Sliding Mode Observer Research Articles

Sensorless Control of Surfaced-Mounted Permanent Magnet Synchronous Motor in a Wide-Speed Range

This paper delves into a comprehensive study of a wide-speed-range sensorless control approach for surface-mounted permanent magnet synchronous motors (SPMSMs). In the low-speed range, a novel high-frequency pulse voltage injection (HFPVI) method is introduced for rotor position estimation, which does not depend on motor saliency and is well-suited for SPMSMs. This method incorporates a second-order generalized integrator (SOGI) and a new modulation signal to enhance the accuracy of rotor position estimation. For medium-to-high speeds, an improved super-twisting sliding mode observer (STSMO) utilizing a continuous hyperbolic tangent function is proposed to mitigate chattering. Additionally, a new phase-locked loop (NPLL) is introduced to accurately obtain the rotor position. Furthermore, this paper designs an exponential weighted switching function to facilitate a smooth transition of the motor from the low-speed domain to the medium- and high-speed domains. The effectiveness and superiority of the proposed methods are validated through simulations and experiments conducted on an RTU-BOX platform. The rotor position estimation errors of the proposed new HFPVI method and the improved STSMO method under various operating conditions are both approximately 0.05 rad (2.8 elc·deg), and the SPMSM can switch smoothly from the low-speed range to the medium- and high-speed ranges.

Attack reconstruction‐based resilient consensus tracking for multi‐agent systems with distributed adaptive control protocol

AbstractThis article considers the distributed secure consensus tracking control problem for multi‐agent systems (MASs) with relative output information. To tackle the potential false‐data‐injection (FDI) attacks on both the communication between physical components and the control center at the agent level, as well as the message transmission between connected agents, local sliding mode observers (SMO) and distributed observers are proposed for each agent. By introducing reconstructed signals for attacks and smooth terms to compensate the unknown input in the leader agent's dynamics, a distributed adaptive consensus protocol with relative output information is proposed. The closed‐loop stability is analyzed by introducing a novel Lyapunov function. It is shown that all closed‐loop signals are globally uniformly bounded and asymptotically consensus tracking can be achieved. Simulation results are provided to validate the theoretical findings.

Robust asymptotic super twisting sliding mode observer for non-linear uncertain biochemical systems

The problem of state estimation (reconstruction of the state vector) for a given class of biochemical systems under uncertain system dynamics has been addressed in this paper. In detail, the bioreactor at a water resource recovery facility represents the considered biochemical systems. The biochemical processes taking place in the bioreactor have been modelled using an activated sludge model. Based on this model, an appropriate utility model has been derived for estimation purposes. The internal dynamics of the model have been burdened with unstructured and parametric uncertainty due to the unknown reaction kinetics functions. Taking this uncertainty into account, an analysis of the observability and detectability of the utility model has been carried out. The utility model and the available set of inputs and measured outputs have been used to design a new robust non-linear observer that allows the estimation of state variables in the presence of uncertainty. In the synthesis of the observer, the asymptotic observer methodology has been combined with a second-order sliding mode observer, a so-called super twisting algorithm. The developed observer generates not only robust and stable estimates of the state variables but also enables the reconstruction of unknown kinetic functions. The stability of the designed observer has been proven using the Lyapunov stability theory. The observer has been implemented in the Matlab/Simulink environment. The comprehensive simulation studies carried out show the high efficiency of the estimation process using the developed state observer.

Improved Finite Control Set Model Predictive Current Control for Permanent Magnet Synchronous Motor With Sliding Mode Observer

Improved Finite Control Set Model Predictive Current Control for Permanent Magnet Synchronous Motor With Sliding Mode Observer

Finite control set model-free predictive current control of permanent magnet synchronous motor

This thesis proposes finite control set model-free predictive current control (FCSMFPCC) algorithm of permanent magnet synchronous motor (PMSM). To address issue of degraded performance during motor operation due to parameter mismatch, a model-free predictive current control arithmetic is devised, which utilizes ultra-local model (ULM) of PMSM. This proposition takes sum of known and sealed disturbances of the system as an unknown quantity, and uses sliding mode observer (SMO) to take stock of sealed quantity. To address the issue of operation delay in predictive control, a two-step method is used to make up for the system. When using price function to choose the first-rank voltage vector, vector selection optimization link is added, which effectively simplifies the algorithm while optimizing the inverter switching action. The simulation outcomes highlight the advantages of the described control algorithm in terms of better dynamic response performance and stronger robustness.

Fixed-Time-Convergent Sliding Mode Control with Sliding Mode Observer for PMSM Speed Regulation.

This paper focuses on the speed control of a permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and external disturbances. Conventional sliding mode control (CSMC) can only converge asymptotically in the infinite domain and will cause unacceptable sliding mode chattering. To improve the performance of the PMSM speed loop in terms of response speed, tracking accuracy, and robustness, a hybrid control strategy for a fixed-time-convergent sliding mode controller (FSMC) with a fixed-time-convergent sliding mode observer (FSMO) is proposed for PMSM speed regulation using the fixed-time control theory. Firstly, the FSMC is proposed to improve the convergence speed and robustness of the speed loop, which can converge to the origin within a fixed time independent of the initial conditions. Then, the FSMO is used as a compensator to further enhance the robustness of the speed loop and attenuate sliding mode chattering. Finally, simulation and experimental results show that the proposed method can effectively improve the dynamic performance and robustness of the PMSM speed control system.

Improved model-free synergetic control of permanent magnet synchronous motor using unknown input observer

Parametric uncertainties and inverter nonlinearity exist in the permanent magnet synchronous motor (PMSM) drive system, which may lead to performance degradation or failure of model-based control. This paper presents an enhanced model-free synergetic control method for PMSMs, addressing the limitations of relying on accurate motor models in existing speed control strategies. The proposed approach aims to achieve robust control performance in the presence of parameter perturbations without the need for an accurate motor model. Firstly, a new ultra-local model of the speed loop for the PMSM is established based on a newly developed ultra-local theory. Subsequently, a model-free synergetic controller is designed using the principles of synergetic control theory. To address the issue of output chattering in the sliding mode observer used to estimate the unknown part of the ultra-local model, a synergetic observer method is proposed. Simulation results are presented and compared with those obtained using a proportional-integral (PI) controller and a conventional model-free sliding mode controller. The results demonstrate that the model-free synergetic controller exhibits robust performance and provides accurate estimation of the unknown part without output chattering.

A Rotor Position Detection Method for Permanent Magnet Synchronous Motors Based on Variable Gain Discrete Sliding Mode Observer

The purpose of this paper is to study the sensor-less rotor position estimation method for permanent magnet synchronous motors, and to achieve accurate estimation of rotor position in different conditions. Firstly, the traditional super-twisting observer algorithm is analyzed, and a new discrete variable gain sliding mode observer is designed to solve the buffeting problem in discrete systems, taking the reaction force as the disturbance signal. By estimating the back potential of the observer, the buffeting problem in the sliding mode algorithm can be effectively improved as shown by the simulation results. Then, to solve the problem of phase delay in rotor position estimation, an adaptive orthogonal phase-locked loop method is used to compensate the estimation error caused by the change in motor speed and increase the estimation accuracy of rotor position. The stability of the method can be proven by Lyapunov’s second method. Simulation experiments verify the accuracy of the proposed PMSM rotor position estimation 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.

Predefined-time position tracking optimization control with prescribed performance of the induction motor based on observers

To solve the position control problem of the induction motor with parameter perturbations, load disturbances, and modeling errors, a predefined-time position tracking optimization control method with prescribed performance is proposed. In practice, the rotor flux linkage of the induction motor can't be measured, and a predefined-time sliding mode observer (PTSMO) is applied to accurately estimate it. Additionally, predefined-time disturbance observers (PTDOs) are employed to identify the uncertainties in the motor system. The position and flux linkage controllers are then designed by integrating the predefined-time control approach with the prescribed performance function method, realizing accurate tracking control of the induction motor within a predefined time. Next, the adaptive genetic algorithm (AGA) and the improved particle swarm optimization (IPSO) technique are combined to optimize the designed controllers, enhancing the convergence rate and steady-state accuracy of the induction motor. Finally, comparative analyses through simulations and dSPACE simulated experiments validate the efficacy of the proposed control method, highlighting its applicability in practical motor systems.

Multi-Parameter Fuzzy-Based Neural Network Sensorless PMSM Iterative Learning Control Algorithm for Vibration Suppression of Ship Rim-Driven Thruster

Aiming to reduce motor speed estimation and torque vibration present in the permanent magnet synchronous motors (PMSMs) of rim-driven thrusters (RDTs), a position-sensorless control algorithm using an adaptive second-order sliding mode observer (SMO) based on the super-twisting algorithm (STA) is proposed. In which the sliding mode coefficients can be adaptively tuned. Similarly, an iterative learning control (ILC) algorithm is presented to enhance the robustness of the velocity adjustment loop. By continuously learning and adjusting the difference between the actual speed and given speed of RDT motor through ILC algorithm, online compensation for the q-axis given current of RDT motor is achieved, thereby suppressing periodic speed fluctuations during motor running. Fuzzy neural network (FNN) training can be used to optimize the STA-SMO and ILC parameters of RDT control system, while improving speed tracking accuracy. Finally, simulation and experimental verifications have been conducted on the vector control system based on the conventional PI-STA and modified ILC-STA. The results show that the modified algorithm can effectively suppress the estimated speed and torque ripple of RDT motor, which greatly improves the speed tracking accuracy.

Improved flux linkage observer for position estimation of permanent magnet synchronous linear motor

Abstract. With the development of motor technology, sensorless control attracts more and more attention. In this paper, an improved flux linkage observer is proposed to overcome issues including inaccurate initial positions and sampling noise. The voltage and current models are combined, and a sliding-mode observer is designed based on the hybrid model to obtain the compensation voltage. Therefore, the estimated flux linkage after compensation can greatly resist the influence caused by inaccurate initial positions or sampling noise. Phase-locked loop technology is used to process the estimated flux linkage to get the stable estimated speed and position. The proposed scheme has a simple structure and only one parameter. It is easy to use and adjust in practice. The simulation and experimental results verify that the proposed algorithm is effective, and the estimated flux linkage and position is accurate with an inaccurate initial position.

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 composite sliding mode control with the first-order differentiator and sliding mode observer for permanent magnet synchronous machine

This paper proposes a composite sliding mode control (SMC) to optimize the tracking performance and the anti-disturbance performance of permanent magnet synchronous machine (PMSM) speed regulation systems. The differential term in the control law can magnify the measurement noise, resulting in more discontinuity. To filter out the high frequency noise and make the control law smoother, the first-order differentiator (FOD) is employed to estimate the speed error and its derivative. Since the feedforward compensation can improve the robustness of the system, a disturbance observer (DOB) based on the sliding mode observer (SMO) is designed to reinforce the dynamic performance under disturbance variation. Under the effect of the feedforward compensation, chattering can be further weakened by decreasing the switching gain appropriately. Finally, the effectiveness of the proposed methods is confirmed by various experimental results.

Improved Compound Vibration Suppression Control for Magnetic Levitation Motor

The magnetic levitation motor is high efficiency, energy saving and environmental protection, which integrates magnetic levitation bearing and permanent magnet motor into the traditional motor. Two key technologies of its stable operation are vibration suppression control of magnetic bearing and speed sensorless chattering suppression control of motor. The innovative research has been studied from the perspective of control systems. First, in order to form the vibration suppression controller, the traditional proportional integral differential control has been improved by adding incomplete differential time constant. In addition, the method using linear variable structure sliding mode observer (SMO) is proposed to achieve speed identification, which can solve the chattering problem caused by the discontinuous high frequency switching signal compared to the traditional SMO. Finally, the experimental platform is built to verify the correctness of the proposed control methods. When the motor operates in speed sensorless mode, the rotor vibration is within the effective range. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Design of Lumped Disturbance Observer in Current Loop of IPMSM Based on Recursive Integral Sliding Mode Surface

To overcome the problem of current control effect being reduced by unideal factors in a motor control system, such as motor parameter variation, inverter dead time, nonlinearity of the system, etc., a sliding mode disturbance observer for an interior permanent magnet synchronous motor is proposed in this paper. The model of an interior permanent magnet synchronous motor with unideal factors is designed, and the unideal factors are unified into lumped disturbances of motor stator voltage. Then, the observer for lumped disturbance is designed. A recursive integral sliding surface is used to replace the terminal sliding surface to avoid the noise sensitivity and singularity problem of the traditional terminal sliding mode observer. The observer can estimate the lumped disturbance of the current loop without relying on the accurate system model in finite time. Moreover, the structure of the current loop does not need to be adjusted while using the observer to observe and compensate for disturbances. Experiments are carried out to verify the effectiveness of the proposed observer.

Nonlinear tyre model-based sliding mode observer for vehicle state estimation

Nonlinear tyre model-based sliding mode observer for vehicle state estimation

Real-Time Synchronisation of Multiple Fractional-Order Chaotic Systems: An Application Study in Secure Communication

In this paper, we use two Fractional-Order Chaotic Systems (FOCS)—one for the sender and one for the receiver—to determine the optimal synchronisation for a secure communication technique. With the help of the Step-By-Step Sliding-Mode Observer (SBS-SMO), this synchronisation is accomplished. An innovative optimisation method, known as the artificial Harris hawks optimisation (HHO), was employed to enhance the observer’s performance. This method eliminates the random parameter selection process and instead selects the optimal values for the observer. In a short amount of time, the secret message that could have been in the receiver portion (signal, voice, etc.) was successfully recovered using the proposed scheme. The experimental validation of the numerical results was carried out with the assistance of an Arduino microcontroller and several electronic components. In addition, the findings of the experiments were compared with the theoretical calculations, revealing a satisfactory level of agreement.

Disturbance rejection design for repetitive control system with state delay based on equivalent input disturbance compensation

A modified equivalent-input-disturbance compensation method is investigated for repetitive control systems with state time delays, which achieve effective rejection of unknown disturbance and effective tracking control of periodic reference input. By incorporating the sliding mode observer into the equivalent-input-disturbance theory, the equivalent-input-disturbance estimator structure is determined. The structure presented in this work can effectively estimate the unknown disturbance without making use of the inverse model of the system. Moreover, an asymptotic stability condition is devised to ensure that the repetitive control systems are stable, as well as the corresponding controller gains are designed with the aim to guarantee the performance of the system to suppress unknown disturbances. Numerical example simulations demonstrate the effectiveness and advantages of the devise 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.