Actuator Saturation Research Articles

Finite-time robust adaptive simultaneous stabilisation of nonlinear time-delay systems with actuator saturation

This paper focuses on finite-time robust adaptive simultaneous stabilisation for nonlinear time-delay systems, taking into account actuator saturation and unknown parameters. Firstly, by employing adaptive control strategies and finite-time stability theory, a finite-time adaptive simultaneous stabilisation scheme for the nonlinear time-delay systems is developed. Secondly, utilising the orthogonal decomposition method, a finite-time robust adaptive simultaneous stabilisation scheme for nonlinear time-delay systems with external disturbances is proposed. Finally, simulations demonstrate the effectiveness of the provided control scheme.

Finite-Time Anti-Saturated Formation Tracking Control of Multiple Unmanned Aerial Vehicles: A Performance Tuning Way

A highly effective control method is very important to guarantee the safety of the formation of flying missions for multiple unmanned aerial vehicles (UAVs), especially in the presence of complex flying environments and actuator constraints. In this regard, this paper investigates the formation tracking control problem of multiple UAVs in the presence of actuator saturation. Firstly, a brand-novel finite-time anti-saturated control scheme is proposed for multiple UAVs to track the desired position commands, wherein the tracking performance is tuned by introducing a logarithmic function-based state-mapping policy. Then, an adaptive scheme based on projection rules is devised to compensate for the negative effects brought by the actuator saturation. Based on the proposed formation tracking controller, the finite-time formation tracking performance tuning and control saturation problems can be addressed simultaneously with a comparatively allowable system robustness. Finally, three groups of illustrative examples are organized to verify the effectiveness of the proposed formation tracking control scheme.

Performance-based activation of anti-windup compensation for control of linear systems subject to actuator saturation

In this paper, we propose a performance-based activation mechanism for anti-windup compensation. The signals representing the transient performance of the closed-loop system are passed through a static performance compensator and then injected into the traditional anti-windup activation module and a performance-based anti-windup design framework is developed. The resulting equivalent controller contains the information of the anti-windup compensator and has the potential for improving the performance of the closed-loop systems. Under this new anti-windup design framework, sufficient conditions are established for estimating the domain of attraction and the nonlinear L2 gain of saturated systems. Based on these conditions, we formulate optimization problems to determine the optimal gains of anti-windup and performance compensators for enlarging the domain of attraction and reducing the nonlinear L2 gain. Simulation results show that, compared with the existing methods, our proposed approach has the ability to acquire a significantly larger estimate of the domain of attraction, a significantly tighter estimate of the nonlinear L2 gain, and significantly higher transient quality in reference tracking.

Anti-disturbance control for HVs system subject to nonlinear actuator characteristics with extended state observer

This paper proposes a radial basis function neural network and the actuator fault extended state observer based fast non-terminal sliding mode fault-tolerant control scheme for hypersonic vehicles (HVs) system. The proposed scheme can cope with actuator faults, actuator saturation, parameter uncertainties, and external disturbances for HVs systems, without relying on redundancy as some passive FTC methods do. Moreover, an anti-windup compensator is designed to mitigate the input saturation effects. Furthermore, the finite-time stability of the attitude angle of the HVs system is proved by Lyapunov's theorem. Numerical simulations validate the effectiveness of the proposed scheme.

Data-Driven Spatial Adaptive Terminal Iterative Learning Predictive Control for Automatic Stop Control of Subway Train With Actuator Saturation

A data-driven spatial adaptive terminal iterative learning predictive control (SATILPC) scheme with actuator saturation is proposed for automatic stop control of the subway train. Considering the outstanding repetitive operation pattern and the unavailable accurate model of a subway train, the unknown train dynamics is firstly transformed into a nonlinear discrete form in spatial domain via the spatial differential operator. Since the train automatic stop control (TASC) only concentrates on the tracking performances of the terminal position and terminal speed, an iterative dynamic linearization approach considering the terminal operation point is devised to formulate the relationship of the train input and output (I/O) into a linear affine form. Then, a terminal iterative learning prediction mechanism is introduced to reconstruct the developed train data model to forecast the future train behaviors through rolling optimization process. As a result, by removing the constraints on the unimportant points, the optimal control input (braking force) can be obtained by minimizing the objective function through terminal I/O data. Further, actuator saturation is considered to address the passenger comfort and the reliable operation of the train. The proposed SATILPC approach is a pure data-driven iterative learning control scheme and no model information is involved in the whole design processes. By utilizing a newly space-based contraction mapping method, the convergence of the proposed approach is strictly proved. Finally, the simulation results further demonstrate the feasibility of the proposed algorithm.

An improved compact-form antisaturation model-free adaptive control algorithm for a class of nonlinear systems with time delays.

To solve the time-delay problem and actuator saturation problem of nonlinear plants in industrial processes, an improved compact-form antisaturation model-free adaptive control (ICF-AS-MFAC) method is proposed in this work. The ICF-AS-MFAC scheme is based on the concept of the pseudo partial derivative (PPD) and adopts equivalent dynamic linearization technology. Then, a tracking differentiator is used to predict the future output of a time-delay system to effectively control the system. Additionally, the concept of the saturation parameter is proposed, and the ICF-AS-MFAC controller is designed to ensure that the control system will not exhibit actuator saturation. The proposed algorithm is more flexible, has faster output responses for time-delay systems, and solves the problem of actuator saturation. The convergence and stability of the proposed method are rigorously proven mathematically. The effectiveness of the proposed method is verified by numerical simulations, and the applicability of the proposed method is verified by a series of experimental results based on double tanks.

Consensus Control for Multiagent Systems Under Asymmetric Actuator Saturations With Applications to Mobile Train Lifting Jack Systems

In this paper, the consensus control problem is investigated for mobile train lifting jack systems (TLJSs) of electric multiple units in the context of distributed industrial systems. First, a kind of global consensus controller is dedicatedly designed to deal with the underlying actuator limitation that is a typical phenomenon in mobile TLJSs and is referred to as actuator saturation. In order to better cater for the impact from the TLJSs, we consider the asymmetric actuator saturations (rather than their symmetric counterparts) whose side effects are later attenuated by means of a novel Lyapunov-function-based method. A series of experiments are conducted on mobile TLJSs so as to illustrate the effectiveness of the proposed consensus control algorithm.

Finite-Time Observer-Based Formation Tracking With Application to Omnidirectional Robots

The challenging problem of robust formation control pertaining to omni-directional robots with model uncertainty and actuator saturation is comprehensively investigated in this paper. Firstly, an observer-based formation controller is designed to ensure the semi-global uniform ultimate boundedness of the system's formation tracking error. Then both global stability and practical finite-time stability are achieved to ascertain the practicality of the observer design. Apart from restricting the control input amplitude, we also investigate the reverse effect caused by saturated and coupled control input. As such, an adaptive compensator is formulated to attenuate the state oscillation caused by the reverse effect. Both numerical simulations and hardware-in-the-loop experiments are carried out to illustrate and evaluate the effectiveness and potentials of the proposed new techniques for real-world applications.

Local Synchronization of Directed Lur'e Networks With Coupling Delay via Distributed Impulsive Control Subject to Actuator Saturation.

This article studies the local exponential synchronization synthesis problem of directed Lur'e networks with coupling time-varying delay under the distributed impulsive control subject to actuator saturation. First, by utilizing proof by contradiction, impulsive comparison principle, and latest improved convex hull representation of saturation function, some delay-independent sufficient criteria for local exponential synchronization are presented in the form of bilinear matrix inequalities. Meanwhile, a novel method with less conservatism is developed to estimate the domain of attraction, which is radically different from the traditional method by means of contractive invariant set. Second, optimization problems constrained by the transformed linear matrix inequalities are established to acquire the maximum estimates of both the domain of attraction and average impulsive interval (AII), which are conveniently solved by the YALMIP toolbox in MATLAB software. Finally, a numerical simulation is rendered to demonstrate the effectiveness and advantages of the proposed theoretical results.

Neural-Network-Based Adaptive Finite-Time Output Feedback Control for Spacecraft Attitude Tracking.

This brief is concerned with neural network (NN)-based adaptive finite-time output feedback attitude tracking control for rigid spacecraft in the presence of actuator saturation, inertial uncertainty, and external disturbance. First, a neural state observer is designed to estimate the unknown state. Then, based on the estimated state, the adaptive neural finite-time command filtered backstepping (CFB) is applied to construct virtual control signal and controller with updating law. The finite-time command filter is given to avoid the computation complexity problem in traditional backstepping, and the compensation signals based on fractional power are constructed to remove filtering errors. Using Lyapunov stability theory, we show that the attitude tracking error (TE) can converge into the desired neighborhood of the origin in finite time and all the signals in the closed-loop system are bounded in finite time although input saturation exists. The numerical simulations are used to show the effectiveness of the given algorithm.

Distributed Dual Closed-Loop Model Predictive Formation Control for Collision-Free Multi-AUV System Subject to Compound Disturbances

This paper focuses on the collision-free formation tracking of autonomous underwater vehicles (AUVs) with compound disturbances in complex ocean environments. We propose a novel finite-time extended state observer (FTESO)-based distributed dual closed-loop model predictive control scheme. Initially, a fast FTESO is designed to accurately estimate both model uncertainties and external disturbances for each subsystem. Subsequently, the outer-loop and inner-loop formation controllers are developed by integrating disturbance compensation with distributed model predictive control (DMPC) theory. With full consideration of the input and state constraints, we resolve the local information-based DMPC optimization problem to obtain the control inputs for each AUV, thereby preventing actuator saturation and collisions among AUVs. Moreover, to mitigate the increased computation caused by the control structure, the Laguerre orthogonal function is applied to alleviate the computational burden in time intervals. We also demonstrate the stability of the closed-loop system by applying the terminal state constraint. Finally, based on a connected directed topology, comparative simulations are performed under various control schemes to verify the robustness and superior performance of the proposed scheme.

Nonlinear disturbance compensator for active suspension systems with actuator saturation

Nonlinear disturbance compensator for active suspension systems with actuator saturation

Rotor cross-tilt optimization for yaw control improvement of multi-rotor eVTOL aircraft

Manned multi-rotor electric Vertical Takeoff and Landing (eVTOL) aircraft is prone to actuator saturation due to its weak yaw control efficiency. To address this inherent problem, a rotor cross-tilt configuration is applied in this paper, with an optimization method proposed to improve the overall control efficiency of the vehicle. First, a flight dynamics model of a 500-kg manned multi-rotor eVTOL aircraft is established. The accuracy of the co-axial rotor model is verified using a single arm test bench, and the accuracy of the flight dynamics model is verified by the flight test data. Then, an optimization method is designed based on the flight dynamics model to calculate an optimal rotor cross-tilt mounting angle, which not only improves the yaw control efficiency, but also basically maintains the efficiency of other control channels. The ideal rotor cross-tilt mounting angle for the prototype is determined by comprehensively considering the optimal results with different payloads, forward flight speeds, and rotor mounting angle errors. Finally, the feasibility of the rotor cross-tilt mounting angle is proved by analyzing the control derivatives of the flight dynamics model, the test data of a ground three Degree-of-Freedom (3DOF) platform, and the actual flight data of the prototype. The results show that a fixed rotor cross-tilt mounting angle can achieve ideal yaw control effectiveness, improving yaw angle tracking and hold ability, increasing endurance time, and achieving good yaw control performance with different payloads and forward speeds.

Distributed asynchronous event-triggered cooperative control for virtually coupled train set subject to gradient terrain and input saturation

The cooperative tracking control problem is investigated for the virtually coupled train set subject to gradient terrain and actuator saturation. This paper proposes an adaptive event-triggered cooperative tracking control scheme, where a distributed asynchronous event-triggered sampling is designed based on the relative states between adjacent trains. In addition, the unknown parameters of high-speed train system are estimated by the adaptive method. By the proposed control scheme, the velocity and position tracking errors between any adjacent trains are ultimately bounded while realizing on-demand interaction between trains. It is proved that the Zeno behavior can be excluded by quantitatively expressing the strictly positive minimum lower bound of the inter-event interval. Finally, a simulation of the Beijing-Shanghai high-speed railway is used to verify the feasibility and effectiveness of the proposed control scheme.

Flexible performance‐based adaptive fault‐tolerant attitude tracking control for input‐constrained satellite

SummaryUnder the actuator saturation and fault, the satellite attitude often violates the prescribed performance function, leading to the satellite attitude's instability. Therefore, the adaptive attitude tracking control problem for the satellite simultaneously considering the finite time‐based prescribed performance, the actuator saturation and the actuator fault is studied in this article. A modification performance function‐based control scheme is designed, which can avoid violating the designed modified performance functions when the actuator saturation occurs due to the actuator fault. A novel fault tolerant auxiliary system is developed, which is used to generate modification signals for adjusting the prescribed performance function. Consequently, the boundedness of all the closed‐loop signal under the designed control scheme is proved via Lyapunov function method. Finally, the feasibility of the designed satellite attitude control scheme is verified by a simulation example.

Global Fixed-Time Sliding Mode Trajectory Tracking Control Design for the Saturated Uncertain Rigid Manipulator

The global fixed-time sliding mode control strategy is designed for the manipulator to achieve global fixed-time trajectory tracking in response to the uncertainty of the system model, the external disturbances, and the saturation of the manipulator actuator. First, aiming at the lumped disturbance caused by system model uncertainty and external disturbance, the adaptive fixed-time sliding mode disturbance observer (AFSMDO) was introduced to eliminate the negative effects of disturbance. The observer parameters can adaptively change with disturbances by designing the adaptive law, improving the accuracy of disturbance estimation. Secondly, the fixed-time sliding surface was introduced to avoid singularity, and the nonsingular fixed-time sliding mode control (NFSMC) design was put in place to ensure the global convergence of the manipulator system. Finally, the fixed time saturation compensator (FTSC) was created for NFSMC to prevent the negative impact of actuator saturation on the manipulator system, effectively reducing system chatter and improving the response speed of the closed-loop system. The fixed-time stability theory and Lyapunov method were exploited to offer a thorough and rigorous theoretical analysis and stability demonstration for the overall control system. Simulation experiments verify that the designed control scheme has excellent control effects and strong practicability.

Saturated exponential super‐twisting sliding mode control for bottom‐following of biomimetic underwater vehicles with unmeasured velocities

AbstractThis article addresses the bottom‐following problem for biomimetic underwater vehicles without translational velocity measurements in the presence of complex uncertainties and actuator saturation. A novel saturated exponential super‐twisting algorithm based integral terminal sliding mode control (SESTA‐ITSMC) scheme is created to ensure fast convergence and strong robustness as well as attenuate the chattering of actuators. Salient features are as follows. Instead of discontinuous term in the conventional super‐twisting algorithm, a novel SESTA is developed by incorporating a fractional power term, which ensures that the system achieves a faster transient response, effectively eliminating the chattering phenomenon. Then, to deal with the unknown states and further improve the anti‐interference ability of the system, the finite‐time dual estimator is devised to fast and precisely estimate the translational velocities and lumped uncertainties. Finally, a finite‐time anti‐windup auxiliary system is proposed to compensate for the saturation constraints on actuators in real time. Finite‐time convergence of estimation errors and bottom following errors is guaranteed by the Lyapunov stability theory. Comparative simulation results fully demonstrate the excellence of the proposed SESTA‐ITSMC scheme.

Robust cooperative tracking of multiagent systems with asymmetric saturation actuator via output feedback

AbstractThe robust tracking control problem of the leader‐follower multiagent systems affected by asymmetric input saturation and external disturbances is addressed in this article, by following three steps. First, an radial basis function neural network (RBFNN) is developed to estimate the external disturbances and supersaturation, where the supersaturation is induced by asymmetric saturation actuator. Second, combining with the developed radial basis function neural network, a reduced‐order observer‐based static protocol and a reduced‐order observer‐based adaptive one are designed for leader‐follower systems with un‐directed communication topology as well as those with directed communication topology, respectively. Third, some mild premises are given to guarantee the semiglobal robust leader‐follower consensus for the above mentioned two kinds of multiagent systems. Finally, the theoretical results are verified by several numerical simulations.

Neural networks-based adaptive tracking control for full-state constrained switched nonlinear systems with periodic disturbances and actuator saturation

In this paper, an adaptive tracking control approach is developed for full-state constrained switched nonlinear systems that have actuator saturation, periodic disturbances and unknown control direction. To deal with the full-state constraints, the Barrier Lyapunov functions are introduced to limit the state variables within the corresponding constraint conditions. Meanwhile, the Fourier series expansion technology is employed to deal with unknown periodic disturbances and unknown nonlinear dynamics jointly. Additionally, a Nussbaum-type function is used in the controller design to cope with the and unknown control gain and input saturation. On the basis of the Lyapunov stability theory, it is demonstrated rigorously that all signals of the closed-loop system are uniformly ultimately bounded, and the proposed controller ensures that the tracking error is kept within a compact set close to zero. In the end, the validity of the designed control protocol is verified by a simulation example.

Leader-follower formation control of Euler-Lagrange systems with limited field-of-view and saturating actuators: A case study for tractor-trailer wheeled mobile robots

In this paper, an adaptive-neural constrained controller is proposed for a group of Tractor-trailer wheeled mobile robots with limited field-of-view (FOV) constraints and saturating actuators. With an effective combination of the asymmetric Barrier Lyapunov function based control design and dynamic surface control in the proposed constrained controller, the limited FOV constraints are not transgressed the predefined and limited bounds. The risk of the actuators saturation is extremely decreased through restricting amplitudes of the output states errors. It is proved that all the output states in the closed-loop system are semi-globally uniformly ultimately bounded and the relative distance and orientation angles errors are converged in the limited and preassigned boundaries. Compared with the existing results, the proposed constrained controller not only assures that these states errors between consecutive TTWMRs are bounded, but also all the output states errors converge to a small region around zero in a fixed-time that this issue accelerates the convergence speed rate and improves the transient response performance of the perfect tracking control for all TTWMRs.