Event-triggered model-free adaptive control for a class of surface vessels with time-delay and external disturbance via state observer

This paper provides an improved model-free adaptive control(IMFAC)strategy for solving the surface vessel trajectory tracking issue with time delay and restricted disturbance.Firstly,the original nonlinear time-delay system is transformed into a structure consisting of an unknown residual term and a parameter term with control inputs using a local compact form dynamic linearization(local-CFDL).To take advantage of the resulting structure,use a discrete-time extended state observer(DESO)to estimate the unknown residual factor.Then,according to the study,the inclusion of a time delay has no effect on the linearization structure,and an improved control approach is provided,in which DESO is used to adjust for uncertainties.Furthermore,a DESO-based event-triggered model-free adaptive control(ET-DESO-MFAC)is established by designing event-triggered conditions to assure Lyapunov stability.Only when the system’s indicator fulfills the provided event-triggered condition will the control input signal be updated;otherwise,the control input will stay the same as it is at the last trigger moment.A coordinate compensation approach is developed to reduce the steady-state inaccuracy of trajectory tracking.Finally,simulation experiments are used to assess the effectiveness of the proposed technique for trajectory tracking.

Solar adaptive optics systems for the New Vacuum Solar Telescope at the Fuxian Lake Solar Observatory

Adaptive optics(AO)is essential for high-quality ground-based observations with large telescopes because it counters the impact of wavefront aberrations caused by atmospheric turbulence.The new vacuum solar telescope(NVST)is one of the most important high-resolution solar observation instruments in the world.Three sets of solar adaptive optics systems have been developed and installed on this telescope:conventional adaptive optics,ground layer adaptive optics,and multi-conjugate adaptive optics.These have been in operation from 2018 to 2023.This paper details the development and application of solar adaptive optics on the NVST and discusses the newest instrumentation.

PMSM speed control using adaptive sliding mode control based on an extended state observer

In this study,a composite strategy based on sliding-mode control( SMC) is employed in a permanent-magnet synchronous motor vector control system to improve the system robustness performance against parameter variations and load disturbances. To handle the intrinsic chattering of SMC,an adaptive law and an extended state observer( ESO) are utilized in the speed SMC controller design. The adaptive law is used to estimate the internal parameter variations and compensate for the disturbances caused by model uncertainty. In addition,the ESO is introduced to estimate the load disturbance in real time. The estimated value is used as a feed-forward compensator for the speed adaptive sliding-mode controller to further increase the system's ability to resist disturbances. The proposed composite method,which combines adaptive SMC( ASMC) and ESO,is compared with PI control and ASMC. Both the simulation and experimental results demonstrate that the proposed method alleviates the chattering of SMC systems and improves the dynamic response and robustness of the speed control system against disturbances.

The Educational Adaptive-optics Solar Telescope at the Shanghai Astronomy Museum

The Educational Adaptive-optics Solar Telescope(EAST)at the Shanghai Astronomy Museum has been running routine astronomical observations since 2021.It is a 65-cm-aperture Gregorian solar telescope for scientific education,outreach,and research.The telescope system is designed in an“open”format so that the solar tower architecture can be integrated with it,and visitors can watch the observations live from inside the tower.Equipped with adaptive optics,a high-resolution imaging system,and an integral field unit spectro-imaging system,this telescope can obtain high-resolution solar images in the TiO and Hαbands,and perform spectral image reconstruction using 400 optical fibers at selected wavelengths.It can be used not only in public education and scientific outreach but also in solar physics research.

H_∞tracking design for a class of decentralized nonlinear systems via fuzzy adaptive observer

A novel H∞ tracking-based decentralized indirect adaptive output feedback fuzzy controller for a class of uncertain large-scale nonlinear systems is developed. By virtue of the proper filtering of the observation error dynamics, the observer-based decentralized indirect adaptive fuzzy control scheme is presented for a class of large-scale nonlinear systems using the combination of H∞ tracking technique, a fuzzy adaptive observer and fuzzy inference systems. The output feedback and adaptation mechanisms are both robust and implementable indeed owing to their freedom from the unavailable observation error vector. All the signals of the closed-loop largescale system are guaranteed to stay uniformly bounded and the output errors take on H∞ tracking performance. Simulation results substantiate the effectiveness of the proposed scheme.

Observer-based adaptive control of uncertain time-delay switched systems with stuck actuator faults

This paper concerns the observer-based adaptive control problem of uncertain time-delay switched systems with stuck actuator faults. Under the case where the original controller cannot stabilize the faulty system, multiple adaptive controllers are designed and a suitable switching logic is incorporated to ensure the closed-loop system stability and state tracking. New delay-independent sufficient conditions for asymptotic stability are obtained in terms of linear matrix inequalities based on piecewise Lyapunov stability theory. On the other hand, adaptive laws for on-line updating of some of the controller parameters are also designed to compensate the effect of stuck failures. Finally, simulation results for reference [1] model show that the design is feasible and efficient.

Robust Adaptive Gain Higher Order Sliding Mode Observer Based Control-constrained Nonlinear Model Predictive Control for Spacecraft Formation Flying

This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.

An adaptive stable observer for on board auxiliary inverters with online current identification strategy

An adaptive stable observer with output current online identification strategy for the auxiliary inverters applied in advanced electric trains, such as high speed railway, urban rail, subway and maglev trains, is proposed. The designed observer is used to estimate the state variables, i.e. controllable duty ratio and current components in d-q-o rotary reference frame. The convergence of the observer estimation error is analyzed with consideration of uncertain level variation of input voltage at direct current(DC) side and sufficient conditions are given to prove its practical stability. Experimental results are shown to confirm the effectiveness of the proposed observer.

Observer-based Adaptive Optimal Control for Unknown Singularly Perturbed Nonlinear Systems With Input Constraints

This paper introduces an observer-based adaptive optimal control method for unknown singularly perturbed nonlinear systems with input constraints. First, a multi-time scales dynamic neural network(MTSDNN) observer with a novel updating law derived from a properly designed Lyapunov function is proposed to estimate the system states. Then, an adaptive learning rule driven by the critic NN weight error is presented for the critic NN, which is used to approximate the optimal cost function. Finally, the optimal control action is calculated by online solving the Hamilton-Jacobi-Bellman(HJB)equation associated with the MTSDNN observer and critic NN.The stability of the overall closed-loop system consisting of the MTSDNN observer, the critic NN and the optimal control action is proved. The proposed observer-based optimal control approach has an essential advantage that the system dynamics are not needed for implementation, and only the measured input/output data is needed. Moreover, the proposed optimal control design takes the input constraints into consideration and thus can overcome the restriction of actuator saturation.Simulation results are presented to confirm the validity of the investigated approach.

A novel robust proportional-integral (PI) adaptive observer design for chaos synchronization

In this paper, chaos synchronization in the presence of parameter uncertainty, observer gain perturbation and exogenous input disturbance is considered. A nonlinear non-fragile proportional-integral （PI） adaptive observer is designed for the synchronization of chaotic systems; its stability conditions based on the Lyapunov technique are derived. The observer proportional and integral gains, by converting the conditions into linear matrix inequality （LMI）, are optimally selected from solutions that satisfy the observer stability conditions such that the effect of disturbance on the synchronization error becomes minimized. To show the effectiveness of the proposed method, simulation results for the synchronization of a Lorenz chaotic system with unknown parameters in the presence of an exogenous input disturbance and abrupt gain perturbation are reported.

Observer-Based Adaptive Fuzzy Tracking Control Using Integral Barrier Lyapunov Functionals for A Nonlinear System With Full State Constraints

A new fuzzy adaptive control method is proposed for a class of strict feedback nonlinear systems with immeasurable states and full constraints.The fuzzy logic system is used to design the approximator,which deals with uncertain and continuous functions in the process of backstepping design.The use of an integral barrier Lyapunov function not only ensures that all states are within the bounds of the constraint,but also mixes the states and errors to directly constrain the state,reducing the conservativeness of the constraint satisfaction condition.Considering that the states in most nonlinear systems are immeasurable,a fuzzy adaptive states observer is constructed to estimate the unknown states.Combined with adaptive backstepping technique,an adaptive fuzzy output feedback control method is proposed.The proposed control method ensures that all signals in the closed-loop system are bounded,and that the tracking error converges to a bounded tight set without violating the full state constraint.The simulation results prove the effectiveness of the proposed control scheme.

Design of Observer-based Adaptive Controller for Nonlinear Systems with Unmodeled Dynamics and Actuator Dead-zone

This paper presents an up-to-date study on the observer-based control problem for nonlinear systems in the presence of unmodeled dynamics and actuator dead-zone.By introducing a dynamic signal to dominate the unmodeled dynamics and using an adaptive nonlinear damping to counter the effects of the nonlinearities and dead-zone input,the proposed observer and controller can ensure that the closed-loop system is asymptotically stable in the sense of uniform ultimate boundedness.Only one adaptive parameter is needed no matter how many unknown parameters there are.The system investigated is more general and there is no need to solve Linear matrix inequality （LMI）.Moreover,with our method,some assumptions imposed on nonlinear terms and dead-zone input are relaxed.Finally,simulations illustrate the effectiveness of the proposed adaptive control scheme.

Actuator fault diagnosis of time-delay systems based on adaptive observer

A novel approach for the actuator fault diagnosis of time-delay systems is presented by using an adaptive observer technique. Systems without model uncertainty are initially considered, followed by a discussion of a general situation where the system is subjected to either model uncertainty or external disturbance. An adaptive diagnostic algorithm is developed to diagnose the fault, and a modified version is proposed for general system to improve robustness. The selection of the threshold for fault detection is also discussed. Finally, a numerical example is given to illustrate the efficiency of the proposed method.

A New Criterion of Fault Estimation for Neutral Delay Systems Using Adaptive Observer

这份报纸用适应观察员学习中立延期系统的差错评价的问题。一个新奇快适应差错评价(FAFE ) 算法首先基于适应观察员被建议包括快和精确性提高差错评价的表演。同时，一个延期依赖者标准被建立特别为小延期系统减少设计过程的保守主义。然后，全面分析被介绍用线性矩阵不平等(LMI ) 讨论精明的步技术。最后，模拟结果被介绍说明建议算法的效率。

Robot Interaction Force Estimation Using an Adaptive Sliding Mode Observer

In constrained motion control of a robot,the interaction force is an important variable,which directly describes the state of interaction.It is required in a number of algorithms for interaction control.Desirably,the interaction force has to be measured by force sensors.However,there are inherent limitations with force sensors,such as the cost,sensing noise,limited bandwidth,and the difficulty of physical location at the required place,which is dynamic.In the present paper,the interaction force is estimated by using high order sliding mode observers.An adaptive version of a high order sliding mode observer is developed to robustly reconstruct the interaction force.Experimental results are given to show the effectiveness of the developed algorithms.

Pressure observer based adaptive robust trajectory tracking control of a parallel manipulator driven by pneumatic muscles

This paper presents a pressure observer based adaptive robust controller (POARC) for posture trajectory tracking of a parallel manipulator driven by three pneumatic muscles without pressure sensors. Due to model errors of the static forces and friction forces of pneumatic muscles, simplified average flow rate characteristics of valves, unknown disturbances of entire system, and unmeasured pressures, there exist rather severe parametric uncertainties, nonlinear uncertainties and dynamic uncertainties in modeling of the parallel manipulator. A nonlinear pressure observer is constructed to estimate unknown pressures on the basis of a single-input-single-output (SISO) decoupling model that is simplified from the actual multiple-input-multiple-output (MIMO) coupling model of the parallel manipulator. Then, an adaptive robust controller integrated with the pressure observer is developed to accomplish high precision posture trajectory tracking of the parallel manipulator. The experimental results indicate that the system with the proposed POARC not only achieves good control accuracy and smooth movement but also maintains robustness to disturbances.

Speed-assigned Position Tracking Control of SRM With Adaptive Backstepping Control

A novel speed-assigned method is applied to the position tracking control of switched reluctance motor(SRM).A speed control freedom can be drawn into the position control through speed assignment. Adaptive backstepping control is used to design the position controller for the SRM. The accuracy of position tracking of the SRM can be enhanced with speed assignment. A disturbance observer is further designed to enhance the estimation accuracy of the unknown load torque. Simulation results certify that the design scheme is right and effective.

Stable Adaptive Fuzzy Control with Hysteresis Observer for Three-Axis Micro/Nano Motion Stages

This paper considers the analytical dynamics with simplified Dahl hysteresis model for a three-axis piezoactuated micro/nano flexure stage. An adaptive controller with nonlinear dynamic hysteresis observer is proposed using Lyapunov stability theory. In the controller, a fuzzy function approximator with parameters update law is included to compensate for the identification inaccuracy, model uncertainty, and flexure coupling effects. Simulation results are used to demonstrate the control performance.

Sensor fault diagnosis of time-delay systems based on adaptive observer

Presents a novel approach for the sensor fault diagnosis of time-delay systems by using an adaptive observer technique. The sensor fault is modeled as an additive perturbation described by a time varying function. Systems without model uncertainty are initially considered, followed by a discussion of a general situation where the system is subjected to either model uncertainty or external disturbance. An adaptive diagnostic algorithm is developed to diagnose the fault, and a modified version is proposed for general system to improve robustness. The stability of fault diagnosis system is proved. Finally, a numerical example is given to illustrate the efficiency of the proposed method.

An adaptive load torque observer using hyperstability for PMSM servo system

An adaptive load torque observer is presented to compensate the torque ripple in PMSM servo system. A simple adaptive scheme is derived using Popov's hyperstability theory. The torque ripple detected by the observer is compensated by a feed forwarding equivalent current which gives fast response. The noisy current information is exempt from the observer to avoid its deterioration to the quality of the observer. The speed measurement delay is considered by using observed speed since the instantaneous velocity can't be estimated precisely at low speed because of too few position pulses from the absolute encoder during one time interval. Simulation and experimental results demonstrate that the proposed method can improve the dynamic performance of PMSM servo system satisfyingly.