SMC Controller Research Articles

Design and Experimental Validation of an Adaptive Multi-Layer Neural Network Observer-Based Fast Terminal Sliding Mode Control for Quadrotor System

This study considers the numerical design and practical implementation of a new multi-layer neural network observer-based control design technique for unmanned aerial vehicles systems. Initially, an adaptive multi-layer neural network-based Luenberger observer is designed for state estimation by employing a modified back-propagation algorithm. The proposed observer’s adaptive nature aids in mitigating the impact of noise, disturbance, and parameter variations, which are usually not considered by conventional observers. Based on the observed states, a nonlinear dynamic inversion-based fast terminal sliding mode controller is designed to attain the desired attitude and position tracking control. This is done by employing a two-loop control structure. Numerical simulations are conducted to demonstrate the effectiveness of the proposed scheme in the presence of disturbance, parameter uncertainty, and noise. The numerical results are compared with current approaches, demonstrating the superiority of the proposed method. In order to assess the practical effectiveness of the proposed method, hardware-in-loop simulations are conducted by utilizing a Pixhawk 6X flight controller that interfaces with the mission planner software. Finally, experiments are conducted on a real F450 quadrotor in a secured laboratory environment, demonstrating stability and good tracking performance of the proposed MLNN observer-based SMC control scheme.

Novel chattering free binomial hyperbolic sliding mode controller for asymmetric cascaded E-type bonded T-type multilevel inverter-based dynamic voltage restorer to meliorate FRT capability of DFIG-based wind turbine

The endurance capability of Doubly Fed Induction Generator (DFIG)-based wind turbine to network against different disturbances is an important criterion to meet the recent grid codes requirements. This generator has to provide the required energy under the perturbation conditions which is principally specified by Fault Ride-Through (FRT) capability. It refers to safe and continuous operation of DFIG without interruption which has been performed by Dynamic Voltage Restorer (DVR) using fast and accurate compensation of the voltage fluctuations. This paper aims to introduce an innovative quasi-sinusoidal voltage synthesizer for DVR to enhance the power quality and power delivery. Hence, a new Asymmetric Cascaded E-type Bonded T-type Multilevel Inverter (ACEBTMI) with binary geometric progression form of DC sources is proposed to provide high-step staircase sinusoidal voltage containing low semiconductor switches. Then, accurate triggering signals for the suggested ACEBTMI corresponding to the voltage fluctuations have been provided by new Chattering Free Binomial Hyperbolic Sliding Mode Controller (CFBHSMC). To validate compensation capability of the proposed DVR, ACEBTMI part has been compared with some traditional and familiar multilevel inverters, and also CFBHSMC part has been compared with SMC, FLC and PID controllers. In precise, the simulation results have definitely confirmed the accurate tracking and robust control performance of CFBHSMC to support ACEBTMI-based DVR which enables DFIG to ride-through different voltage perturbations.

Discrete-Time Impedance Control for Dynamic Response Regulation of Parallel Soft Robots.

Accurately controlling the dynamic response and suppression of undesirable dynamics such as overshoots and vibrations is a vital requirement for soft robots operating in industrial environments. Pneumatically actuated soft robots usually undergo large overshoots and significant vibrations when deactuated because of their highly flexible bodies. These large vibrations not only decrease the reliability and accuracy of the soft robot but also introduce undesirable characteristics in the system. For example, it increases the settling time and damages the body of the soft robot, compromising its structural integrity. The dynamic behavior of the soft robots on deactuation needs to be accurately controlled to increase their utility in real-world applications. The literature on pneumatic soft robots still does not sufficiently address the issue of suppressing undesirable vibrations. To address this issue, we propose the use of impedance control to regulate the dynamic response of pneumatic soft robots since the superiority of impedance control is already established for rigid robots. The soft robots are highly nonlinear systems; therefore, we formulated a nonlinear discrete sliding mode impedance controller to control the pneumatic soft robots. The formulation of the controller in discrete-time allows efficient implementation for a high-order system model without the need for state-observers. The simplification and efficiency of the proposed controller enable fast implementation of an embedded system. Unlike other works on pneumatic soft robots, the proposed controller does not require manual tuning of the controller parameters and automatically calculates the parameters based on the impedance value. To demonstrate the efficacy of the proposed controller, we used a 6-chambered parallel soft robot as an experimental platform. We presented the comparative results with an existing state-of-the-art controller in SMC control of pneumatic soft robots. The experiment results indicate that the proposed controller can effectively limit the amplitude of the undesirable vibrations.

Design of Soft Microjoint to Improve Robotic Cell Micromanipulation Flexibility

Dexterity micromanipulation is a significant topic in the field of robotics. Herein, a novel robotic rotating microjoint controlled by an exogenous magnetic field based on magnetic programmable soft materials, which brings more dexterity to the micromanipulation task is proposed. First, the magnetic soft material is synthesized and the microjoint is manufactured. The maximum rotation angle and response time are characterized. Then the force analysis of the microjoint in a uniform magnetic field is performed and the relationship between the deformation bending angle of a microjoint and the magnetic field magnitude is first proposed. A sliding mode controller based on the deformation mechanism of microjoints and radial basis function neural network (DMRSMC) is proposed to achieve robust deformation control of the microjoint. The experiment that depicts the microjoint is able to achieve a maximum rotation angle of 22.16° and a response time of 16 ms. The DMRSMC controller performs angle control with higher accuracy than conventional SMC and PID controllers. Finally, a dexterous suction mechanism is developed by combining the microjoint with a soft micropipette needle to achieve dexterous grasping of zebrafish embryos with a 97% success rate and an orientation adjustment error is 1.36°.

Power Quality Improvement in Distribution System Using IRP Theory with SMC

This article discusses how to improve power quality in distribution systems by combining (Instantaneous Reactive Power) IPR theory with (Sliding Mode Control) SMC. The distribution system has numerous power quality issues. This paper concentrated primarily on source-side current harmonics. The primary goal of this paper is to reduce source-side current harmonics while also balancing DC-link capacitor voltage. The SMC is used to control the d- and q-axis reference currents. The IPR theory is used in distribution to calculate active and reactive power. The SMC based on IPR theory reduced source current harmonics while maintaining constant DC-link capacitor voltage. The results of MATLAB/Simulation are compared to those of PI and SMC. SMC findings exhibit superior performance than the PI controller.

Fast DC-link voltage control based on power flow management using linear ADRC combined with hybrid salp particle swarm algorithm for PV/wind energy conversion system

Hybrid Energy Systems (HESs) are offering several advantages over conventional generation systems because of the rising need for Renewable Energy Resources (RERs) and its high capability and flexibility of achieving the desired performance for both urban and rural areas. The main goals of HESs are to improve the system performance by increasing its flexibility, reliability and reducing generation instability. In the current work, a hybrid Photovoltaic/Wind Energy Conversion System (PV/WECS) is proposed to supply and support the utility grid. The generated power from the system is greatly responding to the change in both the wind speed and PV irradiance level, and as a result impacting the DC-Bus voltage of the system converters. Therefore, precise, fast and optimum controllers are required for the PV/WECS system to ensure the extraction and generation of stable maximum power during weather variations along with maintaining the DC-Link voltage at the desired value. Further, this study proposes a novel Linear Active Disturbance Rejection Control (LADRC) combined with a hybrid Salp Particle Swarm Algorithm (SPSA) to a grid-connected PV/WECS for extracting the Global Maximum Power (GMP), regulating the DC-Link voltage, and enhancing the active and reactive powers control. The capability of the proposed SPSA-LADRC based-MPPT approach is examined according to the tracking time, accuracy and response to internal and external disturbances and then comparing its performance with other techniques such as SPSA-SMC, SPSA-PID and SPSA-PI controllers respectively. The findings revealed that the LADRC can track and keep the DC-Link voltage as the desired reference value,1500 V, respond much faster than the PI, SMC, and PID controllers as well as keep the THD of the injected current into the grid at a low level of 2.25%. Finally, the performance of the proposed system is experimentally verified using Hardware-In-Loop (HIL). The obtained findings verify the capability and accuracy of the system and its great potential in the management of HESs.

Adaptive Robust Tracking Control of Robotic Manipulator based on SMC and Fuzzy Control Strategy

In recent years, robotic systems have been widely used in different applications, and this has motivated researchers to develop different control methods. A model-free, intelligent, robust control method for a nonlinear robotic manipulator system is proposed in this work. This paper presents a novel solution for the major drawbacks of the sliding mode control scheme, which are chattering. Prior knowledge is needed about the dynamic model of the controlled system and the upper bound of uncertainty. In this paper, a fuzzy-like PD controller with SMC (FLPDSM) is proposed. The fuzzy-like PD controller was designed according to fuzzy rules and membership functions based on the nominal model of the robot manipulator. A robust control term was added to the control signal to compensate for the system uncertainty, and external disturbances are compensated by adding an auxiliary robust term to the SMC control law. Two methods for designing robust control terms are proposed. The first proposed method assumes that the upper bound of system uncertainty is known although it cannot be exactly determined due to external disturbances and uncertainty. Hence, a second method was proposed that assumes this bound to be unknown, and an adaptive gain based on Lyapunov theory was used to derive the adaptation law. The Lyapunov second method was used to ensure the stability of the closed loop system. Performance tests on the proposed methods were implemented through simulation studies for the two-link robotic manipulator, and the test results were compared with the standard SMC to verify the effectiveness of the proposed method. A good trajectory tracking with a high robustness against parameter variations and external disturbances was observed under the presented control scheme.

Feedback Linearization Sliding Mode Control Strategy for Three-Phase Voltage PWM Rectifier Based on New Variable Speed Reaching Law

Three-phase voltage PWM rectifier is a multivariable, strong coupling, nonlinear multi-input and multi-output system. In the design of rectifier control systems, with PI control it is difficult to achieve the ideal control effect, the dynamic performance is poor, and the parameter computation is complex. Moreover, the traditional sliding mode control voltage outer loop suffers from the problem of chattering, which is difficult to solve. Responding to the above issues, a new type of variable speed reaching law is proposed, which is applied to the voltage outer loop sliding mode control, while the feedback linearization principle is introduced to the current inner loop, and a new type of double closed-loop sliding mode control system is obtained by applying the two theories to the design of the sliding mode controller. A simulation model is established in MATLAB/Simulink to compare the PI control, the SMC control and the V-SMC control strategy proposed in this paper (voltage outer loop V-SMC current inner loop FLC-SMC control), and the simulation results show that the rectifier under the new dual-closed-loop sliding mode control strategy has the advantages of good dynamic performance, strong robustness and strong anti-interference ability. At the same time, compared with the traditional sliding mode control strategy, the vibration suppression effect under the proposed control strategy is obvious. Finally, a 10 kW rectifier control system is built on a semi-physical hardware-in-the-loop experimental platform to further verify the correctness and superiority of the proposed control strategy.

On designing a configurable UAV autopilot for unmanned quadrotors.

Unmanned Aerial Vehicles (UAVs) and quadrotors are being used in an increasing number of applications. The detection and management of forest fires is continually improved by the incorporation of new economical technologies in order to prevent ecological degradation and disasters. Using an inner-outer loop design, this paper discusses an attitude and altitude controller for a quadrotor. As a highly nonlinear system, quadrotor dynamics can be simplified by assuming several assumptions. Quadrotor autopilot is developed using nonlinear feedback linearization technique, LQR, SMC, PD, and PID controllers. Often, these approaches are used to improve control and to reject disturbances. PD-PID controllers are also deployed in the tracking and surveillance of smoke or fire by intelligent algorithms. In this paper, the efficiency using a combined PD-PID controllers with adjustable parameters have been studied. The performance was assessed by simulation using matlab Simulink. The computational study conducted to assess the proposed approach showed that the PD-PID combination presented in this paper yields promising outcomes.

Control System for Quadcopter UAV based SMC-RBFNN with External Disturbance

Unmanned aerial vehicles (UAVs) can either be flown autonomously or remotely by a pilot. Due to its many benefits, including the capacity to take off and land vertically and the ability to take off and land in a small space, this form of UAV quadcopter is currently the subject of extensive research. An autonomous UAV is being developed to reduce the likelihood of pilot operating errors when managing the UAV. The quadcopter dynamic system in this study was controlled primarily by a radial basis function neural network (RBFNN), and its performance was evaluated using simulation on a test track with outside disturbances. One test track is used for the simulation, and there are no outside disturbances. Input of external noise occurs concurrently for x, y, and z coordinates. The average of error for the control system SMC and SMC-RBFNN without disturbance is 0 according to the simulation results. Additionally, the SMC control system’s of error with external disturbances is 0.74, whereas it is 0.54 for the SMC-RBFNN control system. This is demonstrated by the system’s ability to return to the test track at the present within 9 seconds while employing the SMC-RBFNN controller. In contrast, the system can reach the test track in 18 seconds while using the SMC. The SMC- RBFNN is one of the suitable control strategies for flight missions with external disturbances, it may be inferred.

Current source converter-based optimal power extraction and power control of a doubly fed induction generator (DFIG) using backstepping control

An improved backstepping control technique for the operation of a doubly fed induction generator (DFIG) powered by a wind turbine (WT) was developed and discussed. It is derived from a current source converter (CSC). The optimal backstepping control (BSC) settings are determined using the CSC approach, which can improve the drive by providing a more rapid dynamic response, greater precision, and stable performance. The CSC approach control function was constructed using the index criterion integral time square error (ITSE) and integral time absolute error (ITAE). With the simulation technique in the MATLAB/Simulink environment, the proposed BSC-CSC effectiveness is confirmed, and analyse the performance by using the PI and SMC control. The results indicate the goals of this work have been achieved in the form of resilience, improved dynamic system efficiency, lowering the harmonic distortion, optimization of stator power, and successfully addressing the problem of model parameter uncertainty.

Path-Tracking Ability of the ASV on Different Adhesion Coefficient Roads Based on Slide Mode Control

A vehicle equipped with an articulated steering system is often used in a particular area, such as a mine or the construction field. These sealing or semi-sealing fields make autonomous driving by an ASV (Articulated Steering Vehicle) easier than in passenger cars. Path-tracking is essential for an autonomous vehicle. To improve the path-tracking ability of an ASV, a path-tracking model is established based on dynamic theory. Then, the slide-mode predictive-control (SMPC) strategy is initiated to design the path-tracking controller. The improvement in the path-tracking ability on roads with different adhesion coefficients is validated via the HIL (Hardware in Loop) platform. According to the simulation in HIL with the provided strategy, the path-tracking error during the typical condition decreased by 21.73~93.84%, demonstrating the SMC controller can be used to improve the path-tracking performance of an ASV.

Application of an intelligent fuzzy logic based sliding mode controller for frequency stability analysis in a deregulated power system using OPAL-RT platform

Owing to unpredicted power demand, integration of distributed generators and parametric disparity in the system cause the power system more intricacy which in turn affects the frequency and power fluctuation critically. To mitigate these phenomena, an intelligent and efficient automatic generation control (AGC) is indispensable. Therefore, in this paper, an intelligent and robust controller named fuzzy sliding mode controller (FSMC) has been recommended to tackle the AGC problem in a deregulated power system in the presence of distributed generators effectively. Again, to manifest its dominance over SMC, fuzzy-PID and PID controllers, dynamic response of the deregulated system under Poolco, Bilateral and Contract violation conditions has been evaluated and compared. Further, to support the FSMC controller’s ability, another test model has been taken for the AGC study. The gains of these controllers have been enumerated by Gannet Optimization Algorithm (GOA) subjecting to a minimization problem. Exploration phase of GOA involves two steps, namely U- & V-shaped diving patterns of Gannets and exploitation phase again involves two steps namely sudden rotation and random walk of Gannets. These four steps ensures quick convergence of the objective function to its optimal value. Apart from transient response under different power transaction conditions, parametric uncertainties of the system, solar and wind power variation and abrupt load change have been considered to support the robustness & credibility of FSMC controller. In addition to this, the stability of the proposed model has been analyzed in the frequency domain. Finally, the MATLAB/SIMULINK based transient response has been validated by a real-time simulator using OPAL-RT-4510, Xilinx Kintex-7 FPGA software.

A novel sliding mode control with MRAS inertia identification for permanent magnet synchronous motors

To enhance the anti-inertia disturbance ability of permanent magnet synchronous motor (PMSM) speed system, an adaptive sliding mode control with inertia identification is proposed. A novel sliding mode control (NSMC) based on a new reaching law coupled with model reference adaptive system (MRAS) inertia identification is realized the adaptive control, named MRAS+NSMC. In the NSMC construct process, an integral sliding mode surface and a variable speed reaching law are introduced to avoid speed differentiation and improve dynamics, respectively. And the new reaching law imported a successive sigmoid( s) to replace the traditional sign( s) to suppress chattering phenomena. For the problem that the performance deteriorated by rotational inertia variation caused by load changes, the inertia is estimated in real time according to the MRAS theory, and the identification value is updated to the NSMC controller to realize adaptive MRAS+NSMC speed control. Experimental results show that the proposed adaptive MRAS+NSMC control has a faster speed response, and the speed response time is reduced from 85 to 49 ms compared with conventional SMC control. In addition, it has strong robustness to inertia disturbances and high speed tracking accuracy. Compared with conventional SMC, the speed tracking accuracy of proposed MRAS+NSMC is increased from 12% to 4%. This makes the proposed MRAS+NSMC control has great potential practical significance for speed control of PMSM.

Dual fuzzy logic PID controller based regulating of dc motor speed control with optimization using Harmony Search algorithm

This paper discusses the implementation of a Proportional-Integral-Derivative (PID) controller for regulating the speed of a closed loop four quadrant chopper fed DC motor. The PID controller is combined with a Dual Fuzzy Logic Controller to form a DFPID controller for enhancing the performance of speed control of the DC motor. The DFLC is optimized using a metaheuristic algorithm known as Harmony Search Algorithm (HSA). The major aim of this research is to gain an effective control over the speed of the motor in the closed loop environment. For achieving this, the parameters for the DFPID are selected through time domain analysis which aims to satisfy the requisites such as settling time and peak overshoot. Initially, the fuzzy logic controller in the DFPID controls the coefficients of the PID achievement gain an effective control over the system error and rate of error change. Further, the DFPID is improved by the HAS for obtaining a precise correction. The solutions obtained by tuning the DFPID controller are evaluated from simulation analysis conducted on a MATLAB/SIMULINK platform. The closed loop performance is analyzed in both time and frequency domain analysis and the performance of DFPID is optimized using the HSA algorithm to obtain precise value of the control process. As observed from the Simulation analysis, the DFPID-HSA generates optimized control signals to the DC motor for controlling the speed. The performance of the intended speed control approach is analyzed in terms of different evaluation metrics such as motor speed, torque and armature current. Experimental outcomes show that the proposed approach achieves better control performance and faster speed of DC motor compared to conventional PID controllers and SMC controllers

A Disturbance Observer-based Novel Fuzzy SMC Control Scheme for Path Tracking of AUV with Mismatched Disturbances

A new sliding mode control scheme is proposed for the path tracking problem of autonomous underwater vehicles (AUVs) with uncertainty and mismatch interference. Considering the complexity of parameter rectification, a fuzzy logic controller-based system rectification scheme is designed in this paper. In the control system, a disturbance observer (DOB) and a radial basis function neural network (RBFNN) are used to estimate the mismatch disturbance and uncertainty, respectively. In addition, this paper analyzes the conditions for the Liapunov stability of the designed controller and the results show the closed-loop stability of the control system. The control scheme can be applied to the path tracking of underwater robots with rapidly changing trajectories in different driving environments. Finally, a number of comparative experiments are carried out to demonstrate the good performance of the proposed controller.

Conditioned adaptive barrier-based double integral super twisting SMC for trajectory tracking of a quadcopter and hardware in loop using IGWO algorithm

Researchers working in the field of unmanned aerial vehicles are observing rapid developments in the field, such as the use of quadrotors to grasp, manipulate, and transport objects. These advancements are made possible through sophisticated control systems, new types of actuation and sensing technologies, and a greater understanding of the aerodynamic effects and gyroscopic moment generated by the rotating blades of the quadrotor involved. Therefore, this research work proposes four novel optimized control laws, i.e., conditioned adaptive barrier-based double integral super twisting sliding mode controller (CABDIST-SMC), BF double integral SMC (BF-DISMC), BF integral SMC, and barrier function-based SMC control laws, for attitude, heading, position, and altitude trajectory tracking of the quadcopter. The non-linear model of the quadcopter is developed using the Lagrange formalism in MATLAB ODE-45 environment, including the gyroscopic moments and aerodynamic effects, and a Lyapunov stability analysis is performed to ensure the asymptotic stability of the system. A 3D-helical complex trajectory is employed to analyze the performance and consistency of the proposed optimized controllers. For performance comparison, the proposed four variants of the SMC are compared with three traditional control strategies, i.e., backstepping SMC, optimized adaptive SMC via particle swarm optimization algorithm, and improved adaptive SMC. These traditional control strategies have also been developed and tested in MATLAB-Simulink. All the controllers are optimized using the improved grey wolf optimization algorithm, and to determine the best control law, six performance indexes, i.e., mean absolute percentage error (MAPE), root mean square error (RMSE), integral square error (ISE), integral absolute error (IAE), integral time absolute error (ITAE), and integral time square error (ITSE) are used. A hardware-in-loop (HIL) test is also performed to validate the performance of the designed novel control law. The C2000 Delfino MCU F28379D launchpad is used for performing the HIL validation test. The simulated results showed that the performance of optimized CABDIST-SMC surpassed all other control laws for altitude, heading, position, and attitude trajectory tracking. It has achieved MAPE of 0.02%, RMSE of 3.9912e−5, ISE of 3.1859e−8, IAE of 7.9823e−4, ITAE of 0.0080, and ITSE of 3.1849e−7 in case of yaw angle control. The proposed control laws have successfully passed the HIL validation test, and real-time implementation of the proposed control laws indicates no significant variations compared to the simulated results.

Cascaded Inner Loop Fuzzy SMC for DC–DC Boost Converter

In this paper, the implementation of the Fuzzy Sliding Mode Controller (FSMC) in the inner loop of the cascaded control structure of the DC–DC Boost Converter is presented. On account of nonlinearity and nonminimum phase nature, switched-mode DC–DC converters show a poor response in their dynamic characteristics. In most of the works, the inner loop is served by SMC/FLC, and the outer loop by PI. In this study, the proposed FSMC, which is the combination of SMC and FLC is recommended in the inner current loop which reduces the chattering phenomena and improves the robustness against uncertainties, disturbances and varying circuit parameters with the reaching law. The Lyapunov approach is considered to study the stability of the proposed controller. A comparative analysis is made with the results obtained from the proposed FSM controller, Fuzzy and SMC control. The effectiveness of the FSMC controller is validated by observing its system performance.

Sugeno-Type Fuzzy Ontology PI Controller for Proportional Electrohydraulic System

In this paper, an ontology representation of the Sougeno-type PI Fuzzy Logic Controller (FLC) is presented. The proposed controller is an extension of the Fuzzy Ontology Controller (FOC), where the new fuzzy annotations relevant to Sougeno-type fuzzy control are added to the ontology. The design of the fuzzy ontology is carried out in Protégé and it is hosted on a remote server in the Virtuoso database. Simulation results for the proportional electrohydraulic system are presented and compared to the PI and the SMC controller. The simulation results show that the proposed concept works, and achieves similar results to the PI controller. Experimental results are carried out on a proportional electrohydraulic system. Results show good tracking capabilities despite slow network communication between the server and experimental setup.

Sliding Mode Controllers Design based on Control Lyapunov functions for uncertain LTI systems

In this paper, a design method of sliding controllers based on control Lyapunov functions for uncertain LTI systems is proposed. Systems with matched non-vanishing disturbances, unmatched uncertainties and uncertain control coefficient matrix are considered. It is shown that whenever a robust nonlinear controller exists that renders the system quadratically stabilizable, in the absence of matched non vanishing disturbances, there is also an appropriate First-Order Sliding-Mode controller stabilizing the origin, that also renders the equilibrium point robustly stable in presence of perturbations. This shows that Sliding-Mode controllers are not more restrictive than other controllers, at least for the class of uncertain systems considered. Moreover, the design based on control Lyapunov functions provides a natural sliding surface, having an asymptotically stable sliding dynamics, so that with the corresponding sliding mode controller ensures global asymptotic stability of the uncertain system. The efficiency of the proposed SMC control is validated experimentally on a Furuta pendulum benchmark.