Observer-based Control Scheme Research Articles

Observer-Based Decentralized Tracking Control with Preview Action for a Class of Nonlinear Interconnected Systems

In this paper, for the first time, the observer-based decentralized output tracking control problem with preview action for a class of interconnected nonlinear systems is converted into a regulation problem for N augmented error subsystems composed of the tracking error dynamics, the difference equation of the state observer, and the available future reference trajectory dynamics associated with each individual subsystem. The developed innovative formulation of an observer-based decentralized preview tracking control scheme consists of the integral control action, the observer-based state feedback control action, and the preview action of the desired trajectory. The controller design feasibility conditions are formulated in terms of a linear matrix inequality (LMI) by using the Lyapunov function approach to ensure the existence of the suggested observer-based decentralized control strategy. Furthermore, both decentralized observer gain matrices and decentralized tracking controller gain matrices can be efficiently and simultaneously computed through a one-step LMI procedure. Stability analysis of the closed-loop augmented subsystem is carried out to illustrate that all tracking errors asymptotically converge toward zero. Finally, a numerical example is provided to demonstrate the effectiveness of the suggested control approach.

Observer-Based Adaptive Sliding Mode Control for Nonlinear Stochastic Markov Jump Systems via T–S Fuzzy Modeling: Applications to Robot Arm Model

In this article, the issue of sliding mode control for nonlinear stochastic Markovian jump systems with uncertain time-varying delay is investigated. Considering the system state measurements and the state-dependent disturbances are not available for feedback purposes, an observer-based adaptive control strategy is proposed. Based on the decomposition of the input matrices, the state-space representation of the system is turned into a regular form with the aid of T-S fuzzy models first. Then, a fuzzy observer system is constructed, which could be transformed into two lower order subsystems. By choosing a common linear switching surface, on which it also obtains linear sliding mode dynamics in a simple form. Further, an adaptive controller is synthesized relying on the bounded system delay information to ensure the estimated states driven on the predefined sliding surface and remain the sliding motion. Also, the stochastic stability analysis of the sliding mode dynamics is undertaken with two types of transition rates, and an interesting result reveals that the stability for the dynamics with type of uncertain transition rates may cover the completely known type. Finally, a single-link robot arm model is provided to verify the validity of the proposed method.

Disturbance Observer-Based Integral Backstepping Control for a Two-Tank Liquid Level System Subject to External Disturbances

A novel method of disturbance observer-based integral backstepping control is proposed for the two-tank liquid level system with external disturbances. The problem of external disturbances can be settled in this paper. Firstly, the mathematical model of the two-tank liquid level system is established based on fluid mechanics and principle of mass conservation. Secondly, an integral backstepping control strategy is designed in order to ensure liquid level tracking performance by making the tracking errors converge to zero in finite time. Thirdly, a disturbance observer is designed for the two-tank liquid level system with external disturbances. Finally, the validity of the proposed method is verified by simulation and experiment. By doing so, the simulation and experimental results prove that the scheme of disturbance observer-based integral backstepping control strategy can suppress external disturbances more effective than the disturbance observer-based sliding mode control method and has better dynamic and steady performance of the two-tank liquid level system.

Fuzzy Observer-Based Dynamic Surface Control for Input-Saturated Nonlinear Systems and its Application to Missile Guidance

In this paper, a fuzzy observer-based tracking control scheme is proposed for a class of strict-feedback uncertain nonlinear system with input saturation. To facilitate the fuzzy logic system (FLS) design, the original uncertain nonlinear system is transformed into an output feedback system firstly. Then, an adaptive state observer is constructed. In order to efficiently tackle the input saturation, an auxiliary system (AS) is introduced. Using the estimated states and AS, the dynamic surface control (DSC) strategy is developed based on backstepping method. Under the DSC scheme, the tracking control problem is reduced to optimal regulation problem of an affine system. Subsequently, an adaptive dynamic programming (ADP) based optimal control scheme is proposed. The stability of the overall system is guaranteed by Lyapunov theory. Finally, guidance simulation is made to confirm the effectiveness of the developed control method.

Disturbance Observer Based Tracking Control of Quadrotor With High-Order Disturbances

In this paper, the flight control of an unmanned aerial vehicle (UAV), quadrotor, in the presence of high-order disturbances is presented. Since during flight, UAV faces enormous, and various kinds of disturbance, the effect of such disturbances becomes vital for consideration during the development of disturbance observer (DO) based tracking control scheme. To obtain the desired tracking performance, standard sliding mode control (SMC) method is utilized while for disturbance estimation, DO based on Simpson's approximation is developed and incorporated with SMC. Furthermore, in this paper, both matched and mismatched disturbances are considered. Hence, a matrix associated with disturbances is invoked in the system model. To show the effective and desired control performance of developed disturbance observer-based control (DOBC) scheme, extensive simulations are conducted, followed by presenting the results in the paper.

Disturbance Observer-Based Finite-Time Speed Control for Marine Diesel Engine With Input Constraints

In this article, a finite-time observer-based speed control strategy for the marine diesel engine is proposed with consideration of system parameter uncertainties, external disturbances and input constraints. Initially, a finite-time disturbance observer is designed, by which the synchronized uncertainties are accurately estimated in the sense of finite-time stability. Based on the observed information, a speed control strategy is proposed, and practical finite-time stability of the closed-loop system is demonstrated by rigorous theoretical analysis. Besides, for solving the input constraints inherent with the speed control system, an auxiliary variable is introduced to compensate the extra part of control output signals. Finally, numerical simulation and comparison are presented. The common operation situations of the marine diesel engines are taken into account, including starting, acceleration and deceleration between speed set points, sudden load changing, varied propulsion system parameters and different slope limits, etc. Comparing with the related existing method, the effectiveness and advantages of the proposed finite-time observer-based control law are illustrated.

Robust Voltage Control in Inverter-Interfaced Microgrids Under Plug-and-Play Functionalities

In this article, a new scheme of designing decentralized extended proportional derivative (DEPD) controllers with combining novel disturbance observers is proposed for the issue of voltage control in islanded inverter-interfaced microgrids. A microgrid system under plug-and-play (PnP) functionality is described by an uncertain linear time-invariant system, and then, the stability of microgrid system is studied for voltage regulation based on the robust control theory and linear matrix inequality. The DEPD controller and the proposed disturbance observers are capable of minimizing undesirable oscillations in PnP operation of distributed generators and topology changes. To attenuate the effects of disturbances and uncertainties, a new nonlinear disturbance observer-based control strategy is provided in this article. The new disturbance observers proposed in this article can estimate any disturbances such as constant, harmonic, random walk, and any time-varying disturbances with slow varying rate. Some case studies and numerical simulations are investigated for evaluating the new control scheme via the MATLAB software. Simulations effectively validate the performance of the proposed approach.

Observer-based load current sensorless control strategy of inverter circuit in three-phase UPS

A load current sensorless control strategy using an optimized observer is designed for a three-phase online transformer-based UPS. A closed-loop observer containing state feedback is constructed based on the improved state space model of the inverter circuit. A simple feedback matrix design method is then applied to the observer according to the dead-beat control law, and the load current feedforward control scheme is reconstructed using the proposed observer. This control strategy can save three load current sensors, reduce the THD of the output voltage, and improve dynamic performance. The effectiveness of this strategy is verified by conducting simulation and experiment in a 10 kVA UPS.

Observer-Based Fuzzy Control for Four-Wheel Independently Driven Electric Vehicles with Active Steering Systems

This paper presents an observer-based control strategy to improve the maneuverability and stability performance of four-wheel independently driven electric vehicles with active front-wheel steering systems. Since the system states are difficult to be measured directly, a novel observer is designed to estimate the vehicle yaw rate and lateral velocity simultaneously. Takagi–Sugeno fuzzy model is used to handle the time-varying parameters of the vehicle model. Based on Lyapunov function theory, stability conditions of the closed-loop system are derived. The fuzzy $$H_{\infty }$$ controller is designed to make the resulting T–S fuzzy system asymptotically stable and satisfy $$H_{\infty }$$ performance under given constraints. Simulation results are given to demonstrate the validity of the presented control method.

Multirate iterative learning disturbance observer with robustness to frequency deviation for high precision attitude stabilization of flexible spacecraft subject to complex disturbances

High precision attitude stabilization of spacecraft is essential for the operation of precision instruments onboard. However, attitude vibrations of spacecraft are inevitably induced by complex disturbances. Disturbance observer based control scheme (DOBC) is a promising anti-disturbance technique, while it is restricted by the inadequate estimation performance of conventional disturbance observers for complex disturbances when taking structural complexity and noise sensitivity into account. To achieve high performance attitude stabilization of spacecraft subject to complex disturbances, a multirate iterative learning disturbance observer (MILDO) based controller is designed in this paper. Firstly, an augmented disturbance model is constructed in view of the periodicities of disturbances with known fundamental frequencies. Then, a generic proportional-derivative type MILDO (PD-MILDO) is designed by using previous disturbance estimates to update current estimates. The gain tuning method and the disturbance estimation performance of PD-MILDO are also presented. It is demonstrated that accurate disturbance estimation for low-frequency disturbance and multiple periodic disturbances can be achieved by PD-MILDO. Besides, the robustness of PD-MILDO to undesired frequency deviation can be significantly improved by introducing the proportional-derivative correction terms. Based on MILDO, a feedback controller is then designed to stabilize the spacecraft attitude. In the concept of DOBC, the controller and observer can be tuned independently. Finally, the effectiveness of the proposed control scheme is verified by simulations.

Control Synthesis for Discrete-Time T–S Fuzzy Systems Based on Membership Function-Dependent $H_{\infty }$ Performance

This article focuses on disturbance attenuation problem for discrete-time Takagi-Sugeno (T-S) fuzzy systems. First, a membership function-dependent H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance index is proposed, by which, different performance can be achieved for local subsystems. Then, the better performance may be obtained for the T-S fuzzy system that works on a particular local subsystem most of the time. It may guarantee better control effects in practical engineering applications. With the help of the newly defined performance index and fuzzy Lyapunov functions, an observer-based feedback control scheme is presented in the form of linear matrix inequalities. In simulation, the performance index obtained by this article can be improved by about 10% than that obtained by the traditional H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control method.

Observer-based adaptive neural tracking control for output-constrained switched MIMO nonstrict-feedback nonlinear systems with unknown dead zone

In this paper, the issue of adaptive neural tracking control for uncertain switched multi-input multi-output (MIMO) nonstrict-feedback nonlinear systems with average dwell time is studied. The system under consideration includes unknown dead-zone inputs and output constraints. The uncertain nonlinear functions are identified via neural networks. Also, neural networks-based switched observer is constructed to approximate all unmeasurable states. By means of the information for dead-zone slopes and barrier Lyapunov function (BLF), the problems of dead-zone inputs and output constraints are tackled. Furthermore, dynamic surface control (DSC) scheme is employed to ensure that the computation burden is greatly reduced. Then, an observer-based adaptive neural control strategy is developed on the basis of backstepping technique and multiple Lyapunov functions approach. Under the designed controller, all the signals existing in switched closed-loop system are bounded, and system outputs can track the target trajectories within small bounded errors. Finally, the feasibility of the presented control algorithm is proved via simulation results.

Observer-Based Adaptive Fuzzy Containment Control for Multiple Uncertain Nonlinear Systems

The adaptive fuzzy containment control problem is addressed for multiple uncertain nonlinear strict-feedback systems with immeasurable states and multiple leaders under directed communication graphs. By utilizing fuzzy logic systems to model the followers’ dynamics, a distributed fuzzy state observer is designed for the state estimation using only the relative position information. Then, an observer-based containment control scheme is constructed by the adaptive fuzzy control technique as well as the command filter. The filtering error loop is introduced to compensate the error arising from the command filter. The proposed adaptive fuzzy containment control scheme guarantees that all followers are driven into the dynamic convex hull spanned by the leaders with a bounded containment error, if there exists at least one of the leaders who has a directed path to the follower. Simulation results are given to illustrate the control performance of the proposed containment control method.

Adaptive Fuzzy Event-Triggered Control for Stochastic Nonlinear Systems With Full State Constraints and Actuator Faults

In this paper, an adaptive fuzzy output feedback control problem is investigated for a class of stochastic nonlinear systems in which the fuzzy logic systems are adopted to approximate the unknown nonlinear functions. A reduced-order observer and a general fault model are designed to observe the unavailable state variables and describe the actuator faults, respectively. An event-triggered control law is developed to reduce the communication burden from the controller to the actuator. Meanwhile, the barrier Lyapunov functions are constructed to guarantee that all the states of the stochastic nonlinear system are not to violate their constraints. Furthermore, an observer-based adaptive fuzzy event-triggered control strategy is proposed for the full-state-constrained nonlinear system with actuator faults based on backstepping technique, which can guarantee that all the signals in the closed-loop system are bounded and the tracking error converges to a small neighborhood of the origin in a finite time. Finally, simulation results are given to illustrate the effectiveness of the proposed control scheme.

Robust finite-horizon stability and stabilization for positive switched FM-II model with actuator saturation

In this paper, robust finite-horizon stability and stabilization problems are investigated for a class of Fornasini–Marchesini second (FM-II) type positive switched systems with actuator saturation. Firstly, finite-horizon stability is analyzed for the addressed 2-D model by utilizing the mode-dependent average dwell time method. Secondly, the traditional state feedback control idea is introduced in the system, and sufficient criteria are derived to guarantee the resulting closed-loop system to be positive and finite-horizon stable. Then, an observer-based control scheme is implemented, where the observer is presented to make the system finite-horizon stabilizable. Explicit controller design schemes are also presented for both of these two types of controllers. Finally, two illustrative examples are provided to show effectiveness of the theoretical criteria.

Event-Triggered Sliding Mode Control of Discrete-Time Markov Jump Systems

This paper studies the problem of event-triggered sliding mode control of discrete-time Markov jump systems (MJSs). Two kinds of classical control schemes, which are observer-based control and state-feedback control schemes, are employed to handle the proposed synthesis problem. The event-triggered observer-based sliding mode controller and event-triggered state-feedback sliding mode controller are established by plunge of discrete-time event detectors into the studied control system, respectively. Moreover, the proposed event-triggered sliding mode controllers can guarantee the MJSs to be stochastically stable with ${H}_{\infty}$ performance, and ensure the finite-time reachability of the specified sliding manifold. Simulation results are provided to illustrate the effectiveness of the proposed theoretical results.

Observer-Based PIGC for Missiles With Impact Angle Constraint

In this paper, we present an observer-based partial integrated guidance and control (PIGC) scheme for missiles to achieve hit-to-kill attack at a given impact angle. This is particularly useful as the lethality of a missile can be maximized if collision occurs at a certain angle. A novel sliding mode observer is proposed to estimate all states of the system in finite time, from which the PIGC is designed to make all states converge to zero and achieve the objective. The observer parameters are automatically updated by adaptive laws, which removes the requirement of knowing the bound of disturbances and hence making the scheme more applicable to real missile systems.

Observer-based H∞ fault-tolerant attitude control for satellite with actuator and sensor faults

This paper investigates the fault-tolerant attitude stabilization control problem for the satellite system subject to actuator failures, sensor failures and external disturbances. First, the H∞ observer is designed to estimate both system states and faults simultaneously. In order to reduce the effect of faults or failures, an auxiliary observer is introduced to improve the observation precision. Exploiting a novel auxiliary variable, the unavailable term in auxiliary observer is eliminated and the real observer is achieved. Second, the observer-based output feedback fault-tolerant control scheme is proposed for the satellite systems to handle actuator and sensor faults, which can stabilize the attitude angle and angular velocity with high precision. Finally, the effectiveness of proposed method is demonstrated via the simulation experiments.

Observed-based adaptive finite-time tracking control for a class of nonstrict-feedback nonlinear systems with input saturation

This paper concentrates upon the problem of adaptive neural finite-time tracking control for uncertain nonstrict-feedback nonlinear systems with input saturation. The design difficulty of non-smooth input saturation nonlinearity is solved by applying a smooth non-affine function to approximate the saturation signal. Neural networks, as a kind of specialized function estimators, are used to estimate the uncertain function. Meanwhile, a neural network-based observer is constructed to observe the unavailable states, and thus an observer-based adaptive finite-time tracking control strategy is developed by combining dynamic surface control (DSC) technique and backstepping approach. Furthermore, the stability of the considered system is analyzed via semi-global practical finite-time stability theory. Under the proposed control method, all the signals in the closed-loop system are bounded, and the system output can almost surely track the desired trajectory within a specified bounded error in a finite time. In the end, two examples are adopted to illustrate the validity of our results.

Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance

In this study, a new neural observer-based dynamic surface control scheme is proposed for the path following of underactuated unmanned surface vessels in the presence of input saturation and time-varying external disturbance. The dynamic surface control technique is augmented by a robust adaptive radial basis function neural network and a nonlinear neural disturbance observer. Radial basis function neural network is employed to deal with system uncertainties, and the nonlinear neural disturbance observer is developed to compensate for the unknown compound disturbance that contains the input saturation approximation error and the external disturbance. Moreover, the stringent known boundary requirement of the unknown disturbance constraint is eliminated with the proposed nonlinear neural disturbance observer. Meanwhile, to deal with the non-smooth saturation nonlinearity, a new parametric hyperbolic tangent function approximation model with arbitrary prescribed precision is constructed, which results in the transient performance improvement for the path following control system. Stability analysis shows that all the signals in the closed-loop system are guaranteed to be ultimately bounded. Comparative simulation results further demonstrate the effectiveness of the proposed control scheme.