Sliding Mode Control Controller Research Articles

Performance improvement of predictive voltage control for interlinking converters of integrated microgrid

Voltage quality in Renewable Energy System may be harmed by varying power demand and fluctuating energy source outputs. The model predictive voltage (MPV) control approach is suggested in this study. The proposed control strategy enables appropriate power interactions between the AC and DC subgrids while sharing power fluctuations in a coordinated way. Both the AC and DC subgrids support each other in accordance with their normalized relative changes in AC frequency and DC voltage, respectively. A typical photovoltaic (PV) wind-battery-based hybrid AC/DC microgrid is modelled and investigated, and the usefulness of the proposed scheme is validated under the renewable energy variations and load perturbations. MATLAB/Simulink has validated the efficacy of the suggested strategy. A set of comparative tests was conducted between conventional Proportional-Integral (PI) control, Sliding Mode Control (SMC) strategies, and a novel Model Predictive Voltage Control (MPV) approach under diverse conditions. The aim was to comprehensively assess the advantages of the proposed MPV method. Results demonstrate that, in contrast to traditional PI and SMC control strategies, the MPV technique exhibits distinct benefits in terms of superior control performance and achieves exceptionally low Total Harmonic Distortion (THD) values. Ultimately, the proposed solution not only raises the performance standard but also ensures the stable operation of the Renewable Energy System (RES).

Performance Comparison of a DC–DC Boost Converter With Conventional and Non-linear SMC Controller in Dual Loop Structure

Generally, the control system confronts various control techniques in the dual-loop control concept. Most of the studies deal with two different controllers in their loops, which increases the problem of designing two distinct procedures with lengthened calculations. In this article, different control techniques like conventional proportional integral (PI), proportional integral derivative (PID), and nonlinear sliding mode control (SMC) have been discussed, and the implementation of SMC in the Dual loop control of a DC–DC Boost converter is presented. The converter’s dynamic behavior is observed by driving their analytical equations. The effective controller for the proposed converter is ascertained by their comparative analysis. The proposed concept is validated with MATLAB/Simulink and a hardware prototype. The controller’s response is compared for various disturbances. Here, dual-loop SMC is put forward in both loops and its competence is confirmed with a minimal settling period of 0.005 sec and a percentage overshoot of 0.2% during the startup conditions, whereas during the line disturbances a minimum peak time of 0.0001 sec is achieved with a settling time of 0.025 sec. Additionally, a nil percentage overshoot and a settling time of 0.02 sec with a 0.001 sec peak time are attained during the load variations. Furthermore, a settling time of 0.01 sec and a percentage overshoot of 0.8% is reached during the reference voltage variations. From the numerical analysis, it is contemplated that an appropriate selection of SMC controllers in both the outer and inner loop results in optimal performance of the converter during the closed loop operation. Finally, the SMC + SMC controller exhibits superior controlling action compared to PI + PI and PID + PID controllers.

Trajectory tracking for non-holonomic mobile robots: A comparison of sliding mode control approaches

This paper implements and compares the performance of three controllers based on Sliding Mode Control (SMC) applied to the motion control of mobile robots. The controllers include a standard SMC controller and two variations, namely Dynamic Sliding Mode Control (D-SMC) and Dual Sliding Mode Control (DM-SMC). The three controllers differ from conventional SMC approaches since they are designed based on a generic reduced-order empirical model that can represent any system that exhibits behavior akin to a First-Order Plus Delay Time (FOPDT) system. In this study, the comparison of controllers focuses on the Trajectory Tracking Problem (TTP) of a Nonholonomic Mobile Robot (NMR). Performance indices are employed to quantify the controllers' results across three trajectory types. Simulation results evidence that if a smooth curvature trajectory is tracked, the best performance (in terms of minimizing trajectory tracking error and controller effort) can be obtained by using a DM-SMC. On the other hand, if there are discontinuities in the curvature, the results suggest that a better alternative is the D-SMC since it compensates for abrupt changes as in the case of tracking a square trajectory. Overall, the findings from this work demonstrated that the use of simplified empirical models to design SMC-based motion controllers can be successfully applied to solve the TTP of NMR.

Rotary inverted pendulum control using neuro-adaptive robust generalized dynamic inversion

The objective of this research is to design a robust control system for trajectory tracking of the under-actuated Rotary Inverted Pendulum (RIP). The focus is on achieving semi-global asymptotic stability in the absence of knowledge about the RIP geometric and inertia parameters. The control design commences by formulating differential servo constraint dynamics (VCD) that encapsulates the control objectives for the RIP. The baseline generalized dynamic inversion (GDI) control law is derived by inverting the VCD for the control voltage input using the Moore–Penrose generalized inverse. To enhance robustness against modeling uncertainties and exogenous disturbances, a sliding mode control (SMC) element is integrated within the GDI control system, resulting in the robust GDI (RGDI) control system. Furthermore, an adaptive estimator that is based on Radial Basis Function Neural Networks (RBF-NN) is adopted to eliminate the dependency of the RGDI control system on the RIP mathematical model. The weighting matrices of the RBF-NN are updated with the aid of a Lyapunov control function. The proposed control system offers robust solution and guarantees semi-global asymptotic stability to the unstable equilibria of the RIP dynamics in the absence of a mathematical model. The proposed control system’s performance is evaluated through computer simulations and experimental tests on a real RIP system. Comparative analyses with traditional SMC and linear quadratic control methodologies are conducted to show the effectiveness of the proposed approach.

Sliding mode controller with neural network compensation for tank

The control effectiveness of the all-electric tank stabilizers directly affects the firing accuracy of the tank gun. In order to improve the firing accuracy of the moving tank, this paper proposes a sliding mode control (SMC) strategy using neural network feed-forward compensation for the tank bidirectional stabilizers. SMC technology can quickly and effectively deal with uncertainties, unmodeled terms, and external disturbances in complex tank systems. Neural networks possess the advantage of approximating arbitrary continuous functions in finite time, realizing the estimation of SMC control errors with feed-forward compensation. The Lyapunov stability analysis proves that the designed controller can achieve asymptotic stabilization in finite time. Finally, both co-simulation and physical experiments are conducted. The results show that the proposed control strategy possesses better tracking speed and tracking accuracy compared to the conventional controller and exhibits strong robustness.

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.

Precision Landing of Unmanned Aerial Vehicle under Wind Disturbance Using Derivative Sliding Mode Nonlinear Disturbance Observer-Based Control Method

Unmanned aerial vehicles (UAVs) are extensively employed in civilian and military applications because of their excellent maneuverability. Achieving fully autonomous quadrotor flight and precision landing on a wireless charging station in the presence of wind disturbance has become a crucial research topic. This paper presents a composite control technique for UAV altitude and attitude tracking in harsh environments, i.e., wind disturbance. A composite controller was developed based on nonlinear disturbance observer (NDOB) control theory to allow the UAV to land in the presence of random external wind disturbances and ground effects. The NDOB estimated the unknown wind disturbance, and the estimation was fed into the derivative sliding mode nonlinear disturbance observer-based control (DSMNDOBC), allowing the UAV to perform autonomous precision landing. Two loop designs were applied: the inner loop for stabilization and the outer loop for altitude tracking. The quadrotor model dynamics and the proposed controller, DSMNDOBC, were simulated employing MATLAB/Simulink®, and the results were compared with the one obtained by the proportional derivative (PD) controller and the sliding mode controller (SMC). The simulation results indicated that the DSMNDOBC has superior altitude and attitude control compared to the PD and SMC controllers and better disturbance estimation and attenuation performance.

Design and position-tracking control of a flexible joint based on the tendon-sheath mechanism

In this study, a flexible joint comprising active and passive driving modes was designed based on the tendon-sheath mechanism. Further, angle sensors and series elastomers (SE) were integrated inside the joint to produce a compact and flexible structure. First, a model of the flexible joint was established based on the involved stiffness relation, and this model was validated using the dSPACE system. Next, to respond to the low control accuracy and poor anti-interference ability of the flexible joints, a sliding-mode controller (SMC) was designed to facilitate the precise position control, as well as achieve improved robustness. However, the flexible joint was prone to considerable tremors when the overall system was subjected to a large load mass. Therefore, a fuzzy-modified adaptive SMC (FMASMC), which adaptively adjusts the SMC parameters, was designed based on the historical-state data of the system. This control method could suppress the trembling phenomenon of the system while improving its control accuracy. Finally, it was experimentally verified that the compliant joint could achieve the expected functions. Compared with the proportional–integral–derivative (PID) and SMC control algorithms, the FMASMC algorithm could effectively overcome the tremors of the compliant actuation system and improve its control accuracy; moreover, it is also suitable for controlling other compliant joints.

An enhanced direct torque control strategy with composite controller for permanent magnet synchronous motor

AbstractDirect torque control (DTC) based on sliding mode control (SMC) has been widely applied to permanent magnet synchronous motor (PMSM) drives for torque ripple reduction and flux tracking. However, the control performance may be degraded due to disturbances such as variations in motor parameters or uncertainties. In this paper, a DTC strategy with an improved composite SMC controller is proposed for the PMSM drive system to enhance its performance under various disturbances. The speed controller is first designed based on a proposed adaptive reaching law (ARL) to eliminate chattering that appears in the conventional SMC, accelerate convergence, improve tracking performance, and reduce torque ripples. Then, an enhanced extended sliding mode disturbance observer (E2SMDO) is developed to estimate the lumped disturbances of the PMSM drive system in real time and compensate for a feedforward to the speed controller. By combining the ARL and E2SMDO, a composite controller (denoted ARL + E2SMDO) is established, whose stability is proven through the Lyapunov theory. The effectiveness of the proposed method is validated by simulations and experiments. The results of both simulations and experiments demonstrate that the composite ARL + E2SMDO controller has a fast dynamic response, reduced torque ripples, strong robustness, and good anti‐disturbance compared to other conventional methods.

Continuous robust controller with fixed convergence time for synchronization of perturbed nonlinear transducers

The synchronization of two chaotic electrostatic and electromechanical transducers is addressed via a continuous terminal sliding-mode control (SMC) strategy. Recently, fixed-time convergence has received increased attention among scholars. The convergence time with this type of controller has an upper bound independent of the initial conditions. In this regard, two fixed-time sliding variables are proposed to design a robust continuous controller having a fixed-time convergence feature. Then, a robust SMC control is formulated to steer the error states onto the sliding surfaces despite the external disturbances and model uncertainties. Due to the continuous structure of the designed strategy, the proposed controller is chattering-free, which is essential in many practical applications. The convergence proof for the continuous robust controller based on the Lyapunov stability theory has been presented. Finally, a comparison of the proposed approach with existing methods has been illustrated through simulation results to demonstrate its superiority.

Sliding Mode Wheel Slip Control for Regenerative Braking of an All-Wheel-Drive Electric Vehicle

Abstract Regenerative braking is one of the main advantages of electric propulsion systems. In such systems, the vehicle brake controller has to prioritize safety while maximizing the recovered energy at all times. This paper proposes a two-step hierarchical brake controller for a dual-motor all-wheel-drive electric vehicle. In the first step, a novel sliding mode controller (SMC) generates the total braking torque on each axle to independently control the slip on the front and rear wheels. In the second step, the torque split controller assigns motor and friction brake torques to maximize the recovered energy. By incorporating the effects of changing vehicle speed, the proposed SMC controller accounts for the nonlinearities in vehicle dynamics and tire model and considers the weight transfer due to vehicle deceleration while being robust to disturbances. Using simulations, we show that while the traditional SMC formulation is not effective during emergency braking scenarios, the proposed formulation successfully generates control commands to bring the vehicle to a stop position at a minimum distance. Furthermore, our controller can maintain both wheels in the stable slip region, even when starting from a locked position. The performance of the proposed controller is evaluated for an emergency braking scenario and on an aggressive segment of the US06 cycle.

Lateral Trajectory Tracking of Self-Driving Vehicles Based on Sliding Mode and Fractional-Order Proportional-Integral-Derivative Control

The tracking accuracy and vehicle stability of self-driving trajectory tracking are particularly important. Due to the influence of high-frequency oscillation near the sliding mode surface and the modeling error of the single-point preview model itself when using sliding mode control (SMC) for the trajectory tracking lateral control of self-driving vehicles, the desired tracking effect of self-driving vehicles cannot be achieved. To address this problem, a combination of sliding mode control and fractional-order proportional-integral-derivative control (FOPID) is proposed for the application of a trajectory tracking lateral controller. In addition, in order to compare with the trajectory tracking controller built using the single-point preview model, 12 real drivers with different levels of proficiency were selected for operational data collection and comparison. The simulation results and hardware-in-the-loop results show that the designed SMC + FOPID controller has high tracking accuracy based on vehicle stability. The trajectory accuracy based on SMC + FOPID outperforms the real driver data, SMC controller, PID controller, and model prediction controller.

Enhancing power control in doubly fed induction generator based wind turbines: a performance comparison of fuzzy logic and sliding mode control methods

Abstract Effective power regulation is critical for ensuring the stability and performance of Doubly Fed Induction Generator (DFIG)-based wind turbines. This study conducts a comparative study between two control methodologies: fuzzy logic control (FLC) and sliding mode control (SMC), to regulate power in DFIG-based wind turbines. The paper emphasizes the importance of power regulation in wind turbines and its impact on grid stability, presents mathematical equations governing DFIG-based wind turbine systems, encompassing machine equations, power equations, and control objectives related to power regulation. A comprehensive model of the DFIG-based wind turbine system is developed, accounting for dynamic machine behavior and grid interface considerations. The modeli ng process integrates relevant electrical and mechanical components, along with power regulation control strategies. Subsequently, FLC and SMC control methodologies are developed and implemented to regulate desired power. Detailed discussions on controller design and tuning are provided, aligning with specific power control requirements. The results highlight SMC’s effectiveness in achieving precise power regulation within DFIG-based wind turbines, showcasing its superior response characteristics. The study offers valuable insights into the advantages and trade-offs associated with each control approach, aiding researchers and practitioners in selecting the most suitable control methodology for their operational needs. In summary, this paper contributes to the field of wind turbine control systems through a comparative study of FLC and SMC controllers, focusing on regulating power in DFIG-based wind turbines. The findings demonstrate SMC’s superior performance in response, enhancing our understanding of control methodologies for optimizing wind turbine performance and grid integration in sustainable energy systems.

Simultaneous adjustment of balance maintenance and velocity tracking for a two-wheeled self-balancing vehicle

The purpose of this research is the development a method for simultaneously adjusting the velocity tracking control and the inclination angle stabilization using control techniques for a two-wheeled self-balancing vehicle. The control tasks involve balancing the vehicle around its unstable equilibrium configuration along with steering and velocity tracking. In this study, the mathematical dynamic model of the vehicle is derived using the Lagrange method, under the assumptions of pure rolling and no-slip conditions which are expressed through nonholonomic constraint equations. Along with the mathematical descriptions, a multibody virtual prototype featuring advanced tire-ground interaction modeling has been developed using the MSC Adams software suite. Several classical and modern control strategies are investigated and compared to implement the method. These include Sliding Mode Control (SMC), Proportional Integral Derivative (PID), Feedback Linearization (FL), and Linear Quadratic Regulator Control (LQR) for the under-actuated and unstable subsystem that accounts for the pitch and longitudinal motions. The capabilities of these control strategies are verified and compared not only through Matlab simulation but also using Adams-Matlab co-simulation of the controller and the plant. Although every control technique has its advantages and limitations, the extensive simulation activities conducted for this study suggest that the SMC controller offers superior performances in keeping the system balanced and providing good velocity-tracking responses. Moreover, a Lyapunov-based analysis is used to prove that the sliding mode control achieves finite time convergence to a stable sliding surface. These advantages are counterbalanced by the complexity and the large number of parameters belonging to the designed SMC laws, the scheduling of which can be difficult to implement. For the comparison results another non-linear control strategy, that is, the feedback linearization method, is presented as an alternative. Through the Jacobian linearization approach the mathematical model of the system is linearized, allowing the use of control techniques such as linear quadratic regulation, which are deployed to treat the balancing, steering, and velocity tracking tasks. Finally, the empirical tuning of a PID controller is also demonstrated. The performance and robustness of each controller are evaluated and compared through several driving scenarios both in pure-Matlab and Adams-Matlab co-simulations.

Mode Predictive Direct Power Control Scheme with Fixed Operation Frequency for a Vienna Rectifier Based on Voltage‐Sensorless

Model predictive direct power control (MPDPC) is a suitable method for the highly nonlinear system of a three‐level Vienna rectifier. However, the traditional MPDPC suffers from irregular switching states, which can decrease current tracking accuracy and generate high current ripple and electromagnetic noise. Additionally, the use of sensors can increase system hardware costs and complexity. To enhance operational reliability and reduce the fault impact of AC voltage sensors, a double closed‐loop control strategy based on voltage‐sensorless MPDPC in the inner loop and sliding mode control (SMC) in the outer loop is proposed. First, the virtual flux model of the three‐phase Vienna rectifier is established in the two‐phase static coordinate system, and the second‐order low‐pass filter is used to improve the voltage observer to estimate the grid‐voltage. Meanwhile, an improved grid voltage observer based on the second‐order low‐pass filter is designed to improve the observation effect. Second, to solve the variable switching operation, current fluctuation and wide harmonic spectrum caused by the traditional MPDPC effectively, a double closed‐loop control strategy with constant switching frequency based on voltage‐sensorless MPDPC in the inner loop and SMC control in the outer loop is proposed. Based on the principle of SVPWM modulation, the modulation voltage of SVPWM is calculated directly, in order to verify the correctness of the theoretical analysis, extensive simulation and matching experimental is presented to verify the correctness of the theoretical analysis. © 2023 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Voltage Stability and Power Sharing Control of Distributed Generation Units in DC Microgrids

Advancements in power conversion efficiency and the growing prevalence of DC loads worldwide have underscored the importance of DC microgrids in modern energy systems. Addressing the challenges of power-sharing and voltage stability in these DC microgrids has been a prominent research focus. Sliding mode control (SMC) has demonstrated remarkable performance in various power electronic converter applications. This paper proposes the integration of universal droop control (UDC) with SMC to facilitate distributed energy resource interfacing and power-sharing control in DC microgrids. Compared to traditional Proportional-Integral (PI) control, the proposed control approach exhibits superior dynamic response characteristics. The UDC is strategically incorporated prior to the SMC and establishes limits on voltage variation and maximum power drawn from the DC–DC converters within the microgrid. A dynamic model of the DC–DC converter is developed as the initial stage, focusing on voltage regulation at the DC link through nonlinear control laws tailored for Distributed Generation (DG)-based converters. The UDC ensures voltage stability in the DC microgrid by imposing predetermined power constraints on the DGs. Comparative evaluations, involving different load scenarios, have been conducted to assess the performance of the proposed UDC-based SMC control in comparison to the PI control-based system. The results demonstrate the superior efficiency of the UDC-based SMC control in handling dynamic load changes. Furthermore, a practical test of the proposed controller has been conducted using a hardware prototype of a DC microgrid.

Longitudinal and Lateral Stability Control Strategies for ACC Systems of Differential Steering Electric Vehicles

To ensure lateral stability during the cruising of a differential steering vehicle (DSV), this paper presents a curving adaptive cruise control (ACC) system coordinated with a differential steering control (DSC) system, which considers both longitudinal cruising capability and lateral stability on curved roads. Firstly, a DSV dynamics model is developed and a control strategy architecture for a curving ACC system is designed. Then, the car-following control strategy for the curving ACC system is designed based on the fuzzy model predictive control (FMPC) algorithm. The strategy aims to improve the economy and balances car following, safety, comfort and economy. Moreover, fuzzy logic rules are designed to update the weight coefficients of the performance indicators in real time. Finally, the lateral stability controller is designed based on the preview algorithm and the sliding mode control (SMC) algorithm. The simulation results show that the lateral stability of the DSV during the curving cruise is realized via the control of the differential drive torque of the two front wheels. The proposed FMPC controller and SMC controller based on the preview control algorithm satisfy the performance in terms of vehicle following and lateral stable driving in the process of cruising.

Adaptive robust control for biped walking under uncertain external forces

Adaptability and robustness are important expressions of the intelligent walking ability of biped robots. This paper is concerned with the problem of dynamical biped walking and robust control of biped robots under external forces. Due to the characteristics of strong coupling and hybrid, the robotic system is modeled as a rigid kinematic chain with Lagrange equations. A novel adaptive feedback controller is proposed based on sliding mode control (SMC) and hybrid zero dynamics. The novelty of the proposed work lies in taking the uncertainty of upper-bound error into consideration. The hybrid robust control is mentioned to approximate unknown dynamic functions with the adaptive weight. The restricted Poincare return map is utilized to analyze the stability of a nonlinear impulsive system. It ensures that the flow of the continuous subsystem can pass through the impact cross section. Finally, the simulation results illustrate that the proposed adaptive SMC control system can favorably track the reference trajectories, even when a fault occurs, which verifies the effectiveness of the proposed method.

Fault tolerant control of two tanks system using gain-scheduled type-2 fuzzy sliding mode controller

To save the robustness of type 2 fuzzy logic control technique and to avoid the high energy consumption that represents the sliding mode control (SMC) technique control technique, without failing the performance of the system, we propose a new fault tolerant control method based on gain-scheduled sliding mode control with interval type 2 fuzzy logic (FTCGST2FSMC) applied to the hydraulic system (two tanks system) with an actuator fault. The proposed control scheme avoids a difficult modeling, due to the chatter effect of the SMC, guarantees the stability studied by Lyapunov with the robustness of the system. The gains of the control with the SMC controller are modified and changed by an adaptation with a technique based on type 2 fuzzy logic, used to improve the gains of the controller when the fault is added, the proposed FTCGST2FSMC controller has been compared with the sliding mode controller. The results obtained confirm the robustness and the performance of this method, in the presence of the actuator fault effect.

Comparative study between PI and SMC controllers for DFIG using fuzzy wind power estimator

In this paper, we are interested in the control of the rotor current of the doubly feed induction generator (DFIG), that is used in wind turbines. In this context, we present a comparative study between two types of controllers. The first is based on a classic PI proportional-integral control, while the second is based on the SMC sliding control. The command chain uses a fuzzy estimator of the wind power, which makes it possible to determine the reference speed of DFIG. The system includes essentially a turbine, two converters, one on the rotor side and the other on the grid side, and a filter. The grid-side converter is used to maintain a constant DC bus voltage and to control rotor reactive power. The rotor side converter is used to control the speed of the DFIG to guarantee maximum power extracted from the turbine. In addition, this converter allows controlling the reactive power through the control of the rotor current according to the axis "d" of the frame linked to the rotating field. The simulation results show the effectiveness of sliding mode control (SMC) for the considered system.