Integral Sliding Mode Control Research Articles

An Attitude Adaptive Integral Sliding Mode Control Algorithm with Disturbance Observer for Microsatellites to Track High-Speed Moving Targets

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution, narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.03°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

Ammonia coverage ratio control of a novel two-cell SCR-DeNOX system configuration based on IA-ISMC

To respond the China’s “14th Five-Year Plan” on the control of nitrogen oxides (NOX) emission, urea-based selective catalytic reduction (SCR) system has been widely applied to reduce the NOX emission from the diesel engine. NO2 is no longer a factor to be ignored while refining the SCR-DeNOX system model because of the ship diesel engine's long-term low temperature and oxygen-rich condition, which provides abundant conditions for the creation of NO2. Therefore, a refined eight-state two-cell SCR-DeNOX model is established in this paper. Meanwhile, the trade-off between NOX emission and tailpipe ammonia (NH3) slip is one of the major challenges which SCR-DeNOX system is facing. While meeting NOX emission standards, the requirement of limiting NH3 slip to prevent secondary pollution is becoming increasingly urgent, which needs a better structure or controller. Therefore, a two-cell SCR-DeNOX system with a by-pass valve in front of the NH3 injection is designed, integral sliding mode control based on inversion algorithm (IA_ISMC) is proposed for each cell. Based on the FTP-75 test cycle, there are three points of view are presented. Firstly, compared with the traditional six-state model, simulation results from the refined eight-state SCR-DeNOX model are closer to the experimental data. Secondly, the introduction of the by-pass structure has a mild impact on the NOX conversion efficiency, but can largely limit the NH3 slip. Finally, the controller based on IA_ISMC effectively improves the tracking performance of NH3 coverage ratio and reduces the cost of NH3 injection. To sum up, the refined two-cell SCR-DeNOX system with a by-pass valve based on IA_ISMC can enhance SCR performance and lower costs.

Robust fixed-time flight controller for a dual-system convertible UAV in the cruise mode

This paper investigates the attitude tracking control problem for the cruise mode of a dual-system convertible unmanned aerial vehicle (UAV) in the presence of parameter uncertainties, unmodeled uncertainties and wind disturbances. First, a fixed-time disturbance observer (FXDO) based on the bi-limit homogeneity theory is designed to estimate the lumped disturbance of the convertible UAV model. Then, a fixed-time integral sliding mode control (FXISMC) is combined with the FXDO to achieve strong robustness and chattering reduction. Bi-limit homogeneity theory and Lyapunov theory are applied to provide detailed proof of the fixed-time stability. Finally, numerical simulation experimental results verify the robustness of the proposed algorithm to model parameter uncertainties and wind disturbances. In addition, the proposed algorithm is deployed in a open-source UAV autopilot and its effectiveness is further demonstrated by hardware-in-the-loop experimental results.

Integrated sensor FTC using integral sliding mode control

In this paper, a sliding mode sensor fault tolerant control scheme which involves a first order sliding mode observer, fault compensation logic and an integral sliding mode controller, is proposed for a class of uncertain linear parameter-varying systems. The proposed scheme has the capability to retain near nominal fault-free performance in the face of a class of sensor faults/failures. In particular, the closed-loop stability of the sensor fault tolerant scheme involving the sliding mode observer and the sliding mode controller in the presence of faults and uncertainty, is rigorously analysed. Furthermore, the paper proposes an algorithm to simultaneously synthesize the design freedom associated with the observer gains and control law despite the lack of a separation principle in the closed loop system overall caused by the uncertainty. The proposed scheme is validated using a commercial aircraft model. Good simulation results show the efficacy of the scheme.

Enhancing Regenerative Energy Capture in Electric Vehicle: Braking Performance through Integral Sliding Mode Control

Enhancing Regenerative Energy Capture in Electric Vehicle: Braking Performance through Integral Sliding Mode Control

Homotopic ADP based [formula omitted] integral sliding mode secure control for Markov jumping cyber-physical systems

This paper addresses the sliding mode secure control problem for continuous-time cyber-physical systems (CPSs) subject to unmatched disturbances and actuator deception attacks. To capture different operating conditions and account for random component failures in CPSs, a Markov jumping model is introduced to characterize the system's component matrices. Next, a novel model-free integral sliding mode function and a corresponding sliding mode controller are presented to mitigate the impact of external disturbances and deception attacks on Markov jumping cyber-physical systems. An algorithm based on adaptive dynamic programming (ADP) and homotopic policy iteration (PI) is applied to develop the sliding mode controller, called the online homotopic ADP algorithm, which avoids the requirement for an initial stabilizing matrix compared to existing PI algorithms. Lastly, the mode-independent integral sliding mode control scheme is studied to a two-mode Markov jumping vertical take-off and landing helicopter system, providing guaranteed reachability of sliding variables and stability of sliding mode dynamics. Importantly, this is achieved without any reliance on knowledge of system dynamics.

PSO-enhanced discrete-time integrated sliding mode-based control of three-level NPC converter for grid-connected PV-FC distributed generation system

This study proposes the control of a three-level NPC converter applied in a PV-FC hybrid generation system based on discrete-time integral sliding mode control (DISMC) combined with the particle swarm optimization (PSO) technique. First, the comprehensive depiction and modeling of the system's main components are initially presented. Then, the controller's detailed design procedure is given. The sliding manifold is designed to have a fast dynamic response, and its stability analysis is verified using the Lyapunov direct method. Next, the optimization procedure is introduced to calculate the optimal values of the DISMC gains. Furthermore, a power management strategy is examined within the proposed control system to maximize the utility of the power produced by the hybrid system; the control is done through the designed PSO-DISMC to allow decoupled control of the active and reactive powers in two distinct modes of operation (the feeder-flow control (FFC) and the unit-power control (UPC) modes). The simulation of the approach is conducted in MATLAB/Simulink, and the findings demonstrate the effectiveness and robustness of the proposed control strategy.

Intelligent robust control for aviation electric fuel pump based on second order integral sliding mode with UDE

This paper proposes an original intelligent robust control method for a kind of aviation electric fuel pump (AEFP) systems, in order to realize on-demand fuel supply for aircraft engines, accurately and robustly. By considering the feature of AEFP, the intelligent robust control method is in a cascaded structure, which combines a novel second order integral sliding mode control (SOISMC) approach with uncertainty and disturbance estimator (UDE) strategy, together with a new multi-objective variable speed grey wolf optimization algorithm (MOVSGWO). To let the current loop of AEFP possess both rapidity and robustness, the SOISMC is presented based on an innovative second order integral sliding mode manifold. To realize that AEFP has strong robustness to both the changing of speed command and the pulsation in fuel pump, UDE is utilized for the speed loop of AEFP. The primary parameters in the intelligent robust controller, namely, UDE-SOISMC controller, are optimized by MOVSGWO. The MOVSGWO is a modified grey wolf optimization algorithm with variable speed by particle swarm optimization. Mismatched uncertainties and disturbances in AEFP can be handled by the proposed robust method. The calculation of instantaneous flow and dynamic torque in AEFP is illustrated. Simulation and experimental results verify the effectiveness of the UDE-SOISMC method.

Improved Power Sharing Strategy for Parallel Connected Inverters in Standalone Micro-grid

The primary goal of integrating alternative energy systems such as solar and wind turbines into the power grid using power electronic devices is to meet the growing energy demands. Connecting inverters in parallel effectively enhance power capacity, reliability, and overall system efficiency. However, an uneven power distribution among the inverters is a significant limitation in these parallel connected inverters (PCI). This study focuses on a distributed generation (DG) unit comprising a solar photovoltaic system (SPV) and a battery energy storage system (BESS) connected to voltage source inverters (VSI) 1 and 2. The proposed approach aims to achieve uniform load/power distribution among the inverters with power management, maintaining a constant DC link voltage despite variations in solar irradiation and temperature. Additionally, the strategy targets the reduction of total harmonic distortion (THD) in the load current. The conventional droop control method is restricted in its ability to achieve accurate and uniform power distribution during load changes. An enhanced P-f and Q-E-based droop control technique (EDCT) and a fuzzy logic controller (FLC) have been proposed to address these challenges. Performance analysis using MATLAB/Simulink was conducted with two test cases, and a comparative assessment was carried out with a conventional controller, such as a Proportional Integral Controller (PIC) and Sliding Mode Controller (SMC), to showcase the effectiveness of the developed control technique. The proposed control method ensures equal sharing of active power of 2.5 and 4kW, 2.5 and 7.5kW and reactive powers of 2.5 and 4Vars, 2.5 and 7.5Vars among the inverters for the two cases even during the load change at t=0.5seconds. The settling time for DC link voltage and THD is effectively diminished to 0.03 and 0.25 seconds and 1.18% and 2.87% for the two test case studies of the proposed method, which are much lower than those of existing methods available in the literature.

Intelligent Solar PV Grid Connected and Standalone UPQC for EV Charging Station Load

The insertion of renewable energy sources into the grid, as well as the development of power electronics technology to regulate loads that are not linear, had an impact on power quality (PQ). This study focuses on the PQ enhancement of grid-connected and standalone solar PV systems (SPVS) with battery energy storage device (BESD) for the Electric vehicle (EV) charging station (EVCS) load in addition to the local load. Here, a hybrid control strategy that uses both the superior qualities of the sliding mode controller (SMC) and the fuzzy logic controller (FLC) is suggested for the unified power quality conditioner (UPQC's) shunt filter. It's major goal is to achieve steady DC capacitance voltage (SVDC) during load (like EVCS, non linear balanced/unbalanced etc.) and irradiation variations, diminish of total harmonic distortion (THD) in source current and load voltage, and mitigate sag, swell disturbances, and source voltage unbalances. The created model's performance is assessed using two scenarios (grid and island) under four case studies with varying combinations of loads and grid voltage circumstances. However, to establish the superiority of the proposed technology, comparative research with standard technologies such as proportional integral controller (PIC) and SMC controllers is required. THD is reduced by the proposed method to 2.25 %, 2.36 %, and 1.71 %, It is inferior to the current approaches found in the survey.

Performance enhancement of a three-phase grid-connected PV inverter system using fractional-order integral sliding mode controls

Grid-integrated photovoltaic (PV) systems hold significant promise for sustainable energy production. However, these systems often struggle with maintaining energy quality and stability in the face of fluctuating conditions. To address these challenges, this study proposes the use of fractional-order integral sliding mode control (FO-ISMC) for grid-connected PV systems. The system comprises solar panel arrays, a DC/DC boost converter with its controller, and a three-phase inverter integrated into the utility grid. The primary goals of this study are to maximize power extraction from the PV system and to regulate system currents, thereby improving effectiveness and power quality. The proposed method is further refined using the particle swarm optimization (PSO) algorithm to fine-tune parameter settings. By optimizing the command gains of the FOI-SMC, the PSO algorithm enhances system performance and stability. Leveraging fractional-order and integral terms provides the control signal with additional degrees of freedom, enhancing system performance in the presence of internal and external disturbances. Simulation results demonstrate the effectiveness of the proposed controller compared to the classical controller, where in the case of Irradiation taking the value of 500 W/m2, the proposed strategy reduced the values of constant voltage, active power, and reactive power by percentages estimated at 88.18%, 90%, and 70%, respectively, compared to the traditional strategy. Also, the overshoot value of active power was reduced in all completed cases compared to the traditional strategy by percentages estimated at 53.57%, 66.66%, and 65%, respectively. The proposed strategy reduced the response time of reactive power in all cases compared to the traditional strategy by percentages estimated at 58.59%, 28.80%, and 75%, respectively. These ratios show the high performance of the proposed control in improving the characteristics of the studied system compared to traditional control based on PI control.

Barrier Function-Based Integral Sliding Mode Controller Design for a Single-Link Rotary Flexible Joint Robot

Abstract This paper proposes and evaluates a novel control approach for trajectory tracking, stability enhancement, and vibration reduction of a flexible joint robot (FJR). The FJR is a 2-degree-of-freedom underactuated nonlinear system that is challenging to control due to vibration, underactuation, uncertainties, and external disturbances. The control objectives are high trajectory tracking performance together with suppressing vibration. The proposed control approach uses integral sliding mode control (ISMC) combined with a barrier function based on back-stepping. This ensures robust and smooth performance by eliminating the reaching phase where sliding mode control (SMC) is typically not robust. Robustness is thus guaranteed from the start. The FJR is modeled as a 4th-order system using Lagrangian mechanics and decomposed into two 2nd-order subsystems for control design. Sliding variables are defined for each subsystem. Using these variables, the proposed control achieves robust trajectory tracking, stability, and vibration reduction. Numerical simulations in MATLAB validate the superior performance of the proposed ISMC-barrier function control compared to conventional ISMC for the FJR. This novel control approach addresses the challenges of controlling this FJR.

Robust interval predictive tracking control for constrained and perturbed unicycle mobile robots

AbstractIn this paper, we propose the design of a robust control strategy for the trajectory tracking problem in perturbed unicycle mobile robots. The proposed strategy comprises the design of a robust control law, which is based on an Integral Sliding‐Mode Control (ISMC) approach together with an interval predictor‐based state‐feedback controller through a Model Predictive Control (MPC) scheme. The robust controller deals with some perturbations in the kinematic model, which represent slipping effects, and with state and input constraints that are related to restrictions on the workspace and saturated actuators, respectively. The proposed approach guarantees the exponential convergence to zero of the tracking error. The performance of the proposed approach is validated through some simulations tracking a lemniscate and a circumference curve.

Adaptive Sliding Mode Resilient Control of Multi-Robot Systems with a Leader–Follower Model under Byzantine Attacks in the Context of the Industrial Internet of Things

In this paper, an adaptive and resilient consensus control mechanism for multi-robot systems under Byzantine attack, based on sliding mode control, is proposed. The primary aim of the article is to develop a finite-time consensus control strategy even in the presence of a Byzantine attack. In the start, a finite-time consensus control mechanism is proposed to identify the essential conditions required for ensuring consensus accuracy in multi-robot systems, even when faced with Byzantine attacks using Lyapunov theory. Subsequently, a sliding mode control is combined with an adaptive technique for multi-robot systems that lack prior knowledge of Byzantine attack. Later, an attack observer is proposed to estimate the performance of multi-robot systems in the presence of a Byzantine attack. Additionally, chattering effects are mitigated by employing integral sliding mode control. As a result, resilient consensus performance of multi-robot systems can be achieved in a finite time interval. A simulation example is also presented to validate the effectiveness of the proposed model. Furthermore, we delve into the data structure of the proposed method and explore its integration with Artificial Intelligence for seamless incorporation into the Industrial Internet of Things applications.

Adaptive integral sliding-mode finite-time control with integrated extended state observer for uncertain nonlinear systems

For the typical uncertain nonlinear systems subjected to controller gain variation and disturbances, an integrated adaptive robust controller, called integral sliding-mode finite-time controller with an integrated extended state observer (ISFC-IESO), is proposed. The designed controller mainly consists of an integrated ESO (IESO) unit and an integral sliding-mode control (ISMC) unit. The IESO unit is composed of improved linear and nonlinear ESOs which are designed to automatically switch each other, with the aim of enhancing disturbance estimation capability. Moreover, the ISMC unit produces an integral sliding-mode control law (SMCL) based on the newly designed integral sliding-mode surface function (SMSF) and sliding-mode reaching law (SMRL). The integral SMSF is developed based on the n-th estimated state and a designed convergence function of tracking error to suppress the influence of the disturbance estimation error. On this basis, SMRL is further presented by combining integral SMSF with a specially designed variable boundary layer thickness saturation function, for the purpose of eliminating chattering and enhancing robustness. Finally, fourteen control methods are compared to illustrate the effectiveness and superiority of the proposed ISFC-IESO.

Fuzzy Super-Twisting Sliding Mode Controller for Switched Reluctance Wind Power Generator in Low-Voltage DC Microgrid Applications

There is limited research focused on achieving optimal torque control performance of Switched Reluctance Generators (SRGs). The majority of existing studies tend to favor voltage or power control strategies. However, a significant drawback of SRGs is their susceptibility to high torque ripple. In power generation systems, torque ripple implicates fluctuations in the generated power of the generator. Moreover, high torque ripple can lead to mechanical vibrations and noise in the powertrain, impacting the overall system performance. In this paper, a Torque Sharing Function (TSF) with Indirect Instantaneous Torque Control (IITC) for SRG applied to Wind Energy Conversion Systems (WECS) is proposed to minimize torque ripple. The proposed method adjusts the shared reference torque function between the phases based on instantaneous torque, rather than the existing TSF methods formulated with a mathematical expression. Additionally, this paper introduces an innovative speed control scheme for SRG drive using a Fuzzy Super-Twisting Sliding Mode Command (FSTSMC) method. Notably robust against parameter uncertainties and payload disturbances, the proposed scheme ensures finite-time convergence even in the presence of external disturbances, while effectively reducing chattering. To assess the effectiveness of the proposed methods, comprehensive comparisons are made with traditional control techniques, including Proportional–Integral (PI), Integral Sliding Mode Control (ISMC), and Super-Twisting Sliding Mode Control (STSMC). The simulation results, obtained using MATLAB®/SIMULINK® under various speeds and mechanical torque conditions, demonstrate the superior performance and robustness of the proposed approaches. This study presents a thorough experimental analysis of a 250 W four-phase 8/6 SRG. The generator was connected to a DC resistive load, and the analysis focuses on assessing its performance and operational characteristics across different rotational speeds. The primary objective is to validate and confirm the efficacy of the SRG under varying conditions.

A novel cascaded trajectory tracking control for UUVs under time-varying disturbances

In this paper, a novel cascaded trajectory tracking control strategy based on the characteristics of kinematics and dynamics is proposed for unmanned underwater vehicles (UUVs) under complex disturbances. A kinematic controller based on an improved model predictive control (MPC) is designed to solve the speed jump problem by considering system constraints. Moreover, an improved whale optimizer with elite strategy (EIWOA) is used to the rolling optimization process of MPC, ensuring that the global best solution is derived by obtaining the elite individuals in the population. Besides, a dynamic controller that consists of an adaptive disturbance observer and a fuzzy integral sliding mode control (ADO-FISMC) is proposed to obtain optimal thrust force under time-varying disturbances. The benefit of ADO lies in that it can estimate time-varying disturbances without specific information about disturbances. The fuzzy logic system is introduced to alleviate the chattering of sliding mode control. The simulation results demonstrate the great tracking performance of the cascaded trajectory tracking controller. The viability of the proposed algorithm is also confirmed by trials conducted in water pools.

A finite-time path-tracking control algorithm for nonholonomic mobile robots with unknown dynamics and subject to wheel slippage/skid disturbances

Path planning and tracking control are two performance-critical tasks for wheeled mobile robots, particularly when nonholonomic constraints are imposed on robots in dynamically uncertain conditions. Accomplishing certain performance and safety considerations related to path-tracking, such as global stability, transient performance, and smooth finite-time convergence, becomes more difficult for nonholonomic robots. This paper is concerned with proposing a new adaptive robust finite-time tracking control approach for a large class of differential drive autonomous nonholonomic wheeled mobile robots (NWMRs) that are subject to structured uncertainties and extraneous disturbances with fully unknown dynamics. For this purpose, nonlinear kinodynamics of a type of rear-wheel drive NWMRs are developed by incorporating the skid/slippage constituents of the wheel motion. Then, a path-tracking controller is proposed using a continuous finite-time adaptive integral sliding mode control coupled with an integral backstepping approach (FTAISM-IBC). For the adaptive controller design, the entire nonlinear dynamics of the robot, including nonlinear vector functions and control gain functions, together with extraneous disturbances, are estimated by leveraging the universal approximation capabilities of radial basis neural networks (RBFNNs). The finite-time stability proof is presented by utilizing the Lyapunov stability theorem. Furthermore, the adaptive gains are derived to ensure the finite-time stability of the system subject to unknown functions, parametric variations, and unknown but bounded disturbances. Finally, the effectiveness of the proposed controller is evaluated through simulations in terms of several key performance indicators against several reported studies.

Fixed‐time sliding mode trajectory tracking control for marine surface vessels under mismatched conditions and input saturation

SummaryThis paper addresses a trajectory tracking control problem for marine surface vessels (MSVs) in the presence of mismatched conditions and input saturation. Firstly, an MSV model under mismatched conditions is established to solve the problem of unreasonable modeling methods in the existing literature. Secondly, fixed‐time disturbance observers (FXDOs) are designed, where the designed FXDOs not only avoid selecting complicated parameters but also has simple structures, and the disturbance estimation errors can converge to the origin within a setting time. Thirdly, based on the FXDOs and an anti–saturation auxiliary dynamic system, a trajectory tracking control scheme in the presence of mismatched conditions and input saturation is constructed by virtue of fixed‐time integral sliding mode control (SMC), and the actual tracking error signals are uniformly fixed‐time bounded rather than finite‐time one. Fourthly, in order to decrease theoretical calculation values of the original setting time in fixed‐time control, the new setting time under three different parameter conditions is derived, and thus reducing the conservatism. Finally, the simulation results are provided to show the effectiveness and superiority of the designed tracking control scheme.

RBFNN-Based Adaptive Integral Sliding Mode Feedback and Feedforward Control for a Lower Limb Exoskeleton Robot

In this paper, an adaptive trajectory tracking control method combining proportional–integral–derivative (PID) control, Radial Basis Function neural network (RBFNN)-based integral sliding mode control (ISMC), and feedforward control, i.e., the PIDFF-ISMC method, is proposed. The PIDFF-ISMC method aims to deal with the dynamic uncertainties, disturbances, and slow response in lower limb exoskeleton robot systems. Firstly, the Lagrange function is utilized to establish dynamic models that include frictional force and unmodeled dynamics. Secondly, the feedback controller is composed of PID and RBFNN-based ISMC to improve tracking performance and decrease the chattering phenomenon. The feedforward controller is adopted to reduce the response time by employing inverse dynamic models. Finally, the Lyapunov function proves the stability of the proposed control method. The experimental results show that the proposed control method can effectively reduce the trajectory tracking error and response time at two different speeds while alleviating control input chattering.