Actuator Delay Research Articles

Equilibrium stability of a nonlinear structural switching system with actuator delay

In this paper, a Lyapunov–Krasovskii functional is used to obtain sufficient conditions of asymptotic stability for the equilibrium of a nonlinear feedback system with state-dependent uncontrolled switching, herein called structural switching, and with actuator delay. The solution of the problem is addressed in two steps. First, a predictive feedback method is used to compensate the actuator delay of the associated linearized system. Thus, the time-delayed control is replaced with a state delay, and the effect of the control appears in a non-homogeneous term in the linearized system. Second, a theorem of asymptotic stability of equilibrium is obtained for the nonlinear switched system, whose linearized components were considered separately in the first step. The result is also valid for certain problems of state-dependent controlled switching. The numerical application, done on a consecrated real world system, the electrohydraulic servomechanism, highlights real difficulties, which are usually avoided by academic constructs in which the results are sometimes illustrated on insignificant models, represented, for example, by 2 × 2 didactic matrices.

Delay compensated control of the Stefan problem and robustness to delay mismatch

SummaryThis paper presents a control design for the one‐phase Stefan problem under actuator delay via a backstepping method. The Stefan problem represents a liquid‐solid phase change phenomenon which describes the time evolution of a material's temperature profile and the interface position. The actuator delay is modeled by a first‐order hyperbolic partial differential equation (PDE), resulting in a cascaded transport‐diffusion PDE system defined on a time‐varying spatial domain described by an ordinary differential equation (ODE). Two nonlinear backstepping transformations are utilized for the control design. The setpoint restriction is given to guarantee a physical constraint on the proposed controller for the melting process. This constraint ensures the exponential convergence of the moving interface to a setpoint and the exponential stability of the temperature equilibrium profile and the delayed controller in the norm. Furthermore, robustness analysis with respect to the delay mismatch between the plant and the controller is studied, which provides analogous results to the exact compensation by restricting the control gain.

Predictor Feedback for Uncertain Linear Systems With Distributed Input Delays

While the existing literature on delay-adaptive control concentrates on uncertain plants with discrete input delays, this article proposes a predictor feedback for stabilization of uncertain linear systems with distributed input delays. A finite-dimensional linear system with distributed actuator delay may come with five types of uncertainties: unknown delay, unknown delay kernel, unknown plant parameters, unmeasurable finite-dimensional plant state, and unmeasurable infinite-dimensional actuator state. For different combinations of uncertainties, distinct control designs are developed in the article, from which the users can make selections to address a vast range of problems they face.

On The Performance of a Fuzzy Variable Structure Satellite Attitude Controller Under Sensor and Actuator Uncertainties

Controlling the attitude of a satellite with high accuracy and stability under both sensor and actuator delay is a great problem. It is possible to correct for errors, but a robust controller is mo...

On the performance of a fuzzy variable structure satellite attitude controller under sensor and actuator uncertainties

Controlling the attitude of a satellite with high accuracy and stability under both sensor and actuator delay is a great problem. It is possible to correct for errors, but a robust controller is more preferable. In this study, the attitude of a 3-DoF satellite model incorporating uncertainties (delays in handling both sensors and actuators) is controlled using a suitably designed integral fuzzy variable structure (IFVSC) controller. The attitude control accuracy of the IFVSC is evaluated and compared to other reference controllers (one is a PID controller and the other is a loop shaping controller). IFVSC is found to perform well with Td = 0.2 s sensor and actuator data delay.

Optimally Allocated Nonlinear Robust Control of a Reusable Launch Vehicle During Re-entry

A nonlinear robust control design approach is presented in this paper for a prototype reusable launch vehicle (RLV) during the critical re-entry phase where the margin for error is small. A nominal control is designed following the dynamic inversion philosophy for the reaction control system (RCS) and optimal dynamic inversion philosophy for the aerodynamic control actuation. This nominal controller is augmented next with a barrier Lyapunov function based neuro-adaptive control in the inner loop, which enforces the body rates of the actual system i.e. in presence of uncertainties to track the closed-loop body rates of the nominal plant. A fusion logic is also presented for fusing the RCS and aerodynamic control. The control design approach presented here assures robust tracking of the guidance commands despite the presence of uncertainties in the plant model. Extensive nonlinear six degree-of-freedom (DoF) simulation study, which embeds additional practical constraints such as actuator delay in the aerodynamic control actuation and constraints related to the RCS, shows that the proposed design approach has both good command following as well as robustness characteristics.

Event-triggered stabilization of nonlinear systems with time-varying sensing and actuation delay

This paper studies the problem of stabilization of a nonlinear system with time-varying delays in both sensing and actuation using event-triggered control. Our proposed strategy seeks to opportunistically minimize the number of control updates while guaranteeing stabilization and builds on predictor feedback to compensate for arbitrarily large known time-varying delays. We establish, using a Lyapunov approach, the global asymptotic stability of the closed-loop system as long as the open-loop system is globally input-to-state stabilizable in the absence of time delays and sampling. We further prove that the proposed event-triggered law has inter-event times that are uniformly lower bounded and hence does not exhibit Zeno behavior. For the particular case of a stabilizable linear system, we show global exponential stability of the closed-loop system and analyze the trade-off between the rate of exponential convergence and a bound on the sampling frequency. We illustrate these results in simulation and also examine the properties of the proposed event-triggered strategy beyond the class of systems for which stabilization can be guaranteed.

Antilock brake algorithm for heavy commercial road vehicles with delay compensation and chattering mitigation

This work provides a model-based approach to develop a wheel slip regulation scheme for Antilock Braking System (ABS) in Heavy Commercial Road Vehicles (HCRVs). Physical constraints of the actuator in the pneumatic brake system such as operating bandwidth and delay were considered in the design. The slip regulation scheme was designed using Power Rate Exponential Reaching Law (PRERL) based Sliding Mode Controller (SMC), which is a new strategy employed for ABS application. This technique consists of both chattering mitigation and robustness properties. Additionally, the effect of actuator delay on performance deterioration of the slip regulator was studied and an appropriate method was developed to mitigate it. The complete design was evaluated in a Hardware-in-Loop (HiL) experimental setup for several cases of road and load conditions and seen to regulate slip fairly accurately with an average tracking error of . Further, the stopping distance reduction was up to with the controller. The developed algorithm was found to be robust to of mass variations and of road surface variations.

Neural-network-predictor-based control for an uncertain multiple launch rocket system with actuator delay

Development of multiple launch rocket system (MLRS) has been restricted for several decades due to the poor dispersion characteristics of rockets, which is caused by the orientation of the MLRS departing from that intended. Hence, it is vital to maintain the angles of MLRS at a desired value via a proper control strategy. In this paper, a new neural network predictive control is developed for orienting control of the MLRS with actuator delay. First, the dynamic model of motor-mechanism coupling system is established using Lagrange method and field-oriented control theory. Then, for cancelling the effects of nonlinearities and uncertainties, the concept of feedback linearization and a dynamic recurrent neural network are introduced. In addition, a modified Smith predictor is employed to maintain the desirable orienting performance in the occurrence of actuator delay. For the stability analysis, Lyapunov’s method is utilized to ensure uniform ultimate boundedness of the closed-loop system. The simulated and experimental results demonstrate the effectiveness of the proposed controller.

Real-time predictive sliding mode control method for AGV with actuator delay

In this paper, a predictive sliding mode control method based on multi-sensor fusion is proposed to solve the problem of insufficient accuracy in trajectory tracking caused by actuator delay. The controller, based on the kinematics model, uses an inner and outer two-layer structure to achieve decoupling of position control and heading control. A reference positional change rate is introduced into the design of controller, making the automatic guided vehicle (AGV) capable of real-time predictive control ability. A stability analysis and a proof of predictive sliding mode control theory are provided. The experimental results show that the new control algorithm can improve the performance of the AGV controller by referring to the positional change rate, thereby improving the AGV operation without derailing.

Loop Shaping by Single-Resonant Controllers for Prescribed Tracking of Sinusoidal References

It is well-known that in ac-grid-connected or motor-driving converters, current behavior directly sets the exchange of power between the two. Moreover, in corresponding current plants, most of the disturbance (formed by grid voltage or back EMF and the dc-link voltage) may be measured/estimated and appropriately canceled, reducing the current regulation problem to tracking challenge only. The latter is still of extreme importance since the amount of active/reactive power exchanged is proportional to current magnitude and phase. Recently, a method for deriving proportional-resonant controller structure and coefficients according to desired tracking behavior of ac signal amplitude, applied to typical power converter current loop, was proposed based on the fact that if ac signal envelope is perceived as dc signal, its transient behavior may be easily shaped utilizing well-known approaches employed in dc systems loop shaping while keeping zero phase tracking error at all time. This paper extends the proposed methodology by introducing in-depth analysis of the resulting loop gain shaping, applying practical issues, such as actuator delay, damping, and finite word length to the system, yielding a closed set of hands-on design guidelines. Experimental results are also given, providing a two-fold value: successfully validating the presented material and demonstrating that some of the previously reported outcomes (based on simulations) cannot be achieved in practice due to the above mentioned real world constraints.

A real-time hybrid aeroelastic simulation platform for flexible wings

The concept of real-time hybrid aeroelastic simulation for flexible wings is introduced in this paper. In a hybrid aeroelastic simulation, a coupled aeroelastic system is “broken down” into an aerodynamic simulation subsystem and a structural vibration subsystem. The coupling between structural dynamics and aerodynamics is maintained by the real-time communication between the two subsystems. As the vibration of the testing article (a wing member or a full aircraft) is actuated by actuators, hybrid aeroelastic simulation and experiment can eliminate the sizing constraint of the conventional aeroelastic testing performed within a wind-tunnel. It also significantly saves the cost of wind-tunnel testing. However, several critical technical problems (such as process noise, measurement noise, and actuator delay) need to be addressed to enable a hybrid simulation in real-time. This paper proves the concept of real-time hybrid simulation and discusses some of the critical problems underlying the technique.

Adaptive control for a class of nonlinear chaotic systems with quantized input delays

This paper proposes adaptive prediction-based control design for nonlinear chaotic systems in the presence of input quantization with actuator delay. A class of sector-bounded quantizer, namely the hysteresis quantizer, has been used to quantize the control signal. Adaptive scheme is utilized to estimate unknown parameters of the nonlinear chaotic system. A new prediction vector is introduced to compensate actuator delay for nonlinear systems with unknown parameters. The proposed controller does not require the restrictive conditions for quantized parameters in contrast to some existing control schemes for systems with input quantization. By error analysis, it is insured that the upper bound of the state vector norm is limited. Moreover, a maximum allowable upper bound for actuator time-delay is achieved and is guaranteed that for any input delay less than this value, the closed-loop system is stable. To show the efficiency of the proposed method, it is applied to brushless DC motor and Chua’s circuit with delayed hysteresis input and compared to the existing results in the literature. Simulation results show that the proposed method is able to compensate actuator time-delay with hysteresis quantized input for a class of nonlinear systems having unknown parameters. The robustness and efficiency of the suggested approach are illustrated by comparative simulation results.

Internal model-based optimal vibration control for linear vehicle suspension systems with actuator delay

The problem of optimal vibration control for active vehicle suspension systems with actuator delay is considered. Based on the model transformation, the quarter-car suspension system with actuator delay is transformed into a delay-free one. The existence and uniqueness of the optimal control law are proved. The vibration control law is obtained by solving an optimal regulation problem. A dynamic compensator is designed, which is combined by an internal model and an optimal control. The actuator delay is compensated by a control memory term. Numerical simulations are used to illustrate the effectiveness of the optimal vibration control.

Fuzzy Guaranteed Cost $$H\infty$$ Control of Uncertain Nonlinear Fuzzy Vehicle Active Suspension with Random Actuator Delay

This paper focuses on the fuzzy guaranteed cost $$H\infty$$ control problem for uncertain nonlinear vehicle active suspension system with random actuator time delay. Its main contribution to the literature is that a fuzzy guaranteed cost $$H\infty$$ controller (FGCHC) is proposed to ensure the resulting closed-loop vehicle active suspension system to be asymptotically stable and guarantee the performance index to be less than a preset upper bound. More specifically, taking the varying masses and the uncertainties caused by random actuator delay into consideration, a discrete-time Takagi-Sugeno fuzzy model for vehicle active suspension is obtained based on an augmented vector, which is without explicit of random actuator delay. By employing the Lyapunov stability theory and the linear matrix inequality (LMI) approach, the existence condition and the design approach for proposed FGCHC are presented. Meanwhile, the computability for proposed FGCHC is guaranteed by solving a corresponding convex optimization problem. By analyzing performance requirements for vehicle active suspension under different simulation scenarios, simulation results demonstrate that the proposed FGCHC can offset the vibration and compensate the varying masses and uncertainties for vehicle active suspension effectively.

Robust nonfragile H∞ optimum control for active suspension systems with time-varying actuator delay

The active suspension has drawn considerable attention due to its superiority in improving the vehicle vertical dynamics. This paper investigates robust nonfragile H∞ optimal control for the vehicle active suspension with time-varying actuator delay. Firstly, the dynamic equation of an active suspension system with actuator delay is established in terms of the main performance objectives, that is, ride comfort, handling ability, and road holding. Then, a robust nonfragile H∞ optimal controller is proposed to deal with the problem of active suspension control with time delay and actuator uncertainty, which is based on Lyapunov theory, convex optimization, and the linear matrix inequality approach. Finally, a quarter-car test rig is used for an experiment to illustrate the effectiveness of the proposed controller. Simulation and experimental results demonstrate that the proposed controller can ensure the asymptotic stability of the closed-loop system with bounded time-varying actuator delay, while managing the tradeoff between the conflicting performances and achieving performance optimization for the active suspension.

Robust actuator dynamics compensation method for real-time hybrid simulation

Abstract Real-time hybrid simulation (RTHS) is a practical, cost-effective, and versatile experimental technique to evaluate structural performance under dynamic excitation. The simulated structure is commonly split into a physically tested rate-dependent substructure (PS) and a numerically simulated substructure (NS). A transfer system such as a servo-hydraulic actuator is used to impose boundary conditions on the PS. Consequently, efficient actuator control is necessary to guarantee reliable simulation results. However, time delay and uncertainties exist due to the dynamics of the actuator, which adversely influence the accuracy and stability of RTHS. Therefore, an innovative robust actuator dynamics compensation method is proposed in this study comprising three components, namely a mixed sensitivity-based robust H∞ controller to stabilize the actuator–specimen dynamics, a polynomial extrapolation module to further cancel the actuator delay, and an adaptive filter for displacement reconstruction of the actuator–specimen system. A detailed design procedure of the proposed strategy is presented. The efficacy of the proposed strategy is validated through a series of virtual tests on the benchmark problem for RTHS. Results show that the proposed method exhibits excellent tracking performance and robustness. In particular, the maximum values of the calculated time delay (TD), root mean square of the tracking error (RMSE), and peak tracking error (PE) are 0 ms, 2.56%, and 2.12%, respectively, whereas the maximum values of the standard deviation of TD, RMSE, and PE are 0 ms, 0.25%, and 0.33%, respectively.

Input‐delay compensation in a robust adaptive control framework

A modification to the ${\cal L}_1$ control framework for uncertain systems with actuator delay is presented. Specifically, a time delay is introduced in the control input of the state predictor to compensate for the destabilizing effect of input delay in the plant. For this modified framework, the analysis shows that the output of the adaptive system closely follows the behavior of a suitably defined, nonadaptive, stable reference system provided that a delay-dependent stability condition is satisfied and the adaptive gain is chosen sufficiently large. The set of combinations of input delay and compensation delay for which the stability condition is satisfied contains an open set of pairs of positive values provided that a filter bandwidth, characteristic of ${\cal L}_1$ adaptive control is chosen sufficiently large. The efficacy of the delay compensation is illustrated by a simple example. A numerical continuation is also performed to explore the stability region for a case where this can be approximated a priori.

Custom Scanning Hyperspectral Imaging System for Biomedical Applications: Modeling, Benchmarking, and Specifications.

Prototyping hyperspectral imaging devices in current biomedical optics research requires taking into consideration various issues regarding optics, imaging, and instrumentation. In summary, an ideal imaging system should only be limited by exposure time, but there will be technological limitations (e.g., actuator delay and backlash, network delays, or embedded CPU speed) that should be considered, modeled, and optimized. This can be achieved by constructing a multiparametric model for the imaging system in question. The article describes a rotating-mirror scanning hyperspectral imaging device, its multiparametric model, as well as design and calibration protocols used to achieve its optimal performance. The main objective of the manuscript is to describe the device and review this imaging modality, while showcasing technical caveats, models and benchmarks, in an attempt to simplify and standardize specifications, as well as to incentivize prototyping similar future designs.

The Impact Research of Delay Time in Steam Turbine DEH on Power Grid

The effects of different link’s delay time in steam turbine DEH (Digital Electric Hydraulic Control System) on electric power unit are not exactly the same. Through the analysis of the main controller of the steam turbine governor, electro-hydraulic mechanism,steam turbine and the single-machine infinity model, we establish the single-machine infinite power system with simulink. The delay time of the electric power feedback, the speed feedback, the oil actuator and the displacement sensor link in the model is changed to explore the influence of different delay times on the power output of the power system. The results show that the electric power feedback, the speed feedback, the Oil actuator and the delay time of the displacement sensor will increase the overshoot of the electric power response curve and increase the time to reach the stability, but their influence degree.is different, the level of influence from low to high is: speed feedback delay, electric power feedback delay, displacement sensor delay, Oil actuator delay.