Effect Of Actuator Saturation Research Articles

Research on a backstepping flight control method improved by STFT in atmospheric disturbance applications

The adaptive backstepping method has strong performance in handling control problems with disturbances in previous research. However, it exhibits limitations when applied to time-varying disturbances. This paper proposes an improved adaptive backstepping method based on Discrete Fourier Transform (DFT). By estimating the frequency spectrum of the disturbance and indirectly obtaining its time-domain estimate, the proposed method effectively overcomes the shortcomings of traditional adaptive backstepping. To address the issue of frequency leakage caused by discontinuities in window data, the idea of DFT is improved by using STFT with the addition of the window function and window-shifting operation. Additionally, a projection operator and adaptive reduction of the control objective are employed to mitigate the effects of actuator saturation. Finally, in simulations involving an aircraft subjected to gusts and turbulence, the proposed method is compared with traditional adaptive backstepping and radial basis function (RBF) neural network control methods. Simulation results demonstrate that the proposed method outperforms the others in these experimental scenarios.

Fast fixed-time extended state observer based command filtering backstepping control of free-flying flexible-joint space robots

System parameter perturbations, external disturbances, and input saturation issues seriously affect the on-orbit operation precision and rapid response capabilities of the free-flying flexible-joint space robots (FFSR). To this end, a fixed-time extended state observer (ESO) based non-singular command filtering backstepping controller is proposed. The fast fixed-time ESO is designed to estimate the parameter perturbations and external disturbances. To avoid the “computational explosion” caused by multiple derivatives of the virtual control law in backstepping control, a second-order command filter is employed to obtain the derivative of virtual control laws. Meanwhile, to reduce the filtering errors induced by the command filter, a non-singular fixed-time filtering error compensation algorithm is developed. Furthermore, considering the constraints of control moment gyroscope (CMG) and joint motors, an anti-saturation compensation algorithm is introduced to drive the system out of the saturated region rapidly, thus reducing actuator saturation effects on the control system performance. Theoretical analysis shows the proposed controller can ensure the system tracking error converges to any arbitrarily small neighborhood of the origin within fixed time. Simulation results demonstrate that the designed non-singular fixed-time command filtering backstepping controller exhibits fast convergence speed and high tracking accuracy.

Deep optimization design of 2D repetitive control systems with saturating actuators: An adaptive multi-population PSO algorithm

This paper presents an optimization design method for a two-dimensional (2D) modified repetitive control system (MRCS) with an anti-windup compensator. Using lifting technology, a 2D hybrid model of the MRCS considering actuator saturation is established to describe the control and learning of the repetitive control. A linear-matrix-inequality (LMI)-based sufficient condition is derived to ensure the stability of the MRCS. Two tuning parameters, the selection of which is critical to the system design, are used in the LMI to adjust the control and learning, and hence the reference-tracking performance. A new cost function, developed through time domain analysis, directly evaluates the control performance of the system without calculating control errors, thus reducing the optimization time. Based on this cost function, an adaptive multi-population particle swarm optimization algorithm is presented to select an optimal pair of tuning parameters in which multiple populations cooperatively search in non-intersecting search intervals. An anti-windup term is added between the low-pass filter and the time delay in the modified repetitive controller to mitigate the undesirable effect of actuator saturation on system performance and stability. Simulations and experiments on the speed control of a rotation control system demonstrate the validity of the approach.

Optimal control of jacket platforms vibrations under the simultaneous effect of waves and earthquakes considering fluid-structure interaction

Offshore platforms are very important structures that experience different types of dynamic loads throughout their service lives. In this study, the effects of the simultaneous occurrence of earthquakes and wave loads are investigated. The influences of earthquake-related water shaking on microwaves have also been considered. For this purpose, a case study is performed on the Ressalat oil platform in the Persian Gulf. The modified endurance wave analysis (MEWA) is used to produce waves corresponding to the structure's location. Moreover, the interactions between the fluid and the structure (FSI), as well as the effect of the added mass caused by the oscillation of the platform in the fluid are considered in the analysis. In order to control platform vibrations, the ideas of semi-active control using magnetic fluid dampers (MR), along with the fractional order proportional-integral-derivative (FOPID) control algorithm, are investigated. For online calculation of the gains of the control algorithm, an observer composed of 2-interval type fuzzy systems (IT2FLS) is used, whose orders, the membership functions of the fuzzy system inputs, as well as the fuzzy rules set, are optimized by Observer-Teacher-Learner-Based Optimization (OTLBO). This technique is a powerful meta-heuristic algorithm. In the used control process, the effect of actuator saturation, which is one of the problems of semi-active control systems, is considered. To evaluate the effectiveness of the proposed control, the maximum value and the root-mean-square (RMS) responses of the platform under 5 waves with different return periods and 7 far-fault earthquake records are compared. The results show that in the cases of simultaneous wave and earthquake loads, the wave load can partly reduce the maximum displacements caused by earthquakes. Also, the maximum and RMS displacement of the jacket platforms' level under wave load with a return period of 100 years and 7 earthquakes are reduced by an average of 35%, which can increase the service life of these structures by 4 times.

A Switched Integral-Based Event-Triggered Control of Uncertain Nonlinear Time-Delay System With Actuator Saturation.

This article explores the asymptotic stabilization criteria of the uncertain nonlinear time-delay system subject to actuator saturation. A switched integral-based event-triggered scheme (IETS) is established to reduce the redundant data transmission over the networks. The switched IETS condition uses the integration of system states over a time period in the past. A fixed waiting time is included to avoid the Zeno behavior. In order to estimate a larger domain of attraction, a delay-dependent polytopic representation method is presented to deal with the effects of actuator saturation in the proposed model. A new series of less conservative linear matrix inequalities (LMIs) is proposed on the basis of delay-dependent Lyapunov-Krasovskii functional (LKF) to ensure the stability of nonlinear time-delay system subject to actuator saturation using the proposed IETS. Numerical examples are used to confirm the effectiveness and advantages of the proposed IETS approach.

Distributed Finite-Time Fault-Tolerant Control for Heterogeneous Vehicular Platoon With Saturation

This paper investigates the distributed fault-tolerant control problem for the heterogeneous vehicular platoon system (HVPS) suffering from actuator faults, saturation, and external disturbances. Firstly, an exponential spacing policy is developed to tackle the string stability (SS) and traffic flow stability issues when the actuator faults occur. Then, a nonlinear observer is developed to estimate the saturation approximation error, bias fault, and external disturbances. Moreover, to achieve the SS of the whole system in finite-time and fault tolerance ability, a distributed adaptive fault-tolerant control scheme based on bidirectional-leader information flow topology is proposed. Adaptive estimation laws are also involved to estimate and update the unknown parameters, in which the effect of actuator saturation can be compensated. Finally, the SS in finite-time and traffic flow stability of the closed-loop system are proved, respectively. Experiment results and comparisons demonstrate the feasibly and advantages of the method.

Observer-based independent joint control for a coupled rigid-flexible manipulator with actuator saturation based on distributed parameter model

This study is concerned with an observer-based independent joint control scheme for a coupled two-link rigid-flexible robotic manipulator considering the effects of actuator saturation and external disturbances. A distributed parameter model of the robotic manipulator system described by ordinary and partial differential equation (ODE-PDE) is derived by using Hamilton’s Principle. An anti-saturation controller is developed to cope with the input saturation problem by using hyperbolic tangent and hyperbolic secant function. Considering the external disturbance, a disturbance observer is designed to estimate the external disturbance. The observer-based independent joint controller can adjust the joint angle and suppress the vibration simultaneously without the need for end-mounted actuators. The extended LaSalle’s Invariance Principle is adopted to strictly prove the asymptotic stability of the robotic manipulator system. The simulation comparisons validate the effectivity of the proposed controllers and observers.

Design of saturated boundary control for hyperbolic systems with in-domain disturbances

Boundary feedback control design is studied for 1D hyperbolic systems with an in-domain disturbance and a boundary feedback controller under the effect of actuator saturation. Nonlinear semigroup theory is used to prove well-posedness of mild solution pairs to the closed-loop system. Sufficient conditions in the form of dissipation functional inequalities are derived to establish global stability for the closed-loop system and L2-stability in presence of in-domain disturbances. The control design problem is then recast as an optimization problem over linear matrix inequality constraints. Numerical results are shown to validate the effectiveness of the proposed control design.

Neural-based formation control of uncertain multi-agent systems with actuator saturation

The formation control problem for a group of first-order agents with model uncertainty and actuator saturation is investigated in this manuscript. An algorithm-and-observer-based formation controller is developed to ensure the semi-global boundedness of the formation tracking error with actuator saturation. First, a fully local-error-related cooperative weight tuning procedure is proposed for the adaptive uncertainty estimation of each agent. The effect of actuator saturation on both the cooperative adaptive estimation and the controller design part is then analysed and discussed. A three-layer neural-based observer is further constructed to achieve finite-time uncertainty approximation with actuator saturation. Besides, the reverse effect led by coupled and saturated control inputs is defined and a new control input distribution algorithm is presented to attenuate the potential oscillation in system states. Finally, comparative simulations based on a multiple omnidirectional robot system are conducted to illustrate the performance of the proposed formation controllers and the new algorithm.

Observer-based synchronization of memristive neural networks under DoS attacks and actuator saturation and its application to image encryption

In this article, the synchronization issue of memristive neural networks (MNNs) under denial-of-service (DoS) attacks and actuator saturation is investigated via an observer-based controller. Due to actual physical constraint, the effect of actuator saturation is taken into account in the controller design. Unlike the existing works where the communication environment is secure, DoS attacks are explored in the communication channel connecting master and slave MNNs. Based on the above considerations, an observer-based control approach is developed to estimate the MNNs states and guarantee the MNNs synchronization in the presences of DoS attacks and actuator saturation. By using the Lyapunov method and stochastic analysis technique, the sufficient synchronization conditions are derived via a set of linear matrix inequalities (LMIs). Meanwhile, the attraction domain of error system is estimated to satisfy the demand of actuator saturation. Then, numerical simulation is used to manifest the validity of our theoretical results. Finally, the proposed synchronization theory is applied to image encryption. The experimental results demonstrate that the presented image encryption scheme has a reliable performance.

Designing a robust controller for a lower limb exoskeleton to treat an individual with crouch gait pattern in the presence of actuator saturation

Crouch gait is a gait anomaly observed in youngsters with cerebral palsy (CP). Rehabilitation robots are useful for treating individuals with crouch gait. Multiple factors have impact on crouch, including contracture, spasticity, weak motor control, and muscle feebleness, which make the designing and controlling of these exoskeletons for this population a challenging job. A harsh kinematic trajectory enforced by an exoskeleton control strategy may place individuals with spasticity at a high risk of muscle tissue injury. Therefore, in this article, a multi-input multi-output (MIMO) control method is proposed to reduce this risk and improve crouch gait pattern. A constrained control law is used in the model since high power demands may threaten the wearer. In addition, the controller needs to be robust enough against external disturbances and uncertainties. Thus, a nonlinear disturbance observer (NDO) is presented to compute the wearer-generated muscular torque and the uncertainties in the modeling. In addition, a robust constrained MIMO backstepping sliding controller (CMBSC) based on NDO is used to deal with the effect of actuator saturation and uncertainties. A simulation test was used to validate the proposed model and controller. The results of Simulation confirmed the efficiency of the proposed control method when applied to crouch gait with subject specific gait reference. Then, some experimental tests were undertaken to validate the efficiency of the proposed controller.

Formulation of nonlinear control problems with actuator saturation as linear programs

Control of input-affine nonlinear dynamical systems is investigated in this paper. In this regard, a system of linear inequalities (SLI) in the control inputs is developed, and it is proved that if this SLI has a solution at all times, applying it to the system leads to moving its state trajectories towards the desired point in space for all initial conditions. But, since it may happen that this SLI has infinitely many solutions or even no solution, the best (possibly, approximate) solution is obtained by solving a linear programming (LP) problem. Different LP problems with different properties and applications are proposed for this purpose. Formulation of the control problem as an LP makes it possible to take into account the effect of actuator saturation simply by adding bound constraints to the problem. We can also make the resulting control system robust to model uncertainties. Some numerical examples including the output voltage regulation of double-source DC-DC converter and robot path-planning, both by considering the effect of actuators saturation and taking into account the uncertainties in model, are also presented.

Adaptive Neural Network Control for Full-State Constrained Robotic Manipulator With Actuator Saturation and Time-Varying Delays.

This article proposes an adaptive neural network (NN) control method for an n -link constrained robotic manipulator. Driven by actual demands, manipulator and actuator dynamics, state and input constraints, and unknown time-varying delays are taken into account simultaneously. NNs are employed to approximate unknown nonlinearities. Time-varying barrier Lyapunov functions are utilized to cope with full-state constraints. By resorting to saturation function and Lyapunov-Krasovskii functionals, the effects of actuator saturation and time delays are eliminated. It is proved that all the closed-loop signals are semiglobally uniformly ultimately bounded, full-state constraints and actuator saturation are not violated, and error signals remain within compact sets around zero. Simulation studies are given to demonstrate the validity and advantages of this control scheme.

Finite-time asynchronous sliding mode control for Markov jump systems with actuator saturation

This paper deals with the finite-time asynchronous sliding mode control for Markov jump systems subject to actuator saturation. The hidden Markov model is adopted to describe the modal information exchange between the system and the designed controller. A sufficient condition is established by employing the Lyapunov stability theorem, which guarantees the stochastic finite-time boundedness of sliding mode. In order to mitigate the effects of actuator saturation and chattering, an adaptive sliding mode controller is designed based on the auxiliary saturation compensation system. Subsequently, the reachability of sliding mode motion is analysed. The controller gain matrix is obtained by solving the minimization problem. Finally, a simulation example is used to demonstrate that the proposed control method can effectively restrain the disturbance and compensate saturation.

Prescribed Performance Concurrent Control of Connected Vehicles With Nonlinear Third-Order Dynamics

Transient performance (e.g., convergence rate and overshoot of spacing errors) is essential for cooperative driving of connected vehicles but was rarely studied. This paper investigates a prescribed performance concurrent control (PPCC) strategy for vehicular platooning systems with consideration of unknown parameters, disturbances and actuator saturation. First, a new spacing policy is considered to achieve string stability and improve the road capacity under virtual leader-bidirectional information flow. Then, to facilitate the controller design without the sign limitations of initial tracking errors (ITEs), a new transformed error function (TEF) is designed. Based on this, PPCC is employed for both individual vehicle stability and string stability directly. Subsequently, distributed adaptive low complexity tracking controllers via sliding mode control method are developed, which can guarantee that all the involved closed-loop signals are uniformly ultimately bounded. Moreover, an auxiliary system is introduced to tackle the effect of actuator saturation. Finally, numerical simulation examples and results are conducted to illustrate the effectiveness and efficiency of the proposed platoon control methods.

Adaptive compensation control for special actuator circumstances with input quantization

SummaryIn this article, considering actuator constraints and possible failures, an adaptive compensation control scheme is developed to realize tracking control for a class of uncertain nonlinear systems with quantized inputs. A new variable is generated to evaluate the effect of actuator saturation and is used in the process of controller design to compensate for the influence of actuator saturation constraint. Moreover, the controller is able to show certain accommodation capability to tolerate possible actuator failures and input quantization error via integrating parameter update process of unknown fault constants into adaption of parametric uncertainties under the backstepping procedure. Specifically, actuator saturation effect and possible actuator failures as well as input quantization error can be dealt with uniformly under the framework of the proposed scheme and the control system has certain robustness to external disturbances. It is proved that all the signals of the closed‐loop system are ensured to be bounded and the tracking error is enabled to converge toward a compact set, which is adjustable by tuning design parameters. Finally, experiments are carried out on an active suspension plant to illustrate the effectiveness of the proposed control scheme.

Intelligent Spectrum Controlled Supplemental Lighting for Daylight Harvesting

This article presents a neural network-based control method for daylight harvesting in a proof-of-concept greenhouse consisting of emulated sunlight and dimmable light emitting diode light fixtures. The objective of this multi-input-multi-output lighting system is to deliver desired levels of light, within a specific spectrum range, to locations of interest in a grow tent. To this end, a learning neural network controller with online adaptive weights is presented which can achieve stability with small errors in the presence of disturbances and modeling uncertainties. A stability analysis of the closed-loop system is presented along with a selection method for obtaining the control parameters. The neural controller is enhanced with an antiwindup mechanism to account for the nonlinear effect of actuator saturation. Experimental results are presented to verify the proposed daylighting control strategy which confirm analytic and simulation studies.

Enhanced Composite Nonlinear Control Technique using Adaptive Control for Nonlinear Delayed Systems

Background and Introduction: The proposed control law is designed to provide fast reference tracking with minimal overshoot and to minimize the effect of unknown nonlinearities and external disturbances. Methods: In this work, an enhanced composite nonlinear feedback technique using adaptive control is developed for a nonlinear delayed system subjected to input saturation and exogenous disturbances. It ensures that the plant response is not affected by adverse effect of actuator saturation, unknown time delay and unknown nonlinearities/ disturbances. The analysis of stability is done by Lyapunov-Krasovskii functional that guarantees asymptotical stability. Results: The proposed control law is validated by its implementation on exothermic chemical reactor. MATLAB figures are provided to compare the results. Conclusion: The simulation results of the proposed controller are compared with the conventional composite nonlinear feedback control which illustrates the efficiency of the proposed controller.

Saturated adaptive output-constrained control of cooperative spacecraft rendezvous and docking

This paper investigates the robust relative pose control for spacecraft rendezvous and docking with constrained relative pose and saturated control inputs. A barrier Lyapunov function is used to ensure the constraints of states, so that the computational singularity of the inverse matrix in control command can be avoided, while a linear auxiliary system is introduced to handle with the adverse effect of actuator saturation. The tuning rules for designing parameters in control command and auxiliary system are derived based on the stability analysis of the closed-loop system. It is proved that all closed-loop signals always keep bounded, the prescribed constraints of relative pose tracking errors are never violated, and the pose tracking errors ultimately converge to small neighborhoods of zero. Simulation experiments validate the performance of the proposed robust saturated control strategy.

Novel anti-saturation robust controller for flexible air-breathing hypersonic vehicle with actuator constraints

A novel anti-saturation robust control algorithm (NARC) is presented for flexible air-breathing hypersonic vehicle (FAHV) with actuator saturation, including two controllers designed for velocity and height subsystem respectively. Firstly, an anti-saturation finite-time dynamic inversion controller is designed for velocity subsystem, in which an anti-saturation fixed-time compensator (ASFC) is proposed to ensure the stability of saturated system and make it exit saturated region faster. Compared with conventional anti-saturation compensator, the auxiliary variable of ASFC can converge with faster speed and higher precision when actuator is not saturated, which avoids the impact on original system. Secondly, an anti-saturation robust command filtered backstepping controller is designed for height subsystem, combining backstepping control, ASFC and a novel fixed-time filter (FTF). Compared with low pass filter, the FTF proposed can track input signal with faster response speed and higher precision without the need to select a smaller time constant, so as to avoid introducing high-frequency noise. Meanwhile, convergence domain of height subsystem can be reduced as well. Ultimately, simulations on FAHV with actuator constraints, parametric uncertainties and external disturbances are performed using the NARC and conventional anti-saturation controller respectively to demonstrate the superiority of NARC.