Adaptive Sliding Mode Observer Research Articles

Integral terminal sliding mode fault tolerant control of quadcopter UAV systems

The article presents an active fault-tolerant control scheme with an integral terminal sliding mode controller for the UAV systems. This scheme effectively addresses saturation issues, disturbances, and sensor and actuator faults. Initially, the quadcopter UAV's model is represented in state space form. Subsequently, an augmented system incorporating auxiliary states from sensor faults is developed. An adaptive sliding mode observer is proposed for estimating the actuator and sensor faults. The integral terminal sliding mode fault-tolerant control, designed for altitude and attitude regulation, relies on fault estimation data. In contrast, a cascade proportional-integral-derivative (PID) controller is employed for position control. Simulation results demonstrate the superiority of the proposed method over existing control algorithms.

Estimation of SOC in Lithium-Iron-Phosphate Batteries Using an Adaptive Sliding Mode Observer with Simplified Hysteresis Model during Electric Vehicle Duty Cycles

This paper develops a model for lithium-ion batteries under dynamic stress testing (DST) and federal urban driving schedule (FUDS) conditions that incorporates associated hysteresis characteristics of 18650-format lithium iron-phosphate batteries. Additionally, it introduces the adaptive sliding mode observer algorithm (ASMO) to achieve robust and swiftly accurate estimation of the state of charge (SOC) of lithium-iron-phosphate batteries during electric vehicle duty cycles. The established simplified hysteresis model in this paper significantly enhances the fitting accuracy during charging and discharging processes, compensating for voltage deviations induced by hysteresis characteristics. The SOC estimation, even in the face of model parameter changes under complex working conditions during electric vehicle duty cycles, maintains high robustness by capitalizing on the easy convergence and parameter insensitivity of ASMO. Lastly, experiments conducted under different temperatures and FUDS and DST conditions validate that the SOC estimation of lithium-iron-phosphate batteries, based on the adaptive sliding-mode observer and the simplified hysteresis model, exhibits enhanced robustness and faster convergence under complex working conditions and temperature variations during electric vehicle duty cycles.

Disturbance‐observer‐based fault‐tolerant control of robotic manipulator: A fixed‐time adaptive approach

AbstractThe concurrent existence of model uncertainties, external disturbances, and actuator faults in a nonlinear system such as a robotic manipulator can significantly affect the trajectory tracking performance of these systems. Therefore this study is devoted to proposing a control approach based on fixed‐time control theory to improve the trajectory tracking performance of the robotic manipulator in the presence of lumped disturbance, including uncertainties, external disturbances, and actuator faults. The control approach in this paper is designed based on the integration of a fixed‐time adaptive sliding mode observer and a fixed‐time non‐singular fast terminal sliding mode control design strategy. Firstly, a new fixed‐time adaptive sliding mode observer is designed based on fixed‐time theory and adaptive control theory to estimate the lumped disturbance present in the system. Then, using the information from the disturbance observer, the fixed‐time non‐singular fast terminal sliding mode control is devised based on a non‐singular fixed‐time sliding surface and a fixed‐time reaching approach. Furthermore, in the sense of the Lyapunov theorem, through rigorous analysis, it is demonstrated that the tracking errors of the closed‐loop system converge to a small neighbourhood within a fixed time, regardless of the information about the initial conditions of the states of the system. Finally, extensive comparative simulations are performed using the PUMA560 robot to manifest the feasibility and validity of the proposed control strategy in terms of trajectory tracking accuracy and fast convergence in the presence of uncertainties, disturbances, and actuator faults.

Fuzzy-tolerant-strategy for constrained nonlinear system via adaptive observer

This article considers the tracking control of nonlinear system with state constraints and faults. A fuzzy tolerant control approach on adaptive sliding-mode observer is proposed to accomplish good tracking performance. Firstly, for the purpose of getting the unknown state, a state estimator based on the fuzzy logic systems (FLSs) is designed. Secondly, a fuzzy observer by variable structure method is posed to approximate the faults, and the finite time convergence of observation error is proven. Furthermore, a two-layer nested adaptive law is constructed to improve the observer. Thirdly, a fuzzy backstepping tolerant controller based on super-twisting differentiator is proposed. In which, the barrier Lyapunov function is designed to counter the state constraints, and the super-twisting estimator is employed to estimate the derivative of virtual control input. Finally, two simulation results are analyzed to demonstrate the potential of the developed schemes.

Adaptive practical predefined-time leader-follower consensus for second-order multiagent systems with uncertain disturbances

This article investigates the predefined-time consensus tracking problem for second-order multiagent systems (MASs) with uncertain disturbances. First, a distributed estimator is proposed to estimate the leader's states within predefined time. Then, a novel sliding mode surface is constructed and an adaptive sliding mode observer is established to estimate the uncertain disturbances within predefined time. Subsequently, by employing the predefined-time sliding surface and the adaptive technique, a novel adaptive sliding mode consensus protocol is proposed to overcome the singularity problem and achieve practical predefined-time convergence of the tracking errors to the neighborhood of origin. The Lyapunov approach is employed to prove the practical predefined-time stability of second-order MAS and the settling time is only determined by a single parameter, which facilitates the control protocol design according to the convergence time requirement. Simulation results illustrate the effectiveness of the proposed control scheme.

A switching gain adaptive sliding mode observer for SoC estimation of lithium-ion battery

A new state of charge (SoC) estimation method for lithium-ion battery that uses a Switching Gain Adaptive Sliding Mode Observer (SGASMO) is proposed. The purpose of SGASMO is to reduce the chattering of estimated results from the sliding mode observers (SMOs) and improve the estimation accuracy. First, the Dual Polarization (DP) equivalent circuit model is selected and its parameters are identified to provide a basis for the design of the new SMO. Second, based on the DP model, the nonlinear terminal sliding surface and continuous control law were introduced. And an improved switching gain equation was designed, which is adaptively adjusted according to the sliding mode surface equation. Thus, the SGASMO was realized, and the convergence of the proposed observer was proved by the Lyapunov stability theory. Finally, based on the test data of the self-built experimental platform, it is verified that the proposed SGASMO has less jitter in the estimated results and better estimation accuracy and robustness compared with the conventional SMOs and other types of mainstream improved SMOs.

SOC estimation and fault identification strategy of energy storage battery PACK: Based on adaptive sliding mode observer

AbstractAccurate state of charge (SOC) estimation and fault identification and localization are crucial in the field of battery system management. This article proposes an innovative method based on sliding mode observation theory for SOC estimation and short‐circuit fault location. The core of this new method is the design of an adaptive sliding mode observer, which reduces jitter by introducing adaptive switching gain, establishes an internal loop of gain and error, and improves the performance of SOC estimation. In addition, recursive least squares method was used to identify the key parameters of the model. Secondly, based on obtaining the SOC of each battery cell in series with the energy storage PACK, the specificity of the faulty battery cell in SOC change trend is utilized to identify and locate the short‐circuit fault of the energy storage PACK. The simulation and test results show that the designed adaptive sliding mode observer can significantly improve the estimation accuracy of SOC and has better stability. Compared to the commonly used Kalman estimation and BP neural network estimation methods, the designed method has improved accuracy by 5.53% and 3.42%, respectively. In addition, based on the accurate identification of SOC, the short‐circuit fault diagnosis results of the battery PACK have a high accuracy, confirming the feasibility and effectiveness of the designed strategy that includes SOC estimation and short‐circuit fault identification and positioning, and has broad application prospects.

Core loss resistance impact on sensorless speed control of an induction motor using hybrid adaptive sliding mode observer

Core loss resistance impact on sensorless speed control of an induction motor using hybrid adaptive sliding mode observer

Sensorless Control of PMSM With Improved Adaptive Super-Twisting Sliding Mode Observer and IST-QSG

Sensorless Control of PMSM With Improved Adaptive Super-Twisting Sliding Mode Observer and IST-QSG

Adaptive sliding mode observers‐based dissipative Hamilton finite time optimization control for the speed and tension system of reversible cold strip rolling mill

SummaryFor the complex time‐varying uncertain nonlinear speed and tension system of reversible cold strip rolling mill, an adaptive sliding mode observers (ASMOs)‐based dissipative Hamilton finite time optimization control method is given in this article. First, the ASMOs are developed to observe rolling mill system's unmatched uncertainties, and their observation errors can converge to the origin in finite time. Second, combined with rolling mill system's physical structure characteristics, its dissipative Hamilton model is established by pre‐feedback processing, and then the dissipative Hamilton finite time controllers are designed based on interconnection and damping configuration and energy shaping method, and the system states can converge in finite time. Third, the adaptive mutation particle swarm optimization algorithm is adopted to optimize the controller parameters, which can further improve rolling mill system's control performance. Finally, the simulation results verify the validity of the given method based on actual field data.

Robust Fault Estimation and Tolerant Control for Uncertain Takagi–Sugeno Fuzzy Systems

This research addresses the intricate challenges of fault estimation (FE) and fault-tolerant control (FTC) within a specific subset of T-S fuzzy systems. These systems are characterized by their localized nonlinear models, the presence of unknown inputs, actuator imperfections, and disruptive output disturbances, making them fertile ground for exploration in this study. The contributions of this paper can be summarized as follows: (1) First, we employ coordinate transformation matrices to convert the T-S fuzzy model. This transformation separates the unknown inputs and disturbances at the output. Subsequently, we equip the modified system with a T-S fuzzy adaptive sliding mode observer (ASMO) that serves the dual purpose of fortifying resilience against disruptions and adeptly deducing an extensive spectrum of fluctuating actuator failure signals. (2) In the next step, the insights gained from FE are harnessed to craft a dynamic fuzzy output feedback fault-tolerant controller (DOFFTC). This controller aims to mitigate the effects of actuator errors to maintain the stability of the closed-loop system. The article creates the necessary conditions for the presence of the required ASMO and DOFFTC using H-infinity filtering methods. To address the optimization issue posed by these criteria, we utilize linear matrix inequalities (LMIs) and calculate the required gains for implementation using convex optimization techniques. (3) The study concludes by illustrating the applicability of the proposed techniques with an example employing an inverted pendulum. This paper presents a comprehensive approach to overcoming the challenges of FE and FTC within T-S fuzzy systems. It leverages precise mathematical formulations and optimization strategies to achieve resilient and dependable control, even when confronted with intricate system dynamics.

Sensorless control of SPMSM based on an adaptive sliding mode observer with optimized phase-locked loop structure

To improve the speed and position detection accuracy of surface-mount permanent magnet synchronous motor (SPMSM) vector control and reduce unnecessary chattering of the system, this paper proposes a sensorless control strategy of SPMSM based on an adaptive sliding mode observer (ASMO) with optimized phase-locked loop (OPLL) structure. First, in order to overcome the chattering of system caused by discontinuous switching characteristic of signum function in conventional sliding mode observer (CSMO), a continuous saturation function is selected as the switching function. The ASMO adopts the system state-related adaptive gain function to adjust the switching gain value of the system in real time, which overcomes the slow response speed or severe chattering of the system caused by the constant switching gain of CSMO. Second, to reduce the phase delay between the rotor position estimation value and the actual value caused by the adoption of low-pass filter (LPF) and the position estimation error caused by arctangent function method, an OPLL method is designed for accurate estimation of rotor position and speed. Finally, the effectiveness and feasibility of the proposed improved SMO algorithm is verified by simulation and experiments on an SPMSM with rated power of 2 kW.

Design of permanent magnet synchronous motor control system for electric vehicle air conditioning compressor

The permanent magnet synchronous motor (PMSM) is extensively utilized in electric vehicle air conditioning compressor control systems due to its numerous advantages, including high efficiency, lightweight design, compact size, excellent reliability, and low maintenance costs. In order to achieve PMSM without position sensor full speed range operation, this paper designs an optimized control strategy for full speed range operation. At low and zero speed, the I/F control mode is employed to achieve quick motor startup with minimized repetition rate, avoiding the overcurrent problem that is easy to occur by traditional V/F control, and the control is switched to the Phase-locked Loop (PLL) adaptive sliding mode observer (SMO) for position estimation at medium and high speed, avoiding the problems of high-frequency jitter and low position accuracy of traditional SMO. The feasibility of this strategy is confirmed by the simulation results of Simulink.

Designing an adaptive robust observer for underactuation fault diagnosis of a remote sensing satellite

SummaryThis paper mainly aims at the underactuated case diagnosis due to an actuator failure for a remote sensing satellite. We consider healthy initial conditions for the actuators to investigate the underactuation fault in an attitude tracking control problem. Reaction wheels are the onboard actuators, and a new fault injection mechanism on the speed characteristic is introduced using the multi‐fault function. The fault detection and diagnosis strategy is based on the sliding mode and adaptive sliding mode observers in a finite‐time decision window. The robust observer and adaptive threshold are designed to detect the fault, and the adaptive robust observer estimates the fault model. The residual signal is evaluated by forming the window with fixed thresholds, and in the decision steps, priority is given to the underactuation fault diagnosis. System performance is presented for two actuator fault scenarios in a snapshot imaging mode to understand this case clearly. Numerical simulations close to in‐orbit conditions confirm the satisfactory performance of the proposed strategy that underactuated case is diagnosed by injecting stuck and idle faults around 2.19 and 3.52 s. The times obtained in this study are guaranteed with a 3‐sigma confidence level statistical characteristic. Furthermore, the results of the present work are validated using an air‐bearing experimental test bed to illustrate a more realistic behavior of an underactuated satellite.

Assessment of a PLL‐ASMO position/speed estimator for sensor‐less control of rotor‐tied DFIG (RDFIG)

AbstractIn this paper, an adaptive sliding mode observer (ASMO) associated with a phase locked loop (PLL) is assessed for the sensor‐less control of a rotor‐tied doubly‐fed induction generator (RDFIG). In the proposed PLL‐ASMO estimator, the ASMO utilizes the stator current, the stator voltage, and the back electromotive force (EMF) as state variables. The proposed ASMO is used in order to estimate the back‐EMF from which the slip position/speed is extracted using a PLL. The design of the ASMO gains is based on the Lyapunov stability criteria to ensure the convergence of the proposed observer in a finite time. Therefore, the main contribution of this paper is to propose a PLL‐based ASMO estimator that aims to improve the estimation by reducing the chattering effect. A comparative study between the standard PLL‐SMO estimator and the PLL‐ASMO estimator is presented. Also, For the first time, an adaptive sliding mode observer is used for the sensor‐less control of a RDFIG. The performance of the proposed sensor‐less control strategy is validated through simulation and experimental measurements under various operating conditions. Furthermore, the estimator is shown to be robust to machine parameter variation.

Robust adaptive sliding mode observer for core temperature and state of charge monitoring of Li-ion battery: A simulation study

State of charge (SOC) and temperature monitoring of Li-ion batteries (LIBs) via battery management system (BMS) is crucial to ensure proper and secure performance of LIBs. Monitoring methods based on electrochemical models are highly accurate, which stems from their phenomenological nature; however, such multi-dimensional and rigorous models are computationally time-consuming and elaborate to implement. Consequently, a relatively accurate but more straight-forward estimation method with fast computational capabilities is needed in real-life BMS applications. In this work, an equivalent circuit model (ECM) together with a lumped thermal model has been considered as design model for an online adaptive sliding mode observer. This observer uses measurement of battery terminal voltage and surface temperature in order to estimate SOC and core temperature, both of which play decisive role in BMS applications. The proposed observer performance has been validated in constant current and urban dynamometer driving schedule (UDDS) load profile experiments, where inspection of results overwhelmingly indicates its utmost stability as well as robust performance in comparison with commonly used observers.

Multi-dimensional vector control for six-phase interior permanent magnet synchronous motor sensorless drive system

In order to realize high-performance control of six-phase interior permanent magnet synchronous motor (IPMSM), a multi-dimensional sensorless vector control scheme is discussed in this paper. Firstly, a new adaptive sliding mode observer (SMO) is designed to estimate the speed and rotor position information online, avoiding the phase delay caused by the traditional SMO method using the low-pass filter, and the detailed design method of observer parameters is given. In addition, the designed multi-dimensional vector control strategy fully exploits the advantages of multi-degree of freedom control for multi-phase motor drive system, considers the influence of x-y harmonic subspace, and sets the reference value of the current loop in harmonic subspace to zero to solve the stator current unbalance problem. Finally, the simulation model of the proposed control algorithm is built based on Matlab/Simulink simulation software, and the simulation results verify that the employed control technology has good control quality.

Model-based observer for vehicle proton exchange membrane fuel cell humidity based on adaptive sliding mode estimation technique

Real-time humidity acquisition for vehicle proton exchange membrane fuel cell (PEMFC) facilitates humidity control to avoid membrane flooding or drying, improving its efficiency and stability. However, due to the frequent changes of actual vehicle conditions and expensive as well as unreliable humidity sensors, it is difficult to obtain real-time water content in PEMFC, which brings obstacles to closed-loop control of humidity. To this end, a model-based observer is proposed to obtain real-time humidity. Specifically, a dimensionless third-order model of relative humidity for PEMFC was established, which includes the dynamic of membrane water content. Based on the proposed model, an adaptive sliding mode convergence algorithm was designed to approach real-time humidity using measurable signals (voltage, current, pressure, flow rate, and temperature). The exploration of proposed adaptive sliding mode observer (ASMO) performance was compared with non-adaptive sliding mode observer (SMO) and classical ASMO by using a real 80 kW commercial fuel system experimental data. The experimental results show that compared with second-order humidity model, proposed third-order humidity model reduced recovery time under small step condition, where 250 s for cathode humidity estimation and 200 s for anode humidity estimation. In addition, under the small step condition, the average error of the three observers was less than 3%, which is accurate for engineering application. Moreover, proposed ASMO had the minimum static error, with 4% for cathode humidity estimation and 9% for anode humidity estimation under large step conditions as well as MAE, MSE, RMSE with 4%, 1.90%, 4.39% for cathode relative humidity estimation, 8.19%, 0.89%, 9.44% for anode relative humidity estimation respectively. The comprehensive results indicate that the proposed ASMO with adaptive parameters tuning has better dynamic performance than non-adaptive SMO as well as classical ASMO in terms of robustness and estimated accuracy.

Study on a Second-Order Adaptive Sliding-Mode Observer Control Algorithm for the Sensorless Permanent Magnet Synchronous Motor

The control of a permanent magnet synchronous motor (PMSM) without a position sensor based on a sliding-mode observer (SMO) algorithm has a serious jitter problem in the process of motor phase tracking. A second-order adaptive sliding-mode observer algorithm was proposed, and the ideas and principles of the second-order sliding-mode observer algorithm based on the super-twisting algorithm were elaborated. In particular, adaptive estimation with the introduction of back-electromotive force (EMF) was investigated, and the Lyapunov stability criterion was used to determine the convergence properties of the algorithm. The results showed that the second-order adaptive sliding-mode observer algorithm had better jitter suppression and a better phase tracking performance than the traditional sliding-mode observer algorithm. The experimental results showed that when the motor velocity was 800 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.57 r/min and the position error was 0.018 rad, with accuracy improvements of 93.63% and 58.34%, respectively. When the motor velocity was 1000 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.94 r/min and the position error was 0.022 rad, with accuracy improvements of 90.55% and 55.10%, respectively. The jitter of the system was suppressed well, the curve of back-EMF was smoother, and the robustness of the system was high. Therefore, the second-order adaptive sliding-mode observer algorithm is more suitable for the position-sensorless control of a PMSM.

SMO Based Position Sensorless BLDC Motor Drive Employing Canonical Switching Cell Converter for Light Electric Vehicle

In this paper, an adaptive sliding mode observer (ASMO) based rotor position sensorless brushless DC (BLDC) motor drive with energy regeneration for light electric vehicle (LEV) is designed. A canonical switching cell (CSC) converter is introduced for optimized MPPT performance and soft starting of the motor is assured during sensorless start-up. The CSC converter provides ripple free current in the output to the voltage source inverter (VSI) and minimizes the losses. It also acts as a fundamental building block for a DC-DC converter with the least element counts. For position sensorless commutation of BLDC motor drive, ASMO technique with self-correction ability of commutation error is used. Estimation of rotor angular position and continuous speed tracking for closed loop control are achieved using this method. This control is robust and derived from linear model of BLDC motor. Proper stability analysis of the observer is derived and ensured using pole placement method. Optimal gain scheduling technique is used in ASMO, which reduces the order of the error function making the computation easier. This model is truly adaptive to any parameter variation and load perturbation. To ensure green mobility, a pulse-width modulated regenerative braking algorithm is also integrated using the same VSI, which avoids any additional converter. Experimental results validate this method as effective for EV applications