Actuator Saturation Constraints Research Articles

Anti-disturbance cooperative formation containment control for multiple autonomous underwater vehicles with collision-free and actuator saturation constraints

This article investigates the formation containment control (FCC) problem of multiple autonomous underwater vehicles system (MAUVS) in the simultaneous presence of disturbances, collision avoidance between autonomous underwater vehicles (AUVs) and actuator saturation constraints. Firstly, for the purpose of enhancing the resisting disturbance capability of the MAUVS, the extended state observers are designed to estimate the total disturbance comprised of internal uncertainties and external interferences in real time. In order to hinder the occurrence of complexity explosion during the backstepping design, tracking differentiators are adopted to provide estimates for the derivative of the virtual control signals. Furthermore, the auxiliary system is constructed for reducing the influence of the actuator saturation on the MAUVS. Potential functions are integrated into the designed FCC strategy, so that the collisions between AUVs can be effectively avoided while the MAUVS achieving formation containment. Afterwards, via resorting to Lyapunov stability theory, it is demonstrated that the formation tracking errors and containment errors are uniformly ultimately bounded. Lastly, the comparative simulation results are illustrated to validate the feasibility of the presented anti-disturbance FCC scheme with collision-free and anti-saturation.

Adaptive Flying Assistance Controller Design to Suppress Nonlinear Pilot-Induced Oscillations

Nonlinear pilot-induced oscillations (PIOs) pose a threat to the safety of piloted aircraft in flight. This study aimed to address this safety concern. A novel method for designing an assistance controller based on incremental model predictive control is proposed to aid pilots in suppressing categories 2 and 3 PIOs. In the assistance controller design, the characteristics of the full pilot–aircraft system are considered through a predictive model that integrates the dynamics of the pilot, actuator, and aircraft. This ensures that the assistance controller coordinates with both the pilot and aircraft. Additionally, an adaptive logic for the pilot–controller authority assignment is proposed to automatically adjust the role of the assistance controller. This adaptive logic adopts a model predictive technique to determine whether the pilot’s independent control will cause actuator saturation over the receding prediction horizon. By doing so, the assistance controller is restricted to work only when the actuator saturation constraints are activated. The pilot model-based simulations and the human-in-the-loop experiments demonstrated that the proposed assistance controller can effectively assist pilots in dealing with factors causing nonlinear PIOs while maintaining a harmonious cooperative relationship with the pilot.

Fixed-time observation and predefined performance regulation for oxygen excess ratio of vehicular fuel cells under input saturation

The efficiency, health and lifetime of vehicle-mounted fuel cells highly rely on the oxygen excess ratio (OER). Faced with urgent research limitations, this article tackles the estimation and regulation for immeasurable OER, while suppressing the influences of dramatic stack current, uncertain system information, actuator saturation and performance constraint. Restricted by high cost and measurement difficulty, two fixed-time adaptive observers are proposed to rebuild unavailable OER and lumped disturbance respectively, which eliminate the dependence of estimation time on initial states and alleviate the peaking issue. Further, a fixed-time prescribed performance controller is developed to elevate the tracking performance for the estimated OER, in which the overshoot, regulation time and convergence region can be quantitatively constrained, regardless of initial conditions. Specially, to exclude undesired control singularity, an improved performance function is established to automatically adjust the predefined constraint boundaries depending on the captured variations of stack current and anti-saturation auxiliary signal. The hardware-in-loop validation results under custom working conditions and a typical vehicle driving cycle exhibit that the estimation and regulation of OER reach stability within 0.2s and 1s respectively, besides, the maximum absolute errors in observing and controlling the OER are limited to around 0.6 and 0.8 respectively, with great adaptability to different scenarios.

Practical finite‐time fuzzy control of uncertain nonstrict‐feedback systems with actuator saturation and output constraints

SummaryThis article investigates the devise issue of a practical finite‐time output‐tracking control for uncertain nonlinear nonstrict‐feedback systems subject simultaneously to time‐varying output constraints (TVOC), actuator saturation, and bounded unmatched disturbances. An adaptive fuzzy approximator‐based control system is devised using the dynamic surface control (DSC) concept. System output constraints are addressed by employing an appropriate barrier Lyapunov function. Adaptive fuzzy disturbance observers are constructed to practically deal with time‐varying unmatched but bounded disturbances. It is verified via Lyapunov stability analysis and simulation experiments that all closed‐loop signals remain bounded, the output tracking error practically converges in finite time to a tiny but adjustable neighborhood around the origin, and the system output stays within its required time‐varying bounds.

B-Spline Wavelet Neural-Network-Based Adaptive Control for Linear-Motor-Driven Systems via a Novel Gradient Descent Algorithm

This paper proposes a gradient descent (GD) algorithm-based B-Spline wavelet neural network (GDBSWNN) learning adaptive controller for linear motor (LM) systems under system uncertainties and actuator saturation constraints. A recursive least squares (RLS) algorithm-based indirect adaptive strategy is used to effectively estimate model parameters, which can guarantee they converge to true values. A novel GDBSWNN compensator is proposed to estimate the remaining complex uncertainties, where weights are updated by online GD training. An auxiliary system is integrated into the control scheme to address the saturation problem, which guarantees stability and satisfactory control performance when saturation occurs. In addition, a stability analysis is presented to prove that all signals of the closed-loop system are bounded using the Lyapunov theory. Experiments have been conducted on an LM-driven motion platform, where different controllers have been tested, demonstrating the effectiveness and advantages of the proposed approach.

Saturated adaptive single-parameter backstepping design for underactuated MSVs tracking control with uncertain dynamics

For realizing the trajectory tracking of underactuated marine surface vehicles (MSVs) in the presence of model dynamic uncertainties, actuator saturation constraints, and time-varying uncertain disturbances, a saturated adaptive single-parameter backstepping control (SPBC) scheme is developed, which possesses the properties of being model-parameter free and single-parameter adaptive. A smooth dead-zone operator (SDZO) and dynamic compensation equations are designed to deal with the propulsion system saturation constraints problem. Then, desired velocities and an auxiliary combined velocity variable are introduced to solve the potential singular problem and stabilize the subsystem of kinematics. Following that, a single-parameter adaptive law is designed in surge and yaw channels to compensate compounded uncertainties, which further alleviate computational burdens. Theoretical analysis indicates that the proposed scheme can guarantee the boundedness of all closed-loop signals. Approach efficiency is validated by simulations and experiments.

Adaptive finite-time output tracker design of uncertain nonlinear systems with sandwich structure and actuator saturation constraint

This paper studies the finite-time output tracking problem for a class of nonlinear sandwich systems with sandwiched dead-zone function and input actuator saturation constraint. To achieve the goal, a systematic adaptive backstepping controller is proposed based on the practical finite-time stability criterion which guarantees the output tracking even if the dead zone and saturation constraints occur, simultaneously. In the control approach to confine the system output to a predefined set, the barrier Lyapunov function is utilised. To cope with the problem of ‘explosion of complexity’, a finite-time command filter is also employed. Furthermore, the values of the unknown parameters are estimated by appropriate adaptive laws. The finite-time stability of the closed-loop system is proved based on the Lyapunov approach which ensures the boundedness of all signals. Finally, the efficiency and applicability of the proposed method are confirmed by providing the simulation results for the hydraulic servo press system.

Underactuated Mechanical Systems With Both Actuator and Actuated/Unactuated State Constraints: A Predictive Control-Based Approach

Underactuated systems are widely used in practice. Due to actuator saturation and transient performance requirements, it is necessary to keep the control inputs and system states within safe limits. However, with fewer control inputs, the state constraints, especially for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">unactuated</i> states, are usually difficult to guarantee. Model predictive control (MPC), as a method that can handle constraints naturally, unfortunately, still struggles to deal with unactuated variable constraints directly. To this end, this article proposes a general MPC algorithm <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">for a class of underactuated systems</i> . First, an MPC method considering actuator saturation constraints is designed, based on which, different velocity constraint-related matrices are constructed to convert both <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">actuated</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">unactuated</i> velocity constraints into control input constraints. Then, by delicately analyzing the coupling relationship between actuated and unactuated variables, the displacement/angle constraints of unactuated variables are theoretically ensured. To our best knowledge, it is the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">first</i> MPC approach designed for a class of underactuated systems with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">both</i> actuated and unactuated state constraints as well as actuator saturation. Finally, the proposed MPC approach is applied to two typical underactuated systems, i.e., tower cranes and boom cranes, and a series of experiments are investigated to verify the effectiveness and superiority of this approach.

Incremental Nonlinear Dynamic Inversion Attitude Control for Helicopter with Actuator Delay and Saturation

In this paper, an incremental nonlinear dynamic inversion (INDI) control scheme is proposed for the attitude tracking of a helicopter with model uncertainties, and actuator delay and saturation constraints. A finite integral compensation based on model reduction is used to compensate the actuator delay, and the proposed scheme can guarantee the semi-globally uniformly ultimately bounded tracking. The overall attitude controller is separated into a rate, an attitude, and a collective pitch controller. The rate and collective pitch controllers combine the proposed method and INDI to enhance the robustness to actuator delay and model uncertainties. Considering the dynamic of physical actuators, pseudo-control hedging (PCH) is introduced both in the rate and attitude controller to improve tracking performance. By using the proposed controller, the helicopter shows good dynamics under the multiple restrictions of the actuators.

Sideslip angle observation-based LOS and adaptive finite-time path following control for sailboat

In this article, double finite-time observers-based line-of-sight guidance (DFLOS) and adaptive finite-time control (DFLOS-AFC) scheme is presented for path following of sailboat. The time-varying sideslip angle is accurately observed by double finite-time sideslip observers (DFSO), which improves the robustness and accuracy of line-of-sight guidance. For heading controller, the finite-time filter is used to solve the differential explosion problem of the virtual control law. The second order integral terminal sliding mode is devised to ensure the precision of heading control. Finite-time auxiliary system is introduced to compensate for actuator saturation constraints. Model uncertainties and external disturbance are compensated through three adaptive updated parameters, which reduces the calculation complexity of heading control system. Finally, simulation and comparisons results demonstrate the effectiveness of DFLOS-AFC scheme.

Cooperative control of time-delay wind power grid-connected unit under actuator saturation based on Hamiltonian method

In large-scale wind power generation, wide area control is often employed to overcome power oscillation, but this can result in the appearance of time-delayed voltage, which is transmitted to the wind power grid-connected system as an input signal. Additionally, ensuring the security of multi-grid parallel connection requires limiting the amplitude of the input signal. To address these challenges, this paper investigates the cooperative control problem for time-delayed wind power grid-connected unit under actuator saturation constraints. A novel control strategy that combines passive control with synchronous control is proposed. The system is transformed into a Hamiltonian structure, and a passive controller is designed using the principle of interconnection and damping assignment passivity-based (IDA-PB) to ensure stability. Based on this, an output feedback synchronous controller is proposed to account for saturation when multiple grids are connected in parallel. Stability criteria are provided to ensure the asymptotic stability of each closed-loop system and synchronous stabilization of all systems. Finally, simulation results verify the effectiveness of the proposed control strategy.

Adaptive fuzzy dynamic surface fault-tolerant control for coupled spacecraft with actuator faults and saturation

This study investigates the fault-tolerant control problem associated with pose tracking for coupled spacecraft in the presence of both actuator faults and actuator saturation constraint. By using the Lie group SE(3), a six-degrees of freedom (6-DOF) coupled kinematics and dynamics model is established to derive the relative motion tracking errors in the exponential coordinates. Then, all system states are reconstructed to develop a dynamic surface fault-tolerant controller. Considering the lumped disturbance consisting of internal uncertainties, external unknown disturbances and actuator faults, a fuzzy adaptive method is used to estimate and compensate for the lumped disturbance. Next, the controller is nested with an auxiliary first-order filter to compensate for the saturation constraints. A Lyapunov analysis is used to prove the stability and finite time convergence of the proposed controller. Finally, The tracking performance is verified through a numerical example.

Event-Triggered Consensus of Matrix-Weighted Networks Subject to Actuator Saturation

This paper examines the event-triggered global consensus of matrix-weighted networks subject to actuator saturation. A distributed protocol design is proposed for this category of networks to guarantee its global consensus subject to both event-triggered communication and actuator saturation. It is shown that the largest singular value of matrix-valued edge weights plays a crucial role in both protocol design and network performance, which renders the proposed framework more general than existing results that are only applicable to scalar-weighted networks. Conditions under which the global consensus can be guaranteed for leaderless matrix-weighted multi-agent networks are derived. However, the average consensus on the initial agents' states cannot be achieved due to the nonlinearities introduced in the closed-loop dynamics by the actuator saturation constraint. We further examine the scenario of leader-follower consensus for matrix-weighted multi-agent networks under the constraints of both event-triggered communication and actuator saturation. The applicability of the proposed protocol design framework to time-varying matrix-weighted networks is also examined. It is shown that the Zeno phenomenon can be excluded under the proposed interaction protocols. Simulation results in the context of the bearing-only cooperative formation of multi-vehicle systems are provided to demonstrate the effectiveness of theoretical results.

Iterative Learning Tracking Control for a Vehicle-Manipulator System With Input Constraint

In this study, the tracking control and saturation nonlinearities problems of a flexible mobile vehicle-manipulator with disturbance uncertainty are investigated. Based on the differential equations model, a novel iterative learning control (ILC) algorithm is designed, where two saturation functions and two hyperbolic tangent functions are utilized to deal with the actuator saturation constraint and an adaptive law is adopted to reduce the impact of disturbance uncertainty. With the ILC algorithm, the target of tracking control and vibration attenuation of the mobile manipulator can come true. Simulations are given to verify the effectiveness of designed control algorithm.

Intelligent Attitude Fault-Tolerant Control of Space Tumbling Target Fly-Around Based on RBF Neural Network

The flying around monitoring task of space tumbling target is one of the key links of its on-orbit service. Considering the practical constraints of system inertia uncertainty, external disturbance, actuator saturation, and fault in engineering practice, a robust composite controller based on radial basis function (RBF) neural network is proposed. First, in a new line of sight rotation (RLOS) coordinate system, the relative attitude kinematics and dynamics equations between the tracker and tumbling target based on the error quaternion are established; second, the RBF neural network is used to estimate the additive and multiplicative faults of the system, and the fast nonsingular terminal sliding mode surface (FNTSMS) is combined with the active disturbance rejection control (ADRC) technology to design a finite-time fault-tolerant control (FTC) strategy with high accuracy, strong robustness, and anti-saturation based on the RBF neural network. It is proven that the designed robust fault-tolerant controller can ensure that the system state error converges to a small region containing the origin in a limited time under the Lyapunov framework. Finally, the effectiveness and superiority of the control strategy were verified by numerical simulation.

Longitudinal speed tracking control for an electric connected vehicle with actuator saturation subject to a replay attack

In this paper, a delay-tolerable and anti-windup control synthesis technique is proposed. Longitudinal speed tracking performed by an integrated electric drive (IED) system under the multi-domain constraints of network bandwidth and actuator saturation is investigated. Controller area network (CAN) connected to the Internet provide an interface for cyber attacks. In addition, the physical saturation characteristics of the electric drive motor sacrifice vehicle speed tracking performance. Based on above problems, a nominal controller satisfying energy-to-peak performance considering the attack-induced delays is designed. Then, an augmented closed-loop system is established including the nominal delay-tolerable controller and an anti-windup controller considering input saturation and random attack-induced delays. The delay-dependent uncertainty caused by attack-induced delay is expressed in the form of polytopes. Furthermore, the saturation nonlinearity is converted to sector-bounded uncertainty. Particle swarm optimization (PSO) algorithm is employed to find anti-windup controller matrices. Finally, the effectiveness and improvement of the proposed method based on MATLAB Simulink and hardware-in-the-loop (HiL) test platform are shown. The variation of speed tracking performance and oscillation damping capability under different attack energies is described.

An Overview of Recent Advances in the Event-Triggered Consensus of Multi-Agent Systems with Actuator Saturations

The event-triggered consensus of multi-agent systems received extensive attention in academia and industry perspectives since it ensures all agents eventually converge to a stable state while reducing the utilization of network communication resources effectively. However, the practical limitation of the actuator could lead to a saturation phenomenon, which may degrade the systems or even induce instability. This paper plans to offer a detailed review of some recent results in the event-triggered consensus of multi-agent systems subject to actuator saturation. First, the multi-agent system model with actuator saturation constraints is given, and the basic framework of the event-triggering mechanism is introduced. Second, representative results reported in recent valuable papers are reviewed based on methods for dealing with saturated terms, including low-gain feedback, sector-bounded conditions, and convex hull representations. Finally, some challenging topics worthy of research efforts are dicussed for future research.

Model Predictive Tracking Control With Parameter Estimation for Spin-Stabilized Indirect Fire Symmetric Projectiles

Abstract Impact point prediction, estimation, and control is a critical component of many smart weapons applications. In this work, I propose a method for estimating and controlling impact points of indirect fire launches for a spin-stabilized symmetric projectile with forward-mounted canard actuators. My method uses an algebraic point mass model to enable parameter estimation for time-varying parameters within a separate linear prediction model that can be leveraged for real-time impact point control. The point mass model also serves as the basis for a reference trajectory for any launch condition and thus eliminates the need for obtaining preloaded reference trajectories. I then use a linear prediction model in conjunction with the parameter estimates to synthesize a linear MPC tracking control algorithm for projectile impact point control. The MPC tracking controller allows incorporation of actuator saturation constraints and is shown to successfully guide a set of indirect fire launches toward a desired downrange target. A comparative case study to existing work in the literature shows that the proposed method results in a 56% reduction in the CEP radius, which is a prescribed radius such that half of the points of a given set lie within the circle, for a set of 50 yaw and pitch launch angle pairs.

Adaptive Fault-Tolerant Control for Flexible Variable Structure Spacecraft with Actuator Saturation and Multiple Faults

This study investigated the adaptive fault-tolerant control (FTC) for a flexible variable structure spacecraft in the presence of external disturbance, multiple actuator faults, and saturation. The attitude system model of a variable structure spacecraft and actuator fault model are first given. A sliding mode-based fault detection observer and a radial basis function-based fault estimation observer were designed to detect the time of actuator fault occurrence and estimate the amplitude of an unknown fault, respectively. Then, the adaptive FTC with variable structure harmonic functions was proposed to automatically repair multiple actuator faults, which first guaranteed that the state trajectory of attitude systems without actuator saturation converges to a neighborhood of the origin. Then, another improved adaptive FTC scheme was further proposed in the actuator saturation constraint case, ensuring that all the closed-loop signals are finite-time convergence. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

Static output‐feedback stabilization of discrete‐time linear parameter‐varying systems under actuator saturation

AbstractThis paper introduces a novel local synthesis condition for gain‐scheduling static output‐feedback control of discrete‐time linear parameter‐varying (LPV) systems under actuator saturation and state constraints. The proposed condition is formulated as a set of parameter‐dependent linear matrix inequalities that are incorporated into a convex optimization procedure to provide an enlarged estimate of the region of attraction of the closed‐loop equilibrium. In contrast with related works, the proposed approach allows handling a wider class of LPV systems since no rank condition is required to employ the so‐called equality constraints.