High-order Sliding Mode Observer Research Articles

Super-twisting MPPT control for grid-connected PV/battery system using higher order sliding mode observer

In recent times, photovoltaic (PV) power generation has been growing due to increase in energy demand. In grid-connected mode, achieving maximum power (MP) from the PV array is difficult by using conventional techniques due to various reasons like low tracking efficiency, stability issues, etc. This motivates the design of an appropriate control strategy to obtain the maximum power point tracking (MPPT) to harvest MP from the PV array. This paper proposes a combined higher order sliding mode observer (HOSMO)–super-twisting control (STC) for a grid-connected scenario. A perturb and observe (P &O) technique is employed to generate reference voltage, and a HOSMO is proposed to drive the STC by estimating the inductor current of the PV boost converter. The proposed controller performance is evaluated based on response time across various scenarios, including generation changes, dynamic faults, islanding and resynchronization, and load variations in comparison to other existing controllers. These microgrid test cases have been thoroughly simulated, and their effectiveness has been validated in real-time using OPAL-RT (OP4510).

An Output Cooperative Controller for a Hydraulic Support Multi-Cylinder System Based on Neural Network Compensation

The straightness control of a fully mechanized working face is the key technology used in intelligent coal mining, so the position control of a hydraulic support multi-cylinder moving system is of great significance. However, due to the harsh environment of coal mines, complex friction, external disturbances, and the coupling relationship between adjacent cylinders, the accuracy of position control is restricted. Therefore, an output cooperative controller is proposed in this paper for a multi-cylinder system. A high-order sliding mode observer is utilized to estimate the system states with the only available output position signal. A neural network disturbance observer is applied to estimate the lump disturbance of the strict-feedback model, including the system uncertainty, disturbance force and the coupling force between adjacent cylinders. Then, continuous motion position tracking simulation is conducted and the estimation performance of the state observer and neural network is analyzed. Furthermore, a multi-cylinder collaborative control test rig is designed, and experiments based on the actual actions of the hydraulic support are conducted. The results show that the proposed output cooperative controller has an excellent position control performance compared with the traditional proportional–integral controller.

DFIG in Wind Energy Applications with High Order Sliding Mode Observer-based Fault-Tolerant Control Scheme using Sea Gull Optimization

This paper describes a new method for maximizing power extraction from a wind energy conversion system (WECS) by using a doubly fed induction generator (DFIG) that operates below nominal wind speed. To maximize the collected power of a wind turbine (WTG) exposed to actuator failure, a fault-tolerant high-order sliding mode observer (HOSMO) and Seagull Optimization Algorithm with a model predictive controller (MPC) technique is proposed. Evaluate both the real state and the sensor error simultaneously using a higher-order sliding-mode observer. Active fault tolerant controllers are designed to regulate wind turbine rotor speed and power in the presence of actuator defects and uncertainty. With the growing interest in employing wind turbines (WTGs) as the primary generators of electrical energy, fault tolerance has been seen as essential to improving efficiency and reliability. This research focuses on optimal fault-tolerant pitch control, which is used to modify the pitch angle of wind turbine blades in the event of sensor, actuator, and system failures. A Seagull Optimization Algorithm (SOA) is proposed to tune controller parameters to improve the performance of WT. The proposed method has achieved 92% of power tracking performance when compared to existing method.

High order sliding mode observer-based fault-tolerant control scheme for DFIG in wind energy applications with model predictive controller

This research presents a novel fault-tolerant predictive power control method for a Doubly-fed induction generator (DFIG) used in wind turbine control systems. Due to the proposed control mechanism, the system can continue to function effectively despite open-circuit or short-circuit faults in the insulated-gate bipolar transistors (IGBTs) of the MPC controller. Depending on the type of problem and its location, the tolerant IGBT overcomes power oscillations and limits the power converter's potential switching states. By monitoring the optimal generator speed, wind turbine control systems strive to maximize power output. For wind turbines operating in the partial-load area, a fault-tolerant model predictive control strategy is recommended in order to achieve control goals despite disturbances, uncertainties, sensor, and actuator difficulties. A high order sliding mode observer (HOSMO) is used to evaluate both the actual states and sensor-faults at the same time. A high order sliding mode (HOSM) control strategy based on the MPC controller is used to regulate the speed of wind turbines in order to harness the wind's maximum power.

Fast Finite-Time Super-Twisting Sliding Mode Control with an Extended State Higher-Order Sliding Mode Observer for UUV Trajectory Tracking

This paper proposes a trajectory tracking control scheme consisting of a fast finite-time super-twisting sliding mode control (FSTSMC) approach and an extended state higher-order sliding mode observer (ESHSMO) for unmanned underwater vehicles (UUVs) with external disturbances and model uncertainties. Firstly, an extended state higher-order sliding mode observer with the finite-time convergence is designed based on the higher-order sliding mode technique and the extended state observer technique. Next, on the basis of disturbances and model uncertainties observation, a fast finite-time super-twisting sliding mode control approach is proposed, and the finite time stabilization property of the tracking errors is proved by Lyapunov theory. Finally, through numerical simulation and experiment in a water pool, it has been verified that the proposed control scheme has achieved the high control precision, the smaller chattering, the disturbance compensation and the fast finite-time convergence in UUV trajectory tracking.

Adaptive-Robust Controller for Smart Exoskeleton Robot.

Rehabilitation robotics has seen growing popularity in recent years due to its immense potential for improving the lives of people with disabilities. However, the complex, uncertain dynamics of these systems present significant control challenges, requiring advanced techniques. This paper introduces a novel adaptive control framework integrating modified function approximation (MFAT) and double-integral non-singular terminal sliding mode control (DINTSMC). The goal is to achieve precise tracking performance, high robustness, a fast response, a finite convergence time, reduced chattering, and effective handling of unknown system dynamics. A key feature is the incorporation of a higher-order sliding mode observer, eliminating the need for velocity feedback. This provides a new solution for overcoming the inherent variations and uncertainties in robot manipulators, enabling improved accuracy within fixed convergence times. The efficacy of the proposed approach was validated through simulations and experiments on an exoskeleton robot. The results successfully demonstrated the controller's effectiveness. Stability analysis using Lyapunov theory proved the closed-loop system's uniform ultimate boundedness. This contribution is expected to enable enhanced control for rehabilitation robots and improved patient outcomes.

Higher Order Sliding Mode Observer Based Fast Composite Backstepping Control for HESS in DC Microgrids

Higher Order Sliding Mode Observer Based Fast Composite Backstepping Control for HESS in DC Microgrids

Advanced control strategy for magnetic levitation system: a higher order sliding mode observer approach

Advanced control strategy for magnetic levitation system: a higher order sliding mode observer approach

Disturbance observer-based robust optimal control of rate-dependent hysteretic systems: Application to a piezoelectric nano-manipulator

This article investigates the robust and optimal control problem of hysteretic systems with both parameter variations and unmodeled dynamics. By means of a hysteresis compensator based on a modified Prandtl–Ishlinskii model and a feedback controller, a novel robust optimal control architecture is proposed to address the asymmetric and rate-dependent hysteresis nonlinearities and various disturbances, where the compensation errors, parameter variations, and unmodeled dynamics are treated as a bounded disturbance. The proposed controller is composed of two components: a high order sliding mode observer and an extended linear quadratic controller. The high order sliding mode observer is introduced to guarantee that the disturbance observation error converges to the origin in a finite time such that the extended linear quadratic controller enables the predefined optimal performance to be achieved. Moreover, the exponential stability of the closed-loop system has been proven, and some sufficient conditions are given. Finally, the proposed control algorithm is applied to a piezoelectric nano-manipulator system, both the good hysteresis modeling accuracy and excellent tracking performance are demonstrated in the real-time experiments.

Nonlinear observer-based adaptive control of ground vehicles with uncertainty estimation

In this work, a nonlinear observer-based controller is designed for the attitude control of a ground vehicle with uncertainty estimation. This controller ensures the tracking of desired references in the presence of environmental disturbances and parametric uncertainties, making use of high-order sliding-mode estimators to estimate these perturbations. Furthermore, the controller incorporates a kinematic observer reconstructing the lateral vehicle velocity, based on a novel high-order sliding-mode observer. The proposed controller ensures good performance and better transient behavior with respect to existing controllers when parametric uncertainties and environmental disturbances are present. Its performance is evaluated by numerical simulation in CarSim, considering a challenging double turn maneuver, which is described in the ISO-3888 specifications.

Cooperative Game Theory based robust shared lateral control for Driver Vehicle Interactions

Extensive manual driving is liable to attention lapses and driver exhaustion resulting in lane offset errors, driver comfort minimization and degradation in vehicle stability. On the contrary, apart from being expensive, autonomous vehicles suffer from the issue of trust, ethics and traffic mapping. In order to address the above limitations, this paper deals with the design of a Game Theoretic based Shared Control (GTSC) framework that enables an interaction between the human and the machine. The novelty lies in the generation of automatic driver automation relative weights based on the vehicle’s lateral position relative to the maximum admissible lateral offset. The interaction between the human driver and automated system based on the cooperative game theory is utilized to develop a robust shared control framework. The driver model parameters have been estimated using the experimentally obtained driver steering torque and steering wheel angle respectively through an inverse modelling procedure. The lateral dynamics of the vehicle model in the presence of crosswinds and yaw moment as disturbances are considered for the design. A higher order sliding mode observer is designed to ensure robust estimation of the unknown states. Unlike the existing studies that primarily concentrates on the robust game theoretic shared controller design, this new study broadens its focus. The study introduces an observer-based robust design for GTSC and establishes the stability of the closed-loop system. The effectiveness of this proposed framework is verified through simulations in Carsim as well as real-world testing on a Hardware-in-the-loop (HIL) platform with a human driver. The study also addresses the challenge of obstacle avoidance using the GTSC framework. Comparisons have been performed with the state-of-the-art shared control studies while considering factors like crosswinds, variation in the longitudinal velocities and alterations in the reference path to evaluate the effectiveness of the proposed shared control study. The results demonstrate the improvement in the lateral offset, driver comfort and the vehicle stability compared to the manual control of the vehicle.

An Improved Full-Speed Domain Sensorless Control Scheme for Permanent Magnet Synchronous Motor Based on Hybrid Position Observer and Disturbance Rejection Optimization

A sensorless control algorithm not only reduces the cost of a permanent magnet synchronous motor (PMSM) system, but also broadens its application scope. Expanding speed threshold and enhancing dynamic performance are crucial aspects. To optimize the adaptability of observers and the immunity of the controller in a full-speed domain, an improved sensorless control scheme for a PMSM based on a hybrid position observer and disturbance compensation is proposed. Firstly, the precise detection of the initial position and the scheme of starting with the load at any position are proposed based on high-frequency rotation injection, magnetic pole direction calibration and square-wave high-frequency injection (HFI). Secondly, a higher-order sliding mode observer (HSMO) is designed to improve high-speed observation performance by introducing an extended electromotive force (EEMF). Correspondingly, a speed controller called PI plus is developed utilizing a reverse control algorithm and the observed disturbance quantity, which further enhances the system’s disturbance rejection capability. Subsequently, a linearly weighted observer switching method and a linear signal withdrawal scheme are proposed to suppress torque and speed oscillations in medium-speed threshold. Furthermore, a normalized linear extended state observer (LESO) is designed to enhance rotor information estimation accuracy and enable the observation of unknown disturbances in full-speed thresholds. Finally, the effectiveness of the proposed sensorless control system is tested through experiments involving variations in speed, load, and parameter. The experimental results indicate that the proposed sensorless strategy is capable of achieving a loaded start. The designed observer switching strategy and the scheme of injection signal withdrawal contribute to a smoother acceleration process. Furthermore, load variation test results at high-speed thresholds demonstrate that the proposed controller can reduce speed drop by 45 rpm compared to a traditional PI. Additionally, the results of parameter variation testing validate the observer’s robustness in the disturbances of ψf within the range of ±0.3 pu.

Robust Observer-Based Visual Servo Control for Quadrotors Tracking Unknown Moving Targets

This article addresses the image-based control problem of a quadrotor for tracking an unknown moving target under external disturbances. Based on the continuous observer design, a constructive image-based visual servoing (IBVS) geometric tracking control strategy is proposed and utilized. First, a higher order sliding mode observer is designed based on image dynamics for continuous estimation of unmeasurable linear velocities and time-varying disturbances. Furthermore, exploiting the linear quadratic regulator optimal design method, an outer loop IBVS controller is proposed such that the position of the quadrotor converges to the desired tracking pattern. Next, an inner loop geometric controller is designed using Lie algebra functions to regulate the attitudes. Based on the Lyapunov stability theory, it is rigorously proven that the proposed IBVS geometric controller achieves asymptotic stability. Finally, the effectiveness and robustness of the proposed approach against uncertain targets, time-varying disturbances, and large initial inclination angles are demonstrated through numerical simulations and experiments.

Resilient Event-Triggered Adaptive Cooperative Fault-Tolerant Tracking Control for Multiagent Systems Under Hybrid Actuator Faults and Communication Constraints

This paper investigates the cooperative fault-tolerant tracking problem for multiagent systems with directed topology that experience communication link faults and actuator faults under malicious attacks. Based on a resilient event-triggered mechanism, a novel distributed high-order sliding-mode observer and a robust adaptive cooperative fault-tolerant control method are proposed, which can achieve the desired formation shape tracking under communication limitations and hybrid actuator faults caused by malicious attacks. First, the designed distributed event-triggered observer can estimate the unknown leader. Second, the proposed event-triggered mechanism can be used to reduce the impact of malicious attacks on the information and physical layers of the multiagent system. Additionally, the utilization rate of network communication is further improved so that it can save communication resources by reducing the number of event triggers. Then, based on the information of the leader, the designed robust adaptive cooperative fault-tolerant controller can compensate for the influence of the hybrid actuator faults on the system under malicious attacks. Finally, the effectiveness of the method is verified by two sets of example simulations.

Higher Order Sliding-Mode Observers for State-of-Charge and State-of-Health Estimation of Lithium-Ion Batteries

This paper proposes a new higher-order sliding mode-based approach to deal with the problem of online state of charge (SOC) and state of health (SOH) estimation for Lithium-ion batteries. The proposed approach is based on the conjunction of a Higher-Order Sliding Mode (HOSM) observer with two Generalized Super-Twisting (GST) observer-based identification algorithms. The HOSM observer provides an exact estimation of SOC, while the two identification algorithms guarantee the finite time estimation of the battery capacity and the battery inner resistance. Thanks to the relationship between the battery capacity and the SOH, an accurate estimation of this latter is obtained. The proposed approach has two main advantages: it ensures SOC estimation using only one observer and estimates the battery parameters without requiring any assumption on the system states. Experimental results using the Worldwide Harmonized Light Vehicles Test procedures (WLTP) are used to illustrate the high efficiency of the proposed approach.

Terminal super-twisting sliding mode based on high order sliding mode observer for two DOFs lower limb system

In this paper, a novel backstepping terminal super-twisting sliding mode (TSTSM) with high order sliding mode observer (HOSMO) is proposed to control the two degrees of freedom (DOFs) Serial Elastic Actuator (SEA), inspired by a lower limb of humanoid robots. First, the dynamic model, extended from our previous study, is presented for developing the control algorithm. Secondly, the backstepping technique is utilized to separate the overall system into two subsystems. One of the challenges of SEA is to deal with the evident oscillations caused by the elastic element, which might lead to the degrading performance of load position control. In order to reduce this adverse effect, a TSTSM is proposed to control the position tracking of two subsystems. The advantages of TSTSM are the finite-time convergence despite the bounded perturbation and the dramatic reduction of the chattering phenomenon. To construct and implement the TSTSM controller, it requires the knowledge of all states, which is not available in the current lower limb system setup. Therefore, a HOSMO is utilized to estimate the unknown states. Finally, experiment results are carried out to assess the effectiveness of the proposed controller and compare it with those of different control schemes.

Robust output feedback control for electro-hydraulic servo system with error constraint based on high-order sliding mode observer

In this paper, a robust output feedback controller with error constraint is proposed to improve the position tracking performance of the electro-hydraulic servo system. Since only the position signal of the system is available, a high-order sliding mode observer is designed to estimate the unobtainable system states. The new state observer can not only avoid the influence of sensor measurement noise but also reduce the chattering of traditional sliding mode observer. To cope with the modeling error, parameter uncertainty, and external disturbance, a robust controller based on backstepping method is designed. In addition, barrier Lyapunov function is introduced to limit the maximum tracking error to a preset range. Finally, comparative experiments are carried out on the asymmetric hydraulic cylinder test bench. The experimental result shows that the proposed controller has a satisfied tracking performance.

Delay Estimation for Nonlinear Systems With Unknown Output Delay

In this letter, the problems of delay identifiability and delay estimation for a nonlinear systems subject to constant unknown output delay are studied. Usually, the estimation of such delay is based on a monotonic condition which is hard to satisfy in the case of nonlinear systems. To deal with this open and interesting problem, a change of coordinates is introduced in this letter to transform the nonlinear system to the triangular form. Then, a high order sliding mode observer is designed based on implicit Lyapunov function to estimate the state and delayed-input, based on these estimation, the delay estimator is proposed. The convergence of the proposed observer is proved and the effectiveness of the proposed method is illustrated through simulation results of an Electro-Hydraulic Actuator (EHA) system.

A High-Order Sliding-Mode Adaptive Observer for Uncertain Nonlinear Systems

A high-order sliding-mode adaptive observer is proposed to solve the problem of an adaptive estimation, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.,</i> the simultaneous estimation of the state and parameters, for a class of uncertain nonlinear systems in the presence of external disturbances, which do not need to satisfy a relative degree condition equal to one. This approach is based on a high-order sliding-mode observer and a nonlinear parameter identification algorithm. The practical, global, and uniform asymptotic stability of the adaptive estimation error, despite the external disturbances, is guaranteed through the small-gain theorem. The convergence proofs are developed based on the Lyapunov and input-to-state stability theories. Some simulation results illustrate the performance of the proposed high-order sliding-mode adaptive observer.

Comparative Analysis of a Family of Sliding Mode Observers under Real-Time Conditions for the Monitoring in the Bioethanol Production

Online monitoring of fermentation processes is a necessary task to determine concentrations of key biochemical compounds, diagnose faults in process operations, and implement feedback controllers. However, obtaining the signals of all-important variables in a real process is a task that may be difficult and expensive due to the lack of adequate sensors, or simply because some variables cannot be directly measured. From the above, a model-based approach such as state observers may be a viable alternative to solve the estimation problem. This work shows a comparative analysis of the real-time performance of a family of sliding-mode observers for reconstructing key variables in a batch bioreactor for fermentative ethanol production. These observers were selected for their robust performance under model uncertainties and finite-time estimation convergence. The selected sliding-mode observers were the first-order sliding mode observer, the proportional sliding mode observer, and the high-order sliding mode observer. For estimation purposes, a power law kinetic model for ethanol production by Saccharomyces cerevisiae was performed. A hybrid methodology allows the kinetic parameters to be adjusted, and an approach based on inference diagrams allows the observability of the model to be determined. The experimental results reported here show that the observers under analysis were robust to modeling errors and measurement noise. Moreover, the proportional sliding-mode observer was the algorithm that exhibited the best performance.