drift, resulting in system chattering. This nonlinear and uncertain state can significantly degrade pressure control performance. Motivated by this, the article presents a controlled state reconstruction-based adaptive robust pressure control technique with noise suppression. Firstly, a reduced dynamics model is established for controller design, which effectively captures the fundamental characteristic of the EHB. Secondly, a multi-bandwidth extended state observer (MBESO) capable of noise suppression is designed to reconstruct controlled states, including unknown disturbances and unmeasured pressure change rates of the EHB. Thirdly, an MBESO-based adaptive robust pressure control technique is introduced, where the control gain and robust factor are updated based on control and observation errors. In addition, the overall performance of the proposed control strategy is analyzed in the frequency domain, and close-loop stability is demonstrated via the Lyapunov method. Finally, the pressure control precision and robustness of the proposed algorithm are validated in both dynamic and static scenarios through sinusoidal and step-response experiments on a hardware-in-loop test bench. The results indicate that the proposed algorithm reduces dynamic pressure-tracking error by up to 62% compared to traditional method under sinusoidal conditions, with steady-state error remaining within 1 bar under step-response conditions.

Distributed Disturbance Observer-Based Containment Control of Multi-Agent Systems with Event-Triggered Communications

This article investigates a class of multi-agent systems (MASs) with known dynamics external disturbances, where the communication graph is directed, and the followers have undirected connections. To eliminate the impacts of external disturbance, the technologies of disturbance observer-based control are introduced into the containment control problems. Additionally, to save communication costs and energy consumption, a distributed disturbance observer-based event-triggered controller is employed to achieve containment control and reject disturbance. Furthermore, designing the event-triggered function using an exponential function is beneficial for a time-dependent term while ensuring the exclusion of Zeno behavior. Finally, a numerical simulation is provided to validate the effectiveness of the theoretical analysis.

Observer-based impulsive control for finite-time synchronization of delayed neural networks on time scales

Observer-based impulsive control for finite-time synchronization of delayed neural networks on time scales

Robust adaptive impedance control of coordinated electrically driven robots: An engineering application for the (p,q)-analogue of Bernstein-Stancu operators

Function approximation techniques have emerged as influential mathematical tools for designing compliant motion controllers capable of managing objects using multiple electrical manipulators without the need for exact models. However, their effectiveness often relies on having access to velocity signals, which may not always be practical in real-world situations. This paper introduces an observer-based robust adaptive impedance control strategy that employs the (p,q)-analogue of Bernstein-Stancu operators as uncertainty estimators to tackle uncertainties in collaborative multiple electrical manipulators. This approach leverages visual task-space information and doesn’t depend on velocity feedback, enhancing cost-effectiveness and applicability in practical robotic systems. The lumped uncertainty is first modeled by this operator. The adaptation laws, derived from stability analysis, are then employed to tune its coefficients, which are not presented in the previous literature. By applying the Lyapunov lemma, the paper ensures that error signals in the controlled system are uniformly ultimately bounded (UUB). The suggested controller is evaluated in a system featuring two arms managing a rigid load. Simulation results showcase the effectiveness and versatility of the proposed approach. The outcomes are also compared with two advanced approximation techniques to demonstrate the precision and effectiveness of the suggested controller design.

Observer-based Event-triggered Fuzzy Control for Switched Multi-agent Systems with State Constraints and Sensor Faults

Observer-based Event-triggered Fuzzy Control for Switched Multi-agent Systems with State Constraints and Sensor Faults

Observer-based iterative learning control with varying iteration lengths and alignment condition

Observer-based iterative learning control is developed in this paper to meet nonlinear systems with alignment condition and varying iteration lengths. Alignment condition is treated by a modified reference trajectory to achieve spatial closed-loop. Virtual forms of estimation error and tracking error are provided to handle varying iteration lengths. An adaptive observer based controller is constructed in terms of two tracking error feedback and three compensation parts for reference trajectory, state estimation and parameter estimation. Convergence of the errors is guaranteed in the framework of the composite energy function. Finally, a comparative simulation is presented to demonstrate the advantage of the proposed algorithm.

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.

Robust Predefined Output Containment for Heterogeneous Nonlinear Multiagent Systems Under Unknown Nonidentical Leaders' Dynamics.

This article discusses the robust predefined output containment (RPOC) control problem for heterogeneous nonlinear multiagent systems having multiple uncertain nonidentical leaders. In order to solve this problem, a new kind of distributed observer-based RPOC control framework is presented. First, for obtaining the information of nonidentical leaders' dynamics, including uncertain parameters in leaders' system matrices, output matrices, states, and outputs, four kinds of adaptive observers are constructed in a fully distributed form without any knowledge of the dynamics of nonidentical leaders, exactly. Second, on the basis of adaptive learning technique, a new RPOC controller is then developed by using the presented observers, where the adaptive observers can make up for the uncertain parameter in followers' dynamics, and the solutions of output regulation equations can be obtained adaptively by the developed adaptive strategy. Furthermore, with the help of the output regulation method and Lyapunov stability theory, the RPOC criteria for the considered system under unknown nonidentical leaders' dynamics are derived from the constructed controller. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed RPOC controller.

Compensation Function Observer-based Adaptive Anti-swing Control for Quadrotor Slung-load System With Constrained Flight States

Compensation Function Observer-based Adaptive Anti-swing Control for Quadrotor Slung-load System With Constrained Flight States

Adaptive Disturbance Observer-Based Local Fixed-Time Sliding Mode Control With an Improved Approach Law for Motion Tracking of Piezo-Driven Microscanning System

Adaptive Disturbance Observer-Based Local Fixed-Time Sliding Mode Control With an Improved Approach Law for Motion Tracking of Piezo-Driven Microscanning System

Observer-Based Adaptive Fuzzy Control for Singular Systems with Nonlinear Perturbation and Actuator Saturation

Observer-Based Adaptive Fuzzy Control for Singular Systems with Nonlinear Perturbation and Actuator Saturation

Ultimate bounded observer-based control of electrical vehicle driven by DC motor system with unmatched load torque

Ultimate bounded observer-based control of electrical vehicle driven by DC motor system with unmatched load torque