Integral Backstepping Control Research Articles

A novel approach to the FPIBSC strategy for an electric power steering system

The electric power steering system is used to improve comfort and steering feel for the user. In this article, we propose to use an integrated nonlinear control strategy for the electric steering system, which is described based on a complicated dynamic model. This work provides two new contributions. First, this control algorithm combines backstepping and proportional–integral (PI) techniques with parameters adjusted by a fuzzy algorithm, so it is called Fuzzy proportional–integral backstepping control (FPIBSC). The output of the PI algorithm is the input of the backstepping technique, while system stability is evaluated based on the Lyapunov function with virtual control variables. Second, road reaction torque is calculated based on a spatial dynamic model, which considers the influence of many other factors. Numerical simulation methods are used to evaluate the performance of the system. According to research findings, the value of the steering motor angle (controlled object) continuously tracks the desired value with negligible error. Under some specific conditions, the error between signals can be reduced to zero. In addition, other outputs that are obtained from the FPIBSC algorithm also tend to follow the reference signal with high accuracy. The phase difference phenomenon only occurs when using the conventional backstepping algorithm instead of FPIBSC. The assisted torque increases as speed decreases or the driver torque increases. In general, the system’s stability is always guaranteed under many different simulation conditions.

Integral Backstepping Control of Two Compartment Microbial Fuel Cell

Integral Backstepping Control of Two Compartment Microbial Fuel Cell

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As the utilization of stratospheric airships becomes more prevalent, ensuring their safe operation becomes crucial. This paper explores the ability of an L1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {L}}_{1}$$\\end{document} adaptive controller to maintain fault tolerance in the actuators of a stratospheric airship. L1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {L}}_{1}$$\\end{document} adaptive control offers fast adaptation while separating adaptation and robustness. This makes the approach a suitable candidate for fault-tolerant control. The performance of the proposed design is compared to the Linear Quadratic Integral and Adaptive Sliding Mode Backstepping controllers. Simulation results show that the robustness of the airship model against faults is improved with the use of the L1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {L}}{}_{1}$$\\end{document} adaptive controller.

Design of integral backstepping controller - sliding mode along with admittance controller of knee joint robot in the presence of noise

Robots are increasingly being used in rehabilitation to assist patients with physical disabilities, particularly the knee joint. Physiotherapists often practice the patient’s leg around the knee joint to strengthen the muscles. However, Continuous Passive Motion (CPM) devices face challenges such as lack of feedback and resistance. This thesis aims to address these issues by using admittance and impedance concepts to control the robot’s flexible behavior against individual foot forces. The research uses a combination of backstepping and admittance algorithms, Model Reference Adaptive Control (MRAC), Sliding-Backstepping and Admittance Control to create a soft interactive patient-robot interaction. The device is designed for both left and right legs.

Trajectory-Tracking Control for Quadrotors Using an Adaptive Integral Terminal Sliding Mode under External Disturbances

In the face of external disturbances affecting the trajectory tracking of quadrotors, a control scheme targeted at accurate position and attitude trajectory tracking was designed. Initially, a quadrotor dynamic model, essential for control design, was derived. Adaptive integral backstepping control (AIBS) was then employed within the position loop, enabling the upper boundaries of disturbances to be estimated through adaptive estimation. Subsequently, a new adaptive backstepping fast nonsingular integral terminal sliding mode control (ABFNITSM) was proposed to enable adherence to the desired Euler angles. Rapid convergence and accurate tracking were facilitated by the incorporation of the nonsingular terminal sliding mode and an integral component. The dead zone technique was deployed to curtail estimation errors, while a saturation function was used to eradicate the phenomenon of chattering. Finally, to validate the proposed control scheme, simulation experiments were conducted in the Simulink environment, and the results were contrasted with those obtained from traditional integral terminal sliding mode control (ITSM) and integral backstepping control (IBS), providing evidence of the effectiveness of the proposed method.

Nonlinear control of two-stage single-phase standalone photovoltaic system.

This paper presents a single-phase Photovoltaic (PV) inverter with its superior and robust control in a standalone mode. Initially, modeling and layout of the Buck-Boost DC-DC converter by adopting a non-linear Robust Integral Back-stepping controller (RIBSC) is provided. The controller makes use of a reference voltage generated through the regression plane so that the operating point corresponding to the maximum power point (MPP) could be achieved through the converter under changing climatic conditions. The other main purpose of the Buck-Boost converter is to act like a transformer and produce an increased voltage at the inverter input whenever desired. By not using a transformer makes the circuit size more compact and cost-effective. The proposed RIBSC is applied to an H-bridge inverter with an LC filter to produce the sinusoidal wave in the presence of variations in the output to minimize the difference between the output voltage and the reference voltage. Lyapunov stability criterion has been used to verify the stability and finite-time convergence of the overall system. The overall system is simulated in MATLAB/Simulink to test the system performance with different loads, varying climatic conditions and inverter reference voltages. The proposed methodology is compared with a back-stepping controller and Proportional Integral Derivative (PID) controller under rapidly varying climatic conditions. Results demonstrated that the proposed technique yielded a tracking time of 0.01s, a total harmonic distortion of 9.71% and a root means square error of 0.3998 in the case of resistive load thus showing superior control performance compared to the state-of-the-art control techniques.

Adaptive terminal synergetic-backstepping technique based machine learning regression algorithm for MPPT control of PV systems under real climatic conditions

This paper deals with a comparative evaluation of nonlinear controllers based on the linear regression technique, which is a machine learning algorithm for maximum power point tracking. In the past decade, most photovoltaic systems have been equipped with classical algorithms such as perturb and observe, hill climbing, and incremental conductance. The simplicity of these techniques and their ease of implementation were seen as the main reasons for their utilization in photovoltaic systems. However, researchers’ attention has recently been attracted by artificial intelligence-based techniques such as linear regression, which offer better performance within the bounds of the nonlinearity of photovoltaic system characteristics. An adaptive terminal synergetic backstepping controller is developed in this paper for a single-ended primary inductance converter. This control scheme is based on the combination of a non-singular terminal synergetic technique with an integral backstepping technique and equally a neural network for the approximation of unmeasured or inaccessible variables that guarantees the finite-time convergence. The proposed controller was further verified under virtual and real environmental conditions, and the numerical results obtained from Matlab/Simulink software under various test conditions, including load variations, show that the adaptive terminal synergetic backstepping controller gives satisfactory performance compared to the adaptive integral backstepping controller used in the same climatic conditions.

Coordinated Control of Quadrotor Suspension Systems Based on Consistency Theory

This paper designs a cooperative control method for the multi-quadrotor suspension system based on consistency theory and realizes the cooperative formation trajectory tracking control of the multi-quadrotor suspension system by designing a consistent formation cooperative algorithm of virtual piloting and a nonlinear controller. First, a new quadrotor suspension system model is established based on the traditional quadrotor model using the Newton–Euler method. This model can accurately reflect the influence of the load on the quadrotor while obtaining the swing of the load. Then, the vertical and horizontal positions are designed separately based on the quadrotor motion characteristics, and the formation algorithm based on the virtual pilot consistency theory ensures that the final convergence of each position is consistent. An integral backstepping controller and an integral backstepping sliding mode controller are designed for quadrotor position, attitude, and load swing control to achieve accurate and fast quadrotor trajectory tracking control while reducing load swing. The stability of all the controllers is demonstrated using Lyapunov functions. Finally, a multi-quadrotor suspension system formation cooperative simulation experiment is designed to verify the designed control method.

Nonlinear position control of electro-hydraulic servo system based on lyapunov robust integral backstepping controller

In electro-hydraulic servo systems (EHSS), high nonlinearity and time-varying features limit the hydraulic actuator performance. In feedback-based systems, linearization reduces nonlinearities. Their cancellation may produce instability when modeling uncertainty exists. This work uses a robust nonlinear controller based on Lyapunov theory to control the nonlinear position of the electro-hydraulic servo system (EHSS). The dynamics of the system were modeled as extensively as possible, and then a simplified mathematical model based on the EHSS dynamics was created for the controller design. Integral backstepping was used to design the nonlinear robust controller utilizing the Lyapunov theory of nonlinear systems. Lyapunov functions theoretically ensured closed-loop stability. Comparative simulation analysis and experimental investigation in real-time with the proportional integral derivative (PID) controller optimized offline for position tracking control were carried out. Besides tracking performance and steady-state error, the mean square error (MSE), the root mean square error (RMSE), the maximum absolute value of tracking errors and the standard deviation of tracking errors (σ) was utilized to evaluate the controllers’ performance. The simulation analysis and experimental verification were accomplished under various sinusoidal trajectories using different testing conditions (amplitudes, frequencies, and external disturbance), in all testing conditions the effectiveness of the robust nonlinear integral backstepping controller was demonstrated.

Improved Robust Control of a New Morphing Quadrotor UAV Subject to Aerial Configuration Change

Over these last years, morphing Unmanned Aerial Vehicles (UAVs) control became one of the critical problems, which has not been properly solved by the researchers. This is due to their particular and complex features compared to the ordinary ones as: morphology change, flight transition, model asymmetry, geometric variation, different dynamics, over-actuation and high nonlinearity. To deal with such challenges, this paper addresses the control of a new over-actuated morphing drone that changes its arms in different orientations to form various morphology and configuration models. First, the present system is divided into two principal parts: an attitude subsystem and a position subsystem. Furthermore, an improved Adaptive Nonsingular Fast Terminal Sliding Mode Controller (ANFTSMC) is proposed to stabilize the attitude loop. While the position loop is controlled by Integral Backstepping Controller (IBC) using Lyapunov theory. Second, with the aim to better adjust the control gains, a recent metaheuristic technique based on the Whale Optimization Algorithm (WOA) is adopted. At last, a comparative study with the standard control algorithms is accomplished to evaluate the effectiveness and robustness of the proposed methods.

POSITION CONTROL OF ELECTRO-HYDRAULIC SERVO SYSTEM WITH FRICTION COMPENSATION

This work presents a model-based friction compensation technique and an integral adaptive backstepping controller to improve the position control of the electrohydraulic servo system. The controller design uses a continuous approximation of the LuGre friction model and the Lyapunov theory of nonlinear systems. The friction compensation enhances system performance, and comparison tests are conducted on a hydraulic servo test bench to validate the control strategy's tracking performance under various conditions. KEYWORDS: Electrohydraulic servo systems; Position control; Integral adaptive backstepping controller; LuGre dynamic friction model; Lyapunov theory; Friction compensation.

Robust integral backstepping control microgrid connected photovoltaic System with battery energy storage through multi-functional voltage source inverter using direct power control SVM strategies

This paper proposes a robust control based on the integral backstepping control (IBC) for power quality enhancement of micro-grid-connected photovoltaic (PV) system with battery energy storage systems (BESS), The DC side consists of a PV system and battery storage. As for the AC side, it consists of three phases of a multi-functional two-level voltage source inverter (MVSI) coupled to the electrical grid via an inductive filter, all feeding a non-linear load. The MVSI is controlled by a nonlinear direct power control (DPC) strategy with space vector modulation (SVM) and the proposed IBC technique. Using the proposed IBC technique to control the voltage of the DC link voltage loop, the active/reactive power loops of the grid, the compensation of the harmonic currents of the network, and the injection of the power of the PV battery into the grid, loop of the maximum power point tracking (MPPT) regardless of the random nature of weather changes and guarantees optimal power management system battery storage. Using simulation under the MATLAB environment, the proposed control system was validated and compared to the conventional strategies (proportional–integral controller and backstepping controller) in terms of success, performance, robustness, and efficiency. In addition to its ability to respond under any irradiation distortion and non-linear load unbalance.

Switched step integral backstepping control for nonlinear motion systems with application to a laboratory helicopter

In this paper, the energy efficiency of the widespread application of backstepping control to a class of nonlinear motion systems is investigated. A Switched Step Integral Backstepping Control (SSIBC) scheme is introduced to improve immunity to measurement noise and to increase the energy efficiency of conventional backstepping in practice. The SSIBC is realized by switching between two candidate controllers obtained at different steps of the iterative backstepping design process. A bi-state dependent hysteresis rule is developed to supervise stable switching between the different regimes in the presence of noise. The proposed method is experimentally verified on a MIMO twin rotor laboratory helicopter involving coupled nonlinear dynamics, inaccessible states and uncertainties. Experimental results show that in addition to a reduction in power consumption, the SSIBC reduces saturation of the control signal and visible motor jerking in contrast with conventional backstepping. Additional comparisons with a previously proposed optimized decoupling PID controller also show significant improvement in precision achieved with higher energy efficiency. Experimental results obtained with the introduction of an external disturbance into the system also show the robustness of the proposed SSIBC.

Integral back-stepping active disturbance rejection control for piezoelectric stick-slip drive nanopositioning stage

Piezoelectric stick-slip driven nanopositioning stage (PSSNS) with nanometer resolution has been widely used in the field of micro-operation. However, it is difficult to achieve nanopositioning over large travel, and its positioning accuracy is affected by the hysteresis characteristics of the piezoelectric elements, external uncertain disturbances, and other nonlinear factors. To overcome the above-mentioned problems, a composite control strategy combining stepping mode and scanning mode is proposed in this paper, and an integral back-stepping linear active disturbance rejection control (IB-LADRC) strategy is proposed in the scanning mode control phase. First, the transfer function model of the system in the micromotion part was established, and then the unmodeled part of the system and the external disturbance were treated as the total disturbance and extended to a new system state variable. Second, a linear extended state observer was used as the core of the active disturbance rejection technique to estimate displacement, velocity, and total disturbance in real time. In addition, by introducing virtual control variables, a new control law was designed to replace the original linear control law and improve the positioning accuracy and robustness of the system. Furthermore, the effectiveness of the IB-LADRC algorithm was verified by simulation comparison experiments and experimentally validated on a PSSNS. Finally, experimental results show that the IB-LADRC is a practical solution for a controller capable of handling disturbances during the positioning of a PSSNS with a positioning accuracy of less than 20 nm, which essentially remains constant under load.

Neuromorphic deep learning frequency regulation in stand-alone microgrids

Frequency instability has been a growing problem in recent years due to the rising penetration of distributed generating systems in the format of Microgrids (MGs), which are powered by renewable energy sources (RESs) with an unpredictable nature. The provision of an effective load frequency control (LFC) to an MG model under such conditions contributes significantly to the restoration regarding the unconfigured power system’s stability. An MG structure is employed, which combines renewable energy sources like solar and wind, as well as biologically renewable sustainable energy sources like wastewater, agricultural and domestic wastes, and contains appropriate battery systems and is suited to achieve both energy and waste control in this study. In addition, redox flow battery (RFB), an innovative battery storage system with a fast dynamic response in this MG structure, has been considered as one of the energy storage devices. A nonlinear integral backstepping (NIB) controller is adopted to stabilize the frequency deviation of the integrated MG system with RFB under various level of load disturbances and randomness of RESs. In particular, a spike neural network (SNN) based on neuromorphic platform is proposed to adjust the coefficients of NIB controller. Furthermore, real time analyses are performed with OPAL-RT to validate the feasibility of the proposed strategy from a systematical viewpoint. As a result of this study, the proposed controller for load disturbance, RES power changes, and contingency circumstances in bio renewable MG is determined to be flexible enough to satisfy the efficient frequency regulation for these grids.

Control of arc suppression devices for reducing powerline bushfires in resonant grounded power distribution networks using global terminal sliding mode controller

AbstractThis paper proposes a global terminal‐sliding mode controller (GT‐SMC) to compensate powerline bushfires due to electric faults in power distribution networks using arc suppression devices (ASDs). A GT‐sliding surface along with a new quick reaching law is used to design the controller. The major control objective is to compensate the fault current caused by single line‐to‐ground (SLG) faults to a value that cannot ignite fires in bushfire prone areas. A T‐type residual current compensator inverter within an ASD is controlled to achieve the goal. An integral‐sliding mode controller (I‐SMC) is also designed using a conventional reaching law for comparing the performance. Simulations studies and processor‐in‐loop implementations are carried out to investigate the ability of the GT‐SMC over an I‐SMC over a range of fault impedance scenarios. Dynamic properties of the voltage and current due to SLG faults along with the current injection by the ASD are analyzed against the standard criteria, to be followed to get rid of powerline bushfires. Results under different operating scenarios indicate that both controllers are capable to maintain standard criteria for preventing powerline bushfires though the GT‐SMC is proven to exhibit superior transient responses to that of the I‐SMC and integral backstepping controller.

Processor in the Loop Experimentation of an Integral Backstepping Control Strategy Based Torque Observer for Induction Motor Drive

Processor in the Loop Experimentation of an Integral Backstepping Control Strategy Based Torque Observer for Induction Motor Drive

RETRACTED: Integral backstepping control with RRFNN and MPSO of LPMSM drive system

RETRACTED: Integral backstepping control with RRFNN and MPSO of LPMSM drive system

A Direct Backstepping Super-Twisting Algorithm Controller MPPT for a Standalone Photovoltaic Storage System: Design and Real-Time Implementation

Abstract In this paper, we introduce a novel direct maximum power point tracking (MPPT) approach that combines the backstepping controller (BSC) and the super-twisting algorithm (STA). The direct backstepping super-twisting algorithm control (BSSTAC) MPPT was developed to extract the maximum power point (MPP) produced by a photovoltaic (PV) generator connected to the battery through a boost DC-DC converter. To reduce the number of sensors required for the BSSTAC implementation, a high gain observer (HGO) was proposed to estimate the value of the state of the PV storage system from measurements of the PV generator voltage and current. The suggested technique is based on the quadratic Lyapunov function and does not employ a standard MPPT algorithm. Results show that the suggested control scheme has good tracking performance with reduced overshoot, chattering, and settling time as compared to the prevalent MPPT tracking algorithms such as perturb and observe (P&O), conventional sliding mode control (CSMC), BSC, and integral backstepping controller (IBSC). Finally, real-time findings using the dSPACE DS 1104 software indicate that the generator PV can accurately forecast the MPP, as well as the efficacy of the suggested MPPT technique. The provided approach’s effectiveness has been validated by a comprehensive comparison with different methods, resulting in the greatest efficiency of 99.88% for BSSTAC.

An Integral-Backstepping Controller for Interleaved Boost Converter based on Photovoltaic Systems

Photovoltaic systems are one of the most widely used technologies for sustainable energy production due to their various advantages, such as being clean, free, and renewable energy sources. However, the power generated by the PV systems is strongly dependent on the atmospheric conditions. In addition, a suitable DC/DC converter must be used with a robust controller to facilitate system operation point changes associated with the changed climate conditions. In this paper, to deal with this challenge, a photovoltaic system based on four leg interleaved boost converter (FLIBC) has been proposed and studied. For robustness, the presented system is controlled using nonlinear integral backstepping control (IBSC) to track the maximum power point (MPP) and ensure an equal sharing current among the FLIBC legs. Moreover, the particle swarm optimization algorithm is used to find the optimum gains of the proposed IBSC. The entire system is simulated and validated using MATLAB/ Simulink environment. The simulation results demonstrate the efficiency of the proposed system based on the optimized IBSC (OIBSC) controller in terms of MPP tracking speed, overshoot and undershoot reduction, power ripple, and optimization of the performance term integral time square error (ITSE).