Predictive Sliding Mode Control Research Articles

Collision-free trajectory tracking strategy of a UUV via finite-time extended state observer-based sliding mode predictive control

This paper focuses on a trajectory tracking problem for unmanned underwater vehicles (UUVs) subject to current disturbances and static obstacles. A double-loop framework is established. The kinematic governor employs model predictive control(MPC), which takes into account the UUV’s kinematic characteristics as well as the conditions for obstacle avoidance when calculating the control command and provides an optimal velocity command input for the dynamic controller. Then, the dynamic controller is developed based on a fast finite-time extended state observer (FESO) and a fast adaptive integral terminal sliding mode controller (FAITSMC). The construction of the fast FESO integrates UUV’s dynamics model, a proportional integral velocity variable, and a fractional order term of the output observation error, which can identify model uncertainties and external disturbances in finite time. By means of adaptive uncertainty compensation, the FAITSMC enables the error between actual speed and speed reference to converge to a minimum quickly. By applying Lyapunov stability theory and the finite-time analysis technique, sufficiency criteria are established to guide and keep the UUV on a reference trajectory via an inner-outer loop control structure. Finally, simulation examples in different scenarios are presented to verify the feasibility and effectiveness of the derived theoretical results.

Fast Terminal Sliding-Mode Predictive Speed Controller for Permanent-Magnet Synchronous Motor Drive Systems

This paper proposes a kind of discrete-time sliding-mode predictive control (SMPC) based on a nonlinear sliding function for permanent-magnet synchronous motors’ (PMSMs’) speed control to improve the convergence performance. Compared with traditional sliding-mode predictive control based on a linear sliding function, the proposed SMPC has a faster convergence rate thanks to the design of a nonlinear fast terminal sliding function. Moreover, one-step prediction is employed, which greatly simplifies the algorithm and improves the real-time performance of its operation. The sliding state will follow the expected trajectory of a predefined sliding-mode reaching law. The stability and convergence performance of the proposed method is analyzed. The results of the theoretical analysis, simulations, and experiments indicate that the proposed method has excellent convergence performance and robustness.

Correction to: Model Predictive Sliding Mode Control of Highway Traffic Flow: Cooperative and Integrated Approach

Correction to: Model Predictive Sliding Mode Control of Highway Traffic Flow: Cooperative and Integrated Approach

Predictor-based constrained fixed-time sliding mode control of multi-UAV formation flight

In this work, a predictor-based fixed-time sliding mode control is designed to tackle the problem of achieving precise trajectory tracking control of multiple unmanned aerial vehicle formation flight. The proposed approach simultaneously addresses various practical requirements, such as optimality, constraints, fixed-time convergence, external interferences, and computational burden. Initially, using the Taylor series concept, we derive the predictive models for the fixed-time sliding surface and reaching law. Subsequently, we formulate a constrained performance index by integrating these predictions with the control input. Ultimately, the optimal control input is computed through solving the constrained quadratic optimization problem. An outstanding feature of this study is the theoretical guarantee of closed-loop fixed-time system stability in the presence of external disturbances and constraints. Furthermore, the comparative analysis with sliding mode predictive control law and fixed-time sliding mode control methods demonstrates that the proposed approach achieves a straightforward control method with improved performance and acceptable accuracy. Finally, an experimental test is conducted to demonstrate the algorithm's potential for hardware implementation by employing the Hardware-in-the-Loop test.

Predictive trajectory tracking control for the USV in networked environments with communication constraints

The trajectory tracking control problem of under-actuated unmanned surface vessels (USVs) suffering from communication constraints (network delay, packet loss, packet disorder) as well as external environment disturbance is investigated in this paper. To solve the aforementioned trajectory control problem, a nonlinear networked predictive control strategy based on the discrete sliding mode framework is proposed. Initially, using the forward Euler discretization method, a novel discrete virtual velocity control law is designed to transform trajectory tracking control into virtual velocity tracking control. Then, a sliding mode controller is suggested to suppress external disturbance of the USV. In addition, a networked sliding mode predictive control (NSMPC) scheme is proffered to guarantee active compensation of the communication constraints and stability of the trajectory tracking system simultaneously. Afterward, a theoretical analysis is given to show that the closed-loop system is uniformly bounded stable after the introduction of the digital network. Finally, extensive comparative simulation examples are provided to demonstrate the effectiveness of the proposed control strategy.

Predefined-Time Sliding Mode Predictive Current Control for Disturbance Suppression and Dynamic Response Improvement in SPMSM Drives

Predefined-Time Sliding Mode Predictive Current Control for Disturbance Suppression and Dynamic Response Improvement in SPMSM Drives

Jointed Observer-Based Sliding Mode Predictive Control for Interconnected Power Systems With Input Delays

Jointed Observer-Based Sliding Mode Predictive Control for Interconnected Power Systems With Input Delays

Double-layer Fast Terminal Sliding Mode Predictive Control for PMSM Speed Regulation

Double-layer Fast Terminal Sliding Mode Predictive Control for PMSM Speed Regulation

Disturbance-Compensation-Based Predictive Sliding Mode Control for Aero-Engine Networked Systems With Multiple Uncertainties

Disturbance-Compensation-Based Predictive Sliding Mode Control for Aero-Engine Networked Systems With Multiple Uncertainties

Novel reaching law based predictive sliding mode control for lateral motion control of in‐wheel motor drive electric vehicle with delay estimation

AbstractThe lateral motion control of an in‐wheel motor drive electric vehicle (IWMD‐EV) necessitates an accurate measurement of the vehicle states. However, these measured states are always affected by delays due to sensor measurements, communication latencies, and computation time, which results in the degradation of the controller performance. Motivated by this issue, a novel reaching law based predictive sliding mode control (NRL‐PSMC) is proposed to maintain the lateral motion control of the IWMD‐EV subjected to unknown time delay. Initially, a PSMC framework is built, in which a predictor integrating with the sliding mode control is designed to eliminate the effect of time delay and generate the virtual control signals. Further, to alleviate the chattering phenomenon, a novel‐reaching law is developed, enabling the vehicle to track the desired states effectively. Subsequently, a dynamic control allocation technique is presented to optimally allocate the virtual control input to the actual control input. The accurate estimation of the aforementioned unknown delay is realized through a delay estimator. Finally, simulation and hardware‐in‐the‐loop experiments are performed for three specific driving manoeuvres, and the results demonstrate the effectiveness of the proposed controller design.

Model-free distributed integral sliding mode predictive control for multi-agent systems with communication delay

This paper explores the problem of distributed cooperative tracking control for networked nonlinear multi-agent systems (MASs) with communication delays. The difficulty of distributed control of subsystems across several geographic areas is addressed by utilizing MASs in this study. To overcome modeling difficulties, a model-free control algorithm is employed. To handle networked delay, a network predictive control approach is utilized. To address these issues in a unified manner, a novel distributed model-free integral sliding mode predictive control strategy is proposed. This approach requires simple data to make predictions to achieve distributed tracking performance while also actively compensating for delays. The effectiveness of the proposed method is demonstrated through simulations and experimental results.

Extended Kalman Filter design for sensorless sliding mode predictive control of induction motors without weighting factor: An experimental investigation.

Due to their simplicity, cheapness, and ease of maintenance, induction motors (IMs) are the most widely used motors in the industry. However, if they are not properly controlled, the load torque and motor speed will fluctuate in an unsatisfactory fashion. To effectively control the load torque and speed of these IMs, it is necessary to use specialized drives. The entire system (IMs + Drives) will experience uncertainty, nonlinearities, and disruptions, which calls for an outstanding performance control structure. The sensorless sliding mode predictive torque control (SSM-PTC) for both AC-DC converter and DC-AC inverter, which are utilized for feeding the IM, is investigated in this work. The AC-DC converter is controlled using the SSM-PTC method in order to follow the DC-link reference voltage throughout any changes in the operating point of the IM. While the DC-AC inverter is controlled using a sensorless predictive power control (SPPC). Within a unity power factor, this SPPC regulates the reactive power flow between the motor and the supply to account for the undesirable harmonic components of the grid current. In addition, an experimental performance improvement of SSM-PTC of IM supplied by a 5-leg AC-DC-AC power converter using extended Kalman filter (EKF) without weighting factor (WF) is also studied in this work. Design and implantation of the suggested control systems are performed using a dSPACE 1104 card. The experimental results of the proposed converter control demonstrate that the suggested approach effectively regulated the DC link, reducing load torque and speed fluctuations. In the context of inverter control, a prompt active power response yields a motor current waveform that resembles a sinusoidal pattern, exhibiting minimal levels of harmonic distortion.

Disturbance-observer-based discrete-time sliding mode predictive control for overhead cranes with matched and unmatched disturbances

In actual working environments, underactuated overhead cranes are susceptible to the adverse effects of the mechanical friction, uncertain parameters, and other disturbances. In particular, if the payload is disturbed (i.e. the unmatched disturbance), unpredictable swings would occur. Therefore, a discrete time sliding mode predictive control for overhead cranes based on a disturbance observer is proposed. Specifically, to eliminate uncertain disturbances, we propose a disturbance observer to estimate and compensate the disturbance to the input channel. Then, a new discrete sliding mode control law is obtained by adding the disturbance error estimator to the discrete sliding mode surface. In order to reduce the chattering inherent in the sliding mode, we integrate the discrete sliding mode law into the model predictive control, and use the rolling optimization and feedback correction of the predictive control, and finally output the optimal control law to act on the system. This control method can not only further improve the control accuracy, but also has sufficient robustness. Simulation and robustness experiments under various conditions verify the effectiveness of the proposed controller.

Design and analysis of event‐triggered predictive sliding mode control for discrete‐time constrained system

AbstractThis paper presents a new approach for designing an event‐triggered predictive sliding mode control (SMC) for discrete‐time systems subject to constraints. The proposed controller is based on an existing reach‐law‐based SMC, and it formulates an optimization control problem (OCP) to generate predictive control actions that satisfy both state and input constraints. An event‐triggered strategy is introduced to reduce the frequency of OCP solving by taking into account the sliding mode controller and unmeasurable states between sampling instants. The paper also analyzes the recursive feasibility of the proposed controller, which ensures the feasibility of each OCP solution. Numerical simulations and comparison studies are performed to validate the theoretical results. The proposed approach offers an effective way to design event‐triggered predictive sliding mode controllers that reduce the computational burden of OCP solving while guaranteeing the satisfaction of system constraints.

A nonsingular fast terminal sliding mode predictive controller for underwater soft crawling robots with parameter uncertainty

Unknown disturbances and material properties affect the trajectory tracking of underwater soft clawing robots. A nonsingular fast terminal sliding mode predictive controller is proposed to eliminate these effects. To characterize hysteresis and creep in dielectric elastomer materials, a dynamic model incorporating an improved dead-zone operator algorithm is constructed. Meanwhile, a nonsingular fast terminal sliding mode predictive controller that combines the Lie derivative function and sliding mode controller surface is developed to improve the accuracy and robustness of trajectory tracking. Additionally, the dynamic response and convergence speed of the proposed control system are improved by using an adaptive nonlinear disturbance observer to estimate the disturbance and uncertainty terms. Finally, the superiority and effectiveness of the proposed control method are verified by numerical simulations and experiments.

A multivariable sliding mode predictive control method for the air management system of automotive fuel cells

The proton exchange membrane fuel cell gas control has been one key point in fuel cell management systems. The complexity and coupling of the air management system make it difficult to achieve precise air intake adjustment. In this paper, an accurate joint control method for the air flow and pressure regulation is proposed. The nonlinear mathematical model of the air management system is developed to describe the output characteristic and state change. Based on this, the feedback linearization method is proposed to obtain the direct correspondence between control variables and controlled variables. In addition, to solve the problem that the controlled variables cannot be measured directly, an extended state observer is applied to estimate the stack cathode pressure. The sliding mode predictive control method is proposed to control the oxygen excess ratio and cathode pressure simultaneously. The relative order of the system is used to design the sliding mode surface, and the corresponding predictive model is proposed. The results obtained by simulation experiments show that pressure and mass flow have little effect on each other through decoupling. The proposed algorithm has been verified to have high precision, fast response, and robustness through comparative experiments.

Design of Sliding Mode Controller Based on 7 nm Gate Logic

In this paper, a new discrete-time sliding mode predictive control (DSMPC) strategy with a PID sliding function is proposed for synchronous DC–DC Buck converter. The model predictive control, along with digital sliding mode control (DSMC) is able to further reducing the chattering phenomenon, steady-state error, overshoot, and undershoot of the converter output voltage. The proposed control method implementation only requires output error voltage evaluation. The effectiveness of the proposed DSMPC is proved through simulation results executed by the MATLAB/SIMULINK software. These results demonstrate its performance is superior to DSMC. The selected synchronous Buck converter in this paper has 380 V input voltage and 48 V output voltage that can be applied in sections of DC distribution systems.

Observer-Based Discrete-Time Cascaded Control for Lateral Stabilization of Steer-by-Wire Vehicles With Uncertainties and Disturbances

This article proposes an observer-based discrete-time cascaded control (ODCC) strategy for lateral stabilization of Steer-by-Wire (SbW) vehicles with consideration of uncertainties and disturbances. First, for the observation of the sideslip angle and yaw rate, an information fusion-based unscented Kalman filter (IFUKF) is designed to reduce the negative effect from the variation of the parameters; Second, aiming to eliminate the errors of control variables for lateral stabilization of SbW vehicles, a discrete-time sliding mode predictive control (DSMPC) is presented to deal with matched and mismatched uncertainties and input constraint; Third, to reduce the tracking error between the actual front wheel steering angle and the desired one generated by the DSMPC, a combination of discrete-time fast terminal sliding mode and active disturbance rejection control is proposed to tackle the problems of parameter uncertainties and disturbances in the SbW system. Performance evaluations are conducted via both software-in-the-loop and hardware-in-the-loop to examine the availability and practicability of the ODCC strategy.

A Discrete-time Integral Sliding Mode Predictive Control Using Iterative Dynamic Linearization Data Model

A Discrete-time Integral Sliding Mode Predictive Control Using Iterative Dynamic Linearization Data Model

Fault-tolerant model predictive sliding mode control with fixed-time attitude stabilization and vibration suppression of flexible spacecraft

This brief proposes two novel double-loop fault-tolerant controllers to tackle the problems of stabilizing the attitude and nullifying appendages' vibration of flexible spacecraft by integrating the advantages of model predictive control (MPC) and sliding mode control (SMC). The structure of the first method is as follows: First in the external loop, by using terminal sliding mode (TSM), the attitude of the spacecraft is derived to its reference value, and the proper angular velocity of the interior part is generated. Then, by employing the preciseness and constrained attributes of MPC, an optimal fault-tolerant controller is suggested in the internal part. Constrained fault-tolerant MPC tracks the angular velocity to the set value while guaranteeing appendages' passive vibration suppression. In another method, as opposed to the first technique, in the inner loop fault-tolerant finite-time TSM, and in the outer loop MPC are designed. The unified double-layer nonlinear controller schemes guarantee good dynamics and robustness against external torques and actuator faults. The closed-loop system's stability of the controllers is precisely proved using the Lyapunov theorem in the presence of actuator faults and external disturbances and in the absence of the damping matrix to study the advantages of the proposed methods. The performance of the proposed methods has been compared with each other. Moreover, the simulation results substantiate that the proposed method outperforms faster fixed-time sliding model control significantly.