Actuator Failure Compensation Research Articles

Adaptive Actuator Failure Compensation Control of Uncertain Nonlinear PDE–ODE Cascaded Systems

Adaptive Actuator Failure Compensation Control of Uncertain Nonlinear PDE–ODE Cascaded Systems

Adaptive Actuator Failure Compensation Control: A New Scheme Based on Fault Detection and Isolation

In flight control systems, multiple actuator stuck (or hardover) failures would cause saturation of the remaining healthy actuators and result in system instability. In this article, a new adaptive actuator failure compensation control scheme is proposed for a class of nonlinear systems with multiple redundant inputs. Under a mild assumption on the time interval between two successive failures, an online fault detection and isolation (FDI) algorithm is introduced, with which an actuator failure can be exactly identified in a given finite time without using the persistent excitation (PE) condition. The main advantage of the proposed scheme is that with the help of the FDI algorithm, an actuator with stuck failure (SF) can be deactivated before a new failure occurs and therefore, the drawback of the current adaptive failure compensation control approach that may cause more control effort or even saturation with multiple actuators being stuck can be overcome.

A switching-free multiple-model approach for adaptive FTC of non-Lipschitz nonlinear uncertain systems under persistent actuator failures

A novel actuator failure compensation scheme is proposed for affine nonlinear uncertain systems (not necessarily Lipschitz) subject to persistent/intermittent actuator faults/failures unknown in time, magnitude and pattern. The proposed control methodology satisfies the nonlinear separation principle through a modular backstepping control. The controller is then augmented with multiple estimation models to estimate failure induced parametric uncertainties and unknown system parameters. The output transient performance at start up and post-failure instances, is improved on account of a two layer adaptation which enhances the convergence speed and accuracy of parameter estimates. The proposed fault tolerant control (FTC) method yields a faithful accommodation of uncertain finite as well as infinite/intermittent/persistent actuator failures while ensuring satisfactory output transient and steady state performances. Further, compared to existing multiple model based adaptive fault tolerant control design for nonlinear systems, the proposed methodology circumvents the issues of stability due to switching between different models and utilizes a minimum number of estimation models for parameter estimation without compromising on the output performance. Consequently, the computational burden is also reduced. Compared to multiple model adaptive control based FTC strategies proposed earlier which assume finite actuator failures and Lipschitz nonlinear system, the proposed method is applicable to both Lipschitz and non-Lipschitz nonlinear systems affected by intermittent actuator failures. Using the concepts from stability analysis in random nonlinear impulsive systems, the L∞ and L2 bounds on tracking error for all future time are derived in the case of intermittent/persistent actuator failures obtained using the proposed fault-tolerant controller. The improvement of output transient performance in the proposed control scheme in comparison with controller with single identifier, is theoretically proved and quantified.

Fractional order robust adaptive control design for actuator failure compensation in dual ball-beam system

This paper is to proposes a fractional order adaptive control scheme design for actuator failure compensation in order to balance of a ball-beam system with redundant actuators. The proposed controller is based on a fractional order sliding surface from which an adaptive actuator failure compensation control scheme is obtained. In order to control the dual ball-beam system with redundant motors, a linearized model is derived, which is subjected to actuator failures. A set of numerical simulation tests representing few selected types of actuator failures scenarios are carried out to assess the output tracking performance of the proposed controller design when dealing with such failures

Adaptive Actuator Failure Compensation on the Basis of Contraction Metrics

This letter develops an adaptive actuator failure compensation method for nonlinear systems with unmatched parametric uncertainty based on contraction metrics. The proposed method, which is constructed by benefiting from the recent achievements on contraction metrics based adaptive control techniques, ensures the closed-loop stability and asymptotic tracking of the desired trajectory in the presence of actuator failures. In particular, a sufficient convex condition is derived for constructing a valid metric, by which a quadratic program-based controller is obtained to determine the inputs of the actuators. The introduced method is more general than the common adaptive actuator failure compensation methods, as it does not require the system to have an identical relative degree for all inputs and be transformable into the parametric strick-feedback or feedback linearization form. Besides, it can be enriched with learning-based algorithms and common robust modifications. Simulation results are presented to verify the effectiveness of the proposed controller.

Adaptive Compensation of Persistent Actuator Failures Using Control-Separation-Based LQ Design

Persistent actuator failures can cause uncertain system dynamics mutation including minimum and nonminimum phase switching, which motivates us to develop a robust adaptive control scheme using a control-separation-based linear quadratic (LQ) design. It is shown that such a system can be expressed by a parameterized time-varying input–output model plus an actuator failure dependent signal and a persistent signal which captures the effect of the system dynamics mutation. A control-separation LQ design has the specific desired functions for output regulation and failure compensation as well, and is applied and analyzed for solving the persistent actuator failure compensation problem. Both nominal control design for system known and adaptive control design for system unknown are developed. The desired control performance is ensured by a robust adaptive control technique and is fully characterized in terms of a small in the mean output regulation, that is, the mean value of the system output is bounded by the average number of actuator failures over time and the average actuator failure value. Such desired system performance is shown by a complete analytical study and demonstrated by an illustrative simulation study.

Adaptive actuator fault-tolerant control for non-minimum phase air-breathing hypersonic vehicle model

In this paper, the tracking control problem of non-minimum phase flexible air-breathing hypersonic vehicles (AHSV) is investigated subject to actuator fault, external disturbances and parameters uncertainties. The study is began with a series of control-oriented manipulations: first, the input–output dynamics are derived by using feedback linearization method and the internal dynamics of AHSV are constructed; then, the zero dynamics stability analysis is conducted to verify the non-minimum phase characteristic of AHSV. In order to realize output tracking of the non-minimum phase system with sufficient accuracy, an adaptive fault tolerant controller (FTC) is proposed based on an output-redefinition making the zero-dynamics with respect to the new output stable. Additionally, robust adaptive laws are utilized for the estimation of unknown parameters and actuator failure compensation of the AHSV model. Furthermore, the stability of the closed-loop system is analyzed based on the Lyapunov stability theory. At last, the numerical simulation results are provided to demonstrate the effective tracking performance of the proposed FTC scheme.

Adaptive Fuzzy Actuator Failure Compensation Control for a Class of MIMO Nonlinear Systems

In this paper, an adaptive fuzzy control scheme is developed for a class of uncertain multi-input multi-output (MIMO) nonlinear systems with uncertain actuator failures. Within this scheme, a fixed grouping of redundant actuators and a proportional actuation scheme for each group are considered. Afterward, a fuzzy system is used for the online approximation of a nominal control vector. The parameter adaptation laws for the nominal controller are driven by the prediction error, which is defined as the difference between the unknown nominal controller and the fuzzy controller. The proposed controller can compensate for both total and partial loss of effectiveness failure types. Closed-loop system stability and convergence properties of the tracking errors are proved based on Lyapunov theory. A piecewise analysis is carried out to prove that these properties hold despite the presence of parameter jumps caused by abrupt failures. A simulation study is carried out on a redundant joint two-link robot manipulator with joint failures at each link. Simulation results show the effectiveness of the proposed control scheme.

Adaptive actuator failure compensation for cooperative robotic manipulators with parameter uncertainties

SummaryThis article develops a new framework of adaptive actuator failure compensation control for cooperative manipulator systems with parameter uncertainties in addition to actuator failures, and designs and analyzes effective actuator failure compensation schemes for such robotic systems. The new adaptive control design uses an integration of multiple individual failure compensators and direct adaptation to handle various types of uncertainties in such robotic systems. The design can also be used for concurrent actuator failure cases, to expand the capability of adaptive actuator failure compensation. With a complete proof and performance analysis, it is shown that the proposed control scheme guarantees the desired closed‐loop stability and asymptotic output tracking, despite actuator failures whose patterns, time instants and values are all unknown. Simulation results of a benchmark cooperative manipulator system are presented to verify the desired control performance of the system with both typical constant and square‐wave actuator failure signals.

Fractional adaptive SMC fault tolerant control against actuator failures for wing rock supervision

This article presents a new fractional order adaptive control scheme design based on sliding mode configuration for actuator failure compensation applied to a wing rock system with redundant actuators. The main objective of this work is to establish an adaptive control law that compensates faulty actuators by taking into account actuator redundancy and introducing fractional calculus. First, a non-integer sliding mode surface is defined. Next, an adaptive scheme is derived from the ideal control law to accommodate for the occurring failures during operation. Then, the stability analysis of the closed loop system is performed using the Lyapunov theory under certain assumptions on the system and the failures. Finally, simulations were carried out on a wing rock system subjected to various actuator failures scenarios in order to illustrate the effectiveness of the proposed control law.

Robust Adaptive Control Allocation for a Class of Cascade ODE-String Systems With Actuator Failures

A robust adaptive control allocation algorithm with actuator failure compensation is presented in this article for a class of cascade ODE-string systems depicted by ordinary differential equations (ODEs) and partial differential equations. The proposed control scheme including actuator fault compensation and allocation algorithm uniformly stabilizes the cascade ODE-string system in the presence of actuator faults, parameter uncertainties and environmental perturbations, and effectively reduces the controller complexity by adaptively grouping redundant actuators. Since this control method needs full-state measurement of the ODE system, it can be regarded as a state-feedback control instead of an output-feedback control. Control design and proof of the closed-loop system stability are implemented by Lyapunov’s direct method. Numerical simulations are finally analyzed to illustrate the feasibility of the proposed control scheme.

Robust Dynamic Actuator Failure Compensation Control of Nonlinear Systems via Cooperative Interaction Design

This article studies fault-tolerant resilient control (FTRC) problems for uncertain Takagi-Sugeno fuzzy systems when subjected to additive actuator faults and/or malicious injections on control input signals. The effects of faults and malicious injections are modeled by unknown bounded signals. The signals are produced by any finite- L2 -gain dynamical system and a Lipschitz and derivable function with respect to states, so that the considered fault model contains some reported ones as special cases. By employing the available state and input data, a function, which is equivalent to a fictitious dynamical system comprising the information about compensation errors for unknown actuator faults, is presented. Then, based on the virtual system, a novel actuator failure compensator (AFC) with the structure of dynamic feedbacks is proposed, so that the compensation capability is improved via cooperative interaction designs between the virtual dynamical systems and closed-loop systems. Furthermore, through the equivalence class and Lyapunov theories, it is proved that the presented robust dynamic AFC-based fuzzy controller ensures the asymptotic convergence of system states to zero. Different from the existing FTRCs, good transient performance is guaranteed, even in the presence of unforeseen actuator faults. Two illustrative examples verify the effectiveness of the presented method.

Linear Adaptive Fault Tolerant Control against Aircraft Actuator Failures for Wing Rock Suppression

In this paper we consider the problem of the suppression of wing rock phenomenon in presence of actuator faults. The main aim of this work is the application of a linear adaptive actuator failure compensation control scheme for wing rock motion of a slender delta wing. First, the analytical nonlinear model that characterizes the phenomenon of wing rock is given, and its behavior for different angles of attack is presented. Then, an adaptive actuator failure compensation redundant control design is proposed, and applied for a rolling motion regulation in the presence of actuator faults. Finally, numerical simulations are conducted to show the effectiveness of the control scheme for wing rock suppression for different actuator failures scenarios.

Adaptive Robust Failure Compensation Control for Servo System Driven by Twin Motors

In the context of failure control of servo system driven by twin motors, there are still no available results to compensate unknown actuator failures which seem inevitable in practice by adaptive backstepping technique. Therefore, to rise the reliability of the system, we aim at addressing such a problem by proposing an adaptive robust actuator failure compensation control scheme based on backstepping technique for servo system driven by twin motors. Unlike the traditional backstepping, the estimation of unknown coefficient of intermediate state variable is introduced in coordinate changes. In addition, matching and non-matching uncertainties have been fully considered in the controller design. Simulation results show that the designed controller can ensure the boundedness of all the signals no matter actuator failures occur or not.

Adaptive Actuator Fault Compensation and Disturbance Rejection Scheme for Spacecraft

An adaptive actuator failure compensation scheme is proposed for attitude tracking control of spacecraft with unknown disturbances and uncertain actuator failures. A new feature of this adaptive control scheme is the adaptation of the failure pattern parameter estimates, as well as the failure signal parameter estimates, for direct adaptive actuator failure compensation. Based on an adaptive backstepping control design, the estimates of the disturbance parameters are used to solve the disturbance rejection problem. Without the requirement of additional fault detection mechanism, the switching function is designed to automatically locate and turn off the unknown faulty actuators by observing a control performance index. The asymptotic stability of the system output in the presence of actuator failures is rigidly proved through standard Lyapunov approach, while the other signals of the closed-loop system are guaranteed to be bounded. Simulation results verify the desired adaptive actuator failure compensation performance.

Diagnosis and Compensation of Control Program, Sensor and Actuator Failures in Nonlinear Systems Using Hierarchical State Space Checks

Autonomous systems with nonlinear dynamics need to be extremely resilient to errors in sensors, actuators and on-board electronics for the purpose of overall vehicle safety. Prior research has focused on control-theoretic methods with significant computational burden with a focus on failures in actuation. In contrast, we propose the use of hierarchical machine learning driven state space checks that detect and diagnose errors in control program execution, sensors and actuators with high sensitivity and low latency. Each check produces a time-varying error signal that facilitates effect-cause diagnosis of the system, while allowing rapid parameter estimation from each check. Since the checks are over small subsets of system parameters, estimation is fast and accurate. The estimated parameters are then used to reconfigure the system controller parameters for rapid system recovery. We use a quadcopter system to demonstrate and validate our approach. Controller, sensor and actuator errors can be detected, diagnosed and compensated using a common checking platform with low computational overhead. The technique is validated on a quadcopter hardware test vehicle.

Adaptive actuator failure compensation for a class of nonlinear systems with full state constraints

AbstractIn this article, an adaptive compensation scheme is proposed for controlling a class of Brunovsky form systems with unknown parameters and possible actuator failures such that the full state constraints can be achieved. Compared with the previous research, the main advantage of the scheme is that by selecting a set of parameters related to the barrier Lyapunov functions, virtual control signals can be constrained within required boundaries. As a result, the full state constraints and tracking performance constraints can be achieved simultaneously even in the presence of actuator failures. It is shown that with this scheme, all the closed‐loop signals are bounded and the tracking error converges to a residue set that can be made arbitrarily small

Adaptive Actuator Failure Compensation Control Schemes for Uncertain Noncanonical Neural-Network Systems.

In this article, direct adaptive actuator failure compensation control is investigated for a class of noncanonical neural-network nonlinear systems whose relative degrees are implicit and parameters are unknown. Both the state tracking and output tracking control problems are considered, and their adaptive solutions are developed which have specific mechanisms to accommodate both actuator failures and parameter uncertainties to ensure the closed-loop system stability and asymptotic state or output tracking. The adaptive actuator failure compensation control schemes are derived for noncanonical nonlinear systems with neural-network approximation, and are also applicable to general parametrizable noncanonical nonlinear systems with both unknown actuator failures and unknown parameters, solving some key technical issues, in particular, dealing with the system zero dynamics under uncertain actuator failures. The effectiveness of the developed adaptive control schemes is confirmed by simulation results from an application example of speed control of dc motors.

Adaptive compensation of persistent actuator failures of nonlinear systems

SummaryIn this article, adaptive compensation designs are developed for nonlinear systems with uncertainties from the system functions and persistent actuator failures of characterizations that (i) some unknown system inputs are stuck at some unknown fixed or varying values at unknown time instants and (ii) the failure pattern always switches from one to another and the switching does not stop. Such a controlled plant is described by an uncertain time‐varying nonlinear system, and some robust adaptive feedback linearization based failure compensation results are studied for closed‐loop system stabilization and bounded output tracking for some specific conditions. To improve the tracking performance in the presence of persistent actuator failures, a new adaptive control scheme is developed, using the failure indicator function which contains the failure pattern and failure time in the formulation. Detailed stability and tracking performance are shown. Simulation results are shown to verify the effectiveness of the proposed adaptive actuator failure compensation method.

Disturbance Observer-Based Fault-Tolerant Control for Robotic Systems With Guaranteed Prescribed Performance

The actuator failure compensation control problem of robotic systems possessing dynamic uncertainties has been investigated in this paper. Control design against partial loss of effectiveness (PLOE) and total loss of effectiveness (TLOE) of the actuator are considered and described, respectively, and a disturbance observer (DO) using neural networks is constructed to attenuate the influence of the unknown disturbance. Regarding the prescribed error bounds as time-varying constraints, the control design method based on barrier Lyapunov function (BLF) is used to strictly guarantee both the steady-state performance and the transient performance. A simulation study on a two-link planar manipulator verifies the effectiveness of the proposed controllers in dealing with the prescribed performance, the system uncertainties, and the unknown actuator failure simultaneously. Implementation on a Baxter robot gives an experimental verification of our controller.