Loss Of Actuator Effectiveness Research Articles

A learning-based nearly optimal control framework for trajectory tracking of a flexible-link manipulator system with actuator fault

AbstractIn this paper, a learning-based nearly optimal control framework with fault-tolerant capability is designed to tackle the tracking control problem of a flexible-link manipulator in the presence of actuator fault and model uncertainties. Initially, the optimal control law is obtained by adopting the dynamic programming and a critic structure as the solution of Hamilton–Jacobi–Bellman equation for the nominal model. Then, by implementing an integral sliding mode control, the robustness against actuator fault and model uncertainty is guaranteed. The adaptive laws are constructed based on radial basis functions neural networks to estimate the upper bound of uncertainty and the actuator bias fault, satisfying both optimal performance and chattering reduction of the sliding surface. Furthermore, the actuator effectiveness loss is handled. The stability of the closed-loop system is analytically proven, and the performance of the proposed framework is investigated against several practical operating conditions. This incorporates the fidelity assessment of tracking precision and trackability of control signal using performance indices such as the integral absolute error and root-mean-square error. The results of extensive simulation studies confirm the effectiveness and robustness of the proposed control framework.

Resilience enhancement to loss of actuator effectiveness in a Model-Free Adaptive framework

Within the theoretical framework supporting the Model Free Adaptive Control approach, this paper investigates on the presence of possible loss of effectiveness affecting the actuator of a Single-Input Single-Output plant. In particular, stemming from a tracking controller proposed in a seminal paper and the related proofs, an identification algorithm is proposed for the estimation of the loss of effectiveness, with proved bounded estimation error, along with a condition for the detection of actuator faults. A fault-resilient tracking controller is finally proposed, based on the estimated loss of effectiveness, providing asymptotically vanishing tracking error. A comparative analysis by simulation on a benchmark system taken from the pertinent literature is also presented to validate the proposed development.

Adaptive Reinforcement Learning for Fault-Tolerant Optimal Consensus Control of Nonlinear Canonical Multiagent Systems With Actuator Loss of Effectiveness

Adaptive Reinforcement Learning for Fault-Tolerant Optimal Consensus Control of Nonlinear Canonical Multiagent Systems With Actuator Loss of Effectiveness

Fault-Tolerant Control of a Variable-Pitch Quadrotor under Actuator Loss of Effectiveness and Wind Perturbations

The actuator fault-tolerant control problem for a variable-pitch quadrotor is addressed under uncertain conditions. Following a model-based approach, the plant nonlinear dynamics are faced with a disturbance observer-based control and a sequential quadratic programming control allocation, where only kinematic data of the onboard inertial measurement unit are required for the fault-tolerant control, i.e., it does not require the measurement of the motor speed nor the current drawn by the actuators. In the case of almost horizontal wind, a single observer handles both faults and the external disturbance. The estimation of the wind is fed forward by the controller, while the actuator fault estimation is exploited in the control allocation layer, which copes with the variable-pitch nonlinear dynamics, thrust saturation, and rate limits. Numerical simulations in the presence of measurement noise show the capability of the scheme to handle multiple actuator faults in a windy environment.

Adaptive fault-tolerant control for spacecraft formation under external disturbances with guaranteed performance

This paper investigates an adaptive fault-tolerant control problem for spacecraft formation flying (SFF) with actuator faults, external disturbances, and unknown inertial uncertainties. First, fault factors are introduced to describe the SFF orbit model with consideration of actuator bias faults and loss of actuator effectiveness. Then, an adaptive fault-tolerant controller is proposed by incorporating prescribed performance function, improved terminal sliding mode control and the proposed adaptive law. Finally, rigorous theoretical analysis ensures the uniformly ultimately bounded stability of the system through Lyapunov theory and simulation verifies the proposed algorithm.

Integrated vehicle control using adaptive control allocation

SummaryThe focus of this paper is an integrated, fault‐tolerant vehicle control algorithm for the overall stability of ground vehicles. The proposed scheme comprises a high‐level controller that creates a virtual control input and a low‐level adaptive control allocator that distributes the virtual control effort among redundant actuators. The proposed control framework distinguishes itself from earlier results in the literature by its ability to blend active suspension, steering and traction control channels, in the presence of uncertainties and time‐varying dynamics, without the need for fault identification. The control structure is validated in the simulation environment using a fourteen‐degree‐of‐freedom non‐linear vehicle model. The integrated controller is compared to the case of a conventional control approach where each control problem is solved separately. Our results show that, compared to the conventional approach, the proposed method ensures that the vehicle follows driver inputs with up to % higher longitudinal maneuver velocity, despite the presence of actuator failures and slippery road conditions. Furthermore, to demonstrate the benefit of integrating active suspension control to the overall control scheme, we replaced the suspension control of the proposed approach with an independent suspension control system for comparison purposes. We then showed that the integrated case provided % lower roll angle deviation, and % lower pitch angle deviation, in the presence of actuator effectiveness loss and adverse road conditions.

Adaptive sliding mode based fault tolerant control of wheeled mobile robots

ABSTRACT In this paper, we propose an adaptive sliding mode-based fault tolerant control for mobile robots. While a mobile robot is tracking a given trajectory, several fault cases may occur, such as sensor model and controller faults, changes in the dynamic equation due to robot body shape or weight changes, and loss of actuator effectiveness. Disturbance signals are caused by the actuator faults and, for various reasons, can be considered the primary issue for the robots. In real-time applications, the Sliding Mode Controller (SMC) is insufficient if the robot parameters are unknown, the robot model is non-linear, and the overall system is subject to disturbances. An adaptive law is used to support the SMC to maintain the sliding surface and solve the problems of unknown system parameters, actuator faults, and disturbances. Besides SMC, the kinematic controller is also used, and its gain values are optimized using a neural network and a kinematic controller. The stability of the overall system is proven by using the Lyapunov theory. Besides actuator faults, the system is disturbed by defining a disturbance signal, which is added to the control signals. To show the effectiveness of the proposed controller, it is compared with traditional SMC and PID.

Spacecraft attitude fault-tolerant stabilization against loss of actuator Effectiveness: A novel iterative learning sliding mode approach

This paper investigates the attitude fault-tolerant stabilization problem for a spacecraft subjected to its actuator effectiveness loss, inertia uncertainties and space disturbances. A novel Iterative Learning Sliding Mode Observer (ILSMO) is proposed to reconstruct the actuator effectiveness factors robustly and accurately by combining the P-type iterative learning algorithm with the sliding mode approach. Based on the reconstructed fault signals, an Iterative Learning Sliding Mode Controller (ILSMC) is designed to guarantee the closed-loop spacecraft attitude fault-tolerant stabilization by compensating for its lumped disturbance. The ILSMO and ILSMC stabilities are guaranteed using the Lyapunov direct approach, respectively. Finally, the numerical simulation results show that the proposed ILSMO-ILSMC-based spacecraft attitude fault-tolerant stabilization method is effective and superior.

Effect of loss of control effectiveness on an inverted pendulum balanced on a moving quadrotor

This paper investigates the effect of loss of rotor effectiveness on the states of an inverted pendulum mounted at the center of mass of a moving quadrotor. An adaptive Model Predictive Controller is utilized to develop a controller that enables the quadrotor to track a circular trajectory while experiencing varied degrees of loss of actuator effectiveness. Nominal states of the quad-pendulum system on a circular trajectory are determined from the investigated dynamic equilibria. The performance of the developed fault tolerant controller against the pendulum states is compared with LQR performance in numerical simulations. Recommendations to improve performance against the observed errors are highlighted.

Adaptive sliding mode fault-tolerant attitude control for flexible satellites based on T-S fuzzy disturbance modeling.

This paper investigates the fault tolerance problem of flexible satellites subject to actuator faults and multiple disturbances. An adaptive sliding mode fault tolerant control (ASMFTC) approach based on Takagi-Sugeno (T-S) fuzzy disturbance observer (TSFDO) is presented for attitude control system (ACS) under loss of actuator effectiveness, environmental disturbance torque and elastic modal generated by flexible appendages. Compared with the traditional disturbance observer based control (DOBC) methods, the T-S fuzzy technology is applied to estimate the unknown nonlinear elastic modal. Then, the energy bounded disturbance is eliminated by designing an adaptive sliding mode controller. The proposed ASMFTC design can guarantee the sliding surface to approach zero. Finally, the effectiveness of the control method proposed in this paper is further verified by comparative simulation.

A hybrid scheme to improve transient and recover performance in a fault-tolerant control system with loss of actuator effectiveness

A hybrid scheme to improve transient and recover performance in a fault-tolerant control system with loss of actuator effectiveness

Observer-Based Predefined-Time Attitude Control for Spacecraft Subject to Loss of Actuator Effectiveness

The predefined-time tracking problem of spacecraft attitude systems with loss of actuator effectiveness and lumped disturbance including the external disturbance and system uncertainty is studied. In order to obtain the estimation of the actuator efficiency factor more quickly and accurately, a robust learning observer is designed. Based on the fault reconstruction information of the learning observer and the predefined-time stability lemma, a predefined-time tracking fault-tolerant control scheme is proposed for the faulty spacecraft attitude system. The stability of the learning observer and the whole control system is verified by the Lyapunov stability theory. Finally, the effectiveness and advantages of the proposed scheme are illustrated by simulation results including comparisons with existing works.

A Performance Evaluation and Analysis Method for Multi-Rotor UAV under Actuator LOE

Loss of Actuator Effectiveness (LOE) reduces the performance parameters of Multi-rotor Unmanned Aerial Vehicle (UAV), which affects the reliability of the mission. However, in practice, researchers used to evaluate the performance of a UAV through lots of flight experiments or by experience, which is normally inefficient and costly. In order to evaluate the performance of UAVs, this paper presents a performance evaluation and analysis method under actuator LOE. First, models are established for the components of a propulsion system, mainly including actuators and batteries. Second, the performance evaluation problem is simplified and decomposed into two sub-problems. performance indices are established by kinetic analysis and then solved, considering the influence of actuator LOE and battery performance. Finally, based on the analysis results, the evaluation method is demonstrated in several cases. The results showed that the evaluation method is effective compared with the simulation results of www.flyeval.com/. In addition, LOE reduces the performance parameters of the UAV, which has a greater impact on the maximum flight speed and maximum cruising distance.

Enhancing performance and stability of gain-scheduling control system using evolutionary algorithms: A case study on transport aircraft

An enhanced gain-scheduling control strategy was presented to establish a smooth adaptation mechanism for the longitudinal motion of B747 between different flight envelopes. The focal objective is to accomplish a smooth and non-conservative gain-scheduling control system that has high performance and stability characteristics for different flight conditions and transitions between them. The proposed approach ensured a successful gain scheduling control system by allocating a specific error performance index that should be minimized for all flight conditions. Then all required performance indices were cohered according to the flight envelope in the form of a multi-objective optimization problem that could be solved using evolutionary algorithms. The performance and stability of the transition points between different flight conditions were preserved through the sets of feasible solutions obtained by an evolutionary algorithm which are known as a set of Pareto optimal solutions. The proposed gain-scheduling system was built based on 2DoF-PID (Two-degree-of-freedom Proportional Integral Derivative) controller. An auto-decision-maker was developed to adjust the parameters of the 2DoF-PID gain-scheduling control system with the current flight condition. The effectiveness of the proposed gain-scheduling control structure was studied for two different multiobjective evolutionary-based optimizers known as fast sorting and elite multi-objective genetic algorithm.II (NSGA.II), and sub-population genetic algorithm.II (SPGA.II). The proposed methodology was evaluated by simulation results according to the quality of the pareto-front and transient response characteristics of the proposed gain-scheduling controller for the chosen flight conditions in normal flight conditions and 50% loss of actuator effectiveness.

Resilient anti-disturbance dynamic surface control of uncertain strict-feedback systems subject to partial loss of actuator effectiveness

This paper is concerned with the tracking control of a class of uncertain strict-feedback systems subject to partial loss of actuator effectiveness, in addition to uncertain model dynamics and unknown disturbances. A resilient anti-disturbance dynamic surface control method is proposed to achieve stable tracking regardless of partial actuator faults. First, data-driven adaptive extended state observers are designed based on memory-based identifiers, such that the uncertain model dynamics, external disturbances and the unknown input gains due to actuator faults can be estimated. Next, a resilient anti-disturbance dynamic surface controller is developed based on recovered information from the data-driven adaptive extended state observers. After that, it is proven that the cascade system formed by the observer and controller is input-to-state stable. Finally, comparative studies are performed to validate the efficacy of the resilient anti-disturbance dynamic surface control method for nonlinear strict-feedback systems subject to partial loss of actuator effectiveness.

Collision-avoiding formation for multiple Euler–Lagrange systems against external disturbances and actuator faults

In this paper, for multiple Euler–Lagrange systems embodying external disturbances and unknown uncertainties, the problems of collision-avoiding formation (CAF) are investigated. With regard to Euler–Lagrange systems under healthy actuator condition and under actuator failures, two distributed collision-avoiding formation (DCAF) control laws are proposed. In one case, which the systems are under healthy actuator condition, firstly, a robust continuous term with adaptive variable gain is utilized to reduce the influence of external disturbances under unknown range. In addition, in order to handle the uncertainties of dynamical systems and collision avoidance, both the estimations for uncertain terms and repulsive potential functions are established in design of algorithms. For the other case, the systems under actuator failures, by utilizing the Lyapunov function and relevant adaptive updating laws, the effects subjected to partial loss of actuator effectiveness can be eliminated. Eventually, two distributed algorithms are proposed to achieve the expected formation configuration with no collision occurred. Numerical simulations are conducted to illustrate the validities of the presented control methodologies.

Arttirimli doğrusal olmayan dinamik çevirmeye dayali bir quadrotor'un hata toleransli kontrolü

The multirotor unmanned aerial vehicles (UAVs) have rapidly attracted interest of the researchers since they play a unique role in a variety of areas including the military, agriculture, rescue, and mining. Actuator fault or failure is inevitable during multi-rotor’s operations, which can endanger humans on the ground in addition to costly damage to the system itself. Therefore, this paper introduces a nonlinear controller algorithm for fault-tolerant control of a quadcopter with partial loss of actuator effectiveness. The introduced controller includes a cascade structure of the fast inner-loop dynamics and slow outer-loop dynamics. In the inner-loop part of the controller, an incremental nonlinear dynamic inversion controller is applied and a modified PID control algorithm is used in the outer-loop of the controller. Simulation results for different fault scenarios demonstrate that the proposed fault-tolerant controller approach can quickly adapt itself to the abrupt change due to the motor faults and tracks the desired inputs satisfactorily.

Robust Fault-Tolerant Control for Stochastic Port-Hamiltonian Systems against Actuator Faults

Exploiting the stochastic Hamiltonian structure, this paper investigates the robust fault-tolerant control (FTC) for stochastic port-Hamiltonian systems (SPHSs) with actuator faults. First, an energy-based robust FT controller is developed for SPHSs against the loss of actuator effectiveness. Then, an alternative condition, as well as its corresponding controller are given to extend the application of the proposed controller. Unlike the existing FT controllers, they are continuous, and there is no need to solve the Lyapunov function and Hamilton–Jacobi–Isaacs (HJI) inequalities associated with the nominal systems. Finally, an energy-based robust adaptive FT controller is presented for the faulty SPHSs to deal with parameter perturbations, and an alternative condition with its corresponding controller is also given. Both the adaptive controllers preserve the main stochastic Hamiltonian structure of the faulty systems. Compared to the existing adaptive controller, simulations on synchronous generators show the effectiveness of the proposed methods.

Output-Only Measurements for Fault Detection of Multi-Actuator Systems in Motion Control Applications

This paper investigates actuator fault detection in linear systems with a number of actuators. We consider some of the most common actuator faults such as actuator loss of effectiveness and fatigue crack in the connection hinges. We use transmissibility operators, which are mathematical models that characterize the relationship between sensors in an underlying system, for fault detection of actuators. Transmissibilities identified under healthy conditions can be used along with measurements of healthy sensors to predict other sensors’ measurements without knowledge of the dynamics of the system or the excitation that acts on the system. We apply the proposed approach to an analytical model with twelve actuators, and an experimental setup consisting of twelve electromechanical actuators and two accelerometers.

Attitude Compensation Control for Quadrotor Under Partial Loss of Actuator Effectiveness

In this paper, an augmented fault tolerant attitude control system is presented to address the problem of attitude adjustment for a quad-rotor unmanned aerial vehicle with inertia parameter uncertainties, the external disturbance and the partial loss of actuator effectiveness. To tackle system uncertainty and actuator faults, a fixed time compensation controller is developed based on adaptation mechanism combing with a monitor strategy and Nussbaum gain technique. Robust compensation algorithms under the proposed closed loop system structure are derived in the sense of Lyapunov stability analysis such that the attitude tracking-errors converge to a prescribed compact set in a fixed time. Finally, the simulation results demonstrate the effectiveness of the proposed controller.