Sliding Mode Control Structure Research Articles

Agile Attitude Maneuver Control of Micro-Satellites for Multi-Target Observation Based on Piecewise Power Reaching Law and Variable-Structure Sliding Mode Control

This paper addresses the issue of agile attitude maneuver control for low-Earth-orbit satellites during short arc segments for multi-target observations. Specifically, a configuration design for Control Moment Gyroscopes (CMGs) and a hybrid control law are provided. The control law is adept at avoiding singularities and escaping singular planes. Subsequently, an optimal time-based attitude maneuver path-planning method is presented, rooted in the relationship between Euler angles/axis and quaternions. Furthermore, a novel satellite attitude maneuver controller is developed based on a piecewise power-reaching law for variable structure sliding mode control. The paper theoretically demonstrates that the proposed piecewise power reaching law possesses two favorable properties regarding convergence time. On the other hand, the designed reaching law maintains continuity at all stages, theoretically eliminating buffeting. The simulation results demonstrate that the proposed controller achieves an Euler angle control precision of ±0.03° and angular velocity accuracy of ±0.15°/s, fulfilling the demands of multi-objective observational tasks. Compared to conventional power reaching law controllers, the convergence time is reduced by 3 s, and Euler angle accuracy is improved by 70%. This underscores the effectiveness of the proposed algorithm.

Particle Swarm Optimization Based Super Twisting Sliding Mode Controller MPPT Algorithm Design for Solar PV System

To maximise energy harvest while keeping the solar photovoltaic (PV) system stable, proper regulation is essential. In this study, we explore the state-of-the-art in solar PV system management and offer a fresh method: Super Twisting Sliding Mode Controller (STSMC) using Particle Swarm Optimisation (PSO). The suggested method enhances control performance by combining the stability of Sliding Mode Control (SMC) with the optimisation skills of PSO. The goal is to improve solar PV systems' fault tolerance, resilience against uncertainties and disturbances, and Maximum Power Point Tracking (MPPT) accuracy. Results show that the suggested PSO-based STSMC is superior to traditional methods of control. Effective maximum power point tracking (MPPT) is made possible by combining PSO optimisation with the SMC structure. This allows for precise MPPT tracking regardless of the sun irradiation or ambient temperature. The technique also improves the system's fault tolerance and robustness by dealing with uncertainty and disturbances efficiently in real time. The study highlights limitations, such as the use of idealised settings, and provides recommendations for further research to enhance the suggested method. The MATLAB/Simulink Simulation Tool is used for the research.

Implementation of Sliding Surface Moving Anfis Based Sliding Mode Control to Rotary Inverted Pendulum

This study covers the control of the pendulum angle by taking into account the dynamic equations and motor dynamics of the rotary inverted pendulum system, with the help of state variables in the Matlab program, by using the sliding mode control method with sliding surface moving and the adaptive neural fuzzy inference system together. The sliding mode control method with a changing sliding surface is a part of the control structure. The slope of the sliding surface was calculated using the adaptive neural fuzzy inference technique. The optimum values of the coefficients in the adaptive neural-fuzzy inference system structure have been calculated by genetic algorithm. The finding of the coefficients, the sum of the squares of the errors chosen as the objective function. The input of the adaptive neural fuzzy inference system structure consists of the error of the pendulum and the derivative of the error of the pendulum. The gradient of the sliding surface of the sliding mode control structure is the output of the adaptive neural fuzzy inference system structure. According to the findings, the pendulum angle achieved the appropriate reference value after 1.5 seconds, with an error of around zero. It obtained that the engine torque value reaches up to 50 Nm. From here, it is seen that the motor torque values used in practical applications and the motor torque values as a result of this study overlap.

A New Self-Tuning Deep Neuro-Sliding Mode Control for Multi-Machine Power System Stabilizer

In order to increase the accuracy and improve the performance of the power system stabilizer (PSS) controller compared to the methods presented in other studies, this paper presents a new method for tuning sliding mode control (SMC) parameters for a PSS using a deep neural network. This controller requires fast switching which can create unwanted signals. To solve this problem, a boundary layer is used. First, the equations of a multi-machine power system are converted into the standard form of sliding mode control, and then the sliding surfaces are determined with three unknown parameters. Calculating and determining the optimal values (at any moment) for these parameters are fundamental challenges. A deep neural network can overcome this challenge and adjust the control system regularly. In the simulation, a power system with 4 machines and 11 buses is implemented and both phase-to-ground and three-phase errors are applied. The simulation results clearly show the good performance of the proposed method and especially the importance of the deep neural network in the SMC structure compared to other methods.

Road Adhesion Coefficient Estimation Based on Second-Order Linear Extended State Observer

In order to estimate different road adhesion coefficients, a new method based on the second-order linear extended state observer is proposed to improve the active safety and driving stability of vehicles. The vehicle single-wheel driving dynamics model and single-wheel braking dynamics model are built with analyzing the driving and braking processes of the vehicle. The controllers of ASR and ABS are designed by using sliding mode structure control, and the chattering phenomenon of sliding mode control is eliminated by the saturation function. The road adhesion coefficient can be estimated by the second-order linear extended state observer in real time with the wheel speeds, and driving torque and braking torque are used as input variables. The simulation results show that the road adhesion coefficient estimation method based on the second-order linear extended state observer can accurately identify the adhesion coefficient of different roads in the presence of external interference and has strong robustness. At the same time, it also provides a reference for the design of the stability control system of unmanned vehicles.

An Adaptive Sliding Mode Control for Multi-Span Nonlinear Web Material Linkage Systems

This study presents an adaptive controller for multi-span nonlinear web material linkage systems with the characteristic of a variable moment of inertia and operating radius of rolls. Sliding mode control is used to control web tensions as well as velocities of the system due to its robustness against modeling imprecision. In addition, an adaptive law combined with sliding mode control is proposed to estimate the moment of inertia. As a result, the adaptive sliding mode control structure takes advantage of nonlinear sliding mode control and adaptation algorithm to deal with parameter changes. To verify the controller, the stability of the whole system is proved based on Lyapunov’s stability theory. The simulation results illustrate reliable performance by comparing several nonlinear controllers.

Regulating the vibration of aerostatic journal spindle based on piezoelectric ceramics

The aerostatic spindle often occur offset and additional vibration under the action of external load due to the low stiffness, thus affecting the rotary accuracy of the spindle. In order to solve the problem of unbalanced vibration of the spindle, a new type of controllable radial aerostatic bearing is designed by combining piezoelectric ceramics. A bearing-rotor-piezoelectric ceramic coupling model was established, and the control method of variable structure sliding mode control was used to reduce the vibration amplitude due to the unbalance. From the results of simulation and experiment, it is found that when the disturbance is taken as a constant value, the vibration amplitude increases with the increase of force; when the disturbance force is an unknown random force, the control effect is slightly worse than that when the disturbance force is known, but the rotary accuracy can be improved by this suppression effect on the aerostatic spindle. Finally, the correctness and effectiveness of this control method are proved through experiments.

Fuzzy Sliding Mode Control with Moving Sliding Surface of Rotary Inverted Pendulum

In this study, considering the dynamic equations of the rotary inverted pendulum system and the motor dynamics, pendulum angle is controlled with fuzzy logic sliding mode control method which has moving sliding surface using state variables in Matlab program. The sliding surface of sliding mode control method is selected as moving. A fuzzy logic structure is used to calculate the slope of slip surface. The boundary values of the membership functions in the fuzzy logic structure have been optimized using genetic algorithm codes in Matlab program. The sum of the squares of the errors is preferred as the objective function. Inputs of the fuzzy logic structure are the error of the pendulum angle and the derivative of pendulum angle error. In the fuzzy logic structure, the slope of sliding surface of sliding mode control structure is obtained as an output. From the results, it was seen that the pendulum angle reached the desired reference value around the first second and the error was approximately zero. In addition, it has been observed that the motor torque value is at the levels of 20 Nm and the motor current value is at the levels of 3 ampers. It has been obtained from the results that the motor values are at reasonable levels close to the values in practical applications. When the motor is selected according to these obtained values, there won't be a problem with the implementation of this control method in real-time applications of the rotary inverted pendulum system

A Novel MPPT Algorithm for Photovoltaic Systems Based on Improved Sliding Mode Control

Due to the poor tracking performance and significant chattering of traditional sliding mode control in the maximum power point tracking (MPPT) algorithm, a novel MPPT algorithm based on sliding mode control for photovoltaic systems is proposed in this paper. The sliding mode control structure and new sliding mode surface of the multi-power reaching law are designed with the boost converter as the carrier of the photovoltaic system, and the sigmoid function is proposed to replace the symbolic function and saturation function in the power reaching law to improve the reaching rate and control quality of the traditional sliding mode control. Furthermore, the Liapunov function is employed to analyze the accessibility, existence and stability of the improved sliding mode control. Simulation results under dynamic and partial shading conditions show that compared with exponential sliding mode and constant speed sliding mode, the improved sliding mode control strategy can quickly track the maximum power point of photovoltaic systems under various atmospheric conditions. The proposed MPPT algorithm has stronger robustness and universality. Additionally, the efficiency of the proposed algorithm is improved by 2.3% and 5.6% as compared to the exponential sliding model control algorithm and constant velocity sliding model control algorithm. In addition, the experimental platform is constructed to further validate the feasibility and effectiveness of the proposed algorithm.

Rigid-Flexible Coupled Dynamic and Control for Thermally Induced Vibration and Attitude Motion of a Spacecraft with Hoop-Truss Antenna

As space exploration activities are developing rapidly, spacecraft with large antennas have gained wide acceptance in providing reliable telecommunications and astrophysical observations. In this paper, the dynamic responses and control strategy for a spacecraft with a large hoop-truss antenna under solar flux shock are studied. According to the momentum and angular momentum principle, the rigid-flexible coupled rotational dynamic equation and the translational dynamic equation of the system are established, which include the attitude motion of the rigid main body and the vibration of the antenna. Then, a finite element model of the antenna is established to analytically obtain the corresponding vibration modal shape matrix and natural frequencies. Last, the coupled responses for the attitude motion and vibration are investigated. The corresponding control strategy is designed based on a double-loop structure sliding mode control method. The Lyapunov method is used to demonstrate the global asymptotic stability of the system. Simulations verify the effectiveness of the proposed rigid-flexible coupled model and control strategy.

A new adaptive sliding mode controller based on the RBF neural network for an electro-hydraulic servo system

Accuracy and robust trajectory tracking for electro-hydraulic servo systems in the presence of load disturbances and model uncertainties are of great importance in many fields. In this work, a new adaptive sliding mode control method based on the RBF neural networks (SMC–RBF) is proposed to improve the performances of a robotic excavator. Model uncertainties and load disturbances of the electro-hydraulic servo system are approximated and compensated using the RBF neural networks. Adaptive mechanisms are designed to adjust the connection weights of the RBF neural networks in real time to guarantee the stability. A nonlinear term is introduced into the sliding mode to design an adaptive terminal sliding mode control structure to improve dynamic performances and the convergence speed. Moreover, a sliding mode chattering reduction method is proposed to suppress the chattering phenomenon. Three types of step, ramp and sine signals are used as the simulation reference trajectories to compare different controllers on a co-simulation platform. Experiments with leveling and triangle conditions are presented on a robotic excavator. Results show that the proposed SMC–RBF controller is superior to existing proportional integral derivative (PID) and sliding mode controller (SMC) in terms of tracking accuracy and disturbance rejection.

Enhanced Sliding Mode Control for a Nonlinear Active Suspension Full Car Model

This paper delivers findings on optimal robust control studies of nonlinear full car models. A nonlinear active suspension full car model is used, which considers the dynamic of a hydraulic actuator. The investigation on the benefit of using Sliding Mode Control (SMC) structure for the effective trade-off between road handling. The design of SMC in the chassis/internal subsystem is enhanced by modifying a sliding surface based on Proportional-Integral-Derivatives (PID) with the utilization of particle swarm optimization (PSO) algorithm in obtaining the best optimum value of control parameters. The switching control is designed through the Lyapunov function, which includes the boundedness of uncertainties in sprung masses that can guarantee the stability of the control design. The responses of the proposed controller have improved the disturbance rejection up to 60% as compared to the conventional SMC controller design and shown the high robustness to resist the effect of varying the parameter with minimal output deviations. The study proved that the proposed SMC scheme offers an overall effective performance in full car active suspension control to perform a better ride comfort as well as the road handling ability while maintaining a restriction of suspension travel. An intensive computer simulation (MATLAB Simulink) has been carried out to evaluate the effectiveness of the proposed control algorithm under various road surface conditions.

Fractional Order Adaptive Fast Super-Twisting Sliding Mode Control for Steer-by-Wire Vehicles with Time-Delay Estimation

It is difficult to model and determine the parameters of the steer-by-wire (SBW) system accurately, and the perturbation is variable with complex and changeable tire–road conditions. In order to improve the control performance of the vehicle SBW system, an adaptive fast super-twisting sliding mode control (AFST-SMC) scheme with time-delay estimation (TDE) is proposed. The proposed scheme uses TDE to acquire the lumped dynamics in a simple way and establishes a practical model-free structure. Then, a fractional order (FO) sliding mode surface and a fast super-twisting sliding mode control structure were designed on the basic super-twisting sliding mode to ensure fast convergence and high control accuracy. Since the uncertain boundary information of the actual system is unknown, a novel adaptive algorithm is proposed to regulate the control gain based on the control errors. Theoretical analysis concerning system stability is given based on the Lyapunov theory. Finally, the effectiveness of the method is verified through comparative experiments. The results show that the proposed TDE-AFST-FOSMC control scheme has the advantages of model-free, fast response and high accuracy.

Development of on-line neural network based adaptive fractional-order sliding mode robust controller on electromechanically actuated engine cooling system

The reduction of temperature fluctuations around desired reference and control input energy for cooling actuators are among the most important aims of engine thermal management system. However, maintaining of engine/radiator outlet temperature within certain limits is a challenging process in different engine operating conditions due to unknown in-cylinder variable heat transfer rate in terms of the control theory. For this purpose, the thermodynamic model is obtained by dividing into two subsystems, such as the engine and the radiator subsystem in the presence of unknown heat transfer rate, external disturbance, and uncertainties in this study. To increase system robustness, tracking engine inlet/outlet temperature control of engine cooling components is performed using the adaptive fractional-order sliding mode control structure. Moreover, the disturbances acting on the system and unknown heat transfer dynamics of the system are estimated with a radial basis function on-line neural network estimator. The efficiency of proposed controller strategy for electromechanically actuated engine cooling system is compared by proportional–integral–derivative and classical integral sliding mode control under the NEDC (New European Driving Cycle) and WLTP (Worldwide Harmonized Light Vehicles Procedure) transient operating conditions. The temperature error tracking performance is tested by paying attention integral square error, integral absolute error, integral time-weighted absolute error along to the driving cycles. The obtained results showed that the adaptive fractional-order sliding mode control–based engine cooling system outperforms compared to the optimally gain tuned proportional–integral–derivative and integral sliding mode control schemes in terms of reducing of tracking error and engine cooling actuators energy consumption for all engine operating cycles.

Sliding Mode Control for Micro Turbojet Engine Using Turbofan Power Ratio as Control Law

The interest in turbojet engines was emerging in the past years due to their simplicity. The purpose of this article is to investigate sliding mode control (SMC) for a micro turbojet engine based on an unconventional compound thermodynamic parameter called Turbofan Power Ratio (TPR) and prove its advantage over traditional linear methods and thrust parameters. Based on previous research by the authors, TPR can be applied to single stream turbojet engines as it varies proportionally to thrust, thus it is suitable as control law. The turbojet is modeled by a linear, parameter-varying structure, and variable structure sliding mode control has been selected to control the system, as it offers excellent disturbance rejection and provides robustness against discrepancies between mathematical model and real plant as well. Both model and control system have been created in MATLAB® Simulink®, data from real measurement have been taken to evaluate control system performance. The same assessment is conducted with conventional Proportional-Integral-Derivative (PID) controllers and showed the superiority of SMC, furthermore TPR computation using turbine discharge temperature was proven. Based on the results of the simulation, a controller layout is proposed and its feasibility is investigated. The utilization of TPR results in more accurate thrust output, meanwhile it allows better insight into the thermodynamic process of the engine, hence it carries an additional diagnostic possibility.

New structure of sliding mode control for variable speed wind turbine

This article investigates a new sliding mode control structure for a variable speed wind turbine, in order to maximize the captured wind energy and to reduce the transient loads (shafts vibration) caused by the fast fluctuation of wind speed. The variable speed wind turbine control presents a difficult problem because of the nonlinearities of equivalent mathematical models and the effects of external disturbances (wind speed fluctuation). The sliding mode technique is a nonlinear control, widely used in this field; this is due to its robustness in terms of stability and performance against disturbances and modeling uncertainties, and its simplicity of implementation. However, this technique has a major problem which is the chattering phenomenon caused by the discontinuous portion of its control law. A new structure of sliding mode technique is developed in this paper to overcome this phenomenon and maintain the effectiveness of traditional approach. The performance of the developed control will be offered by numerical simulations and will be compared to the basic method of sliding mode control based on a strong nonlinear model of wind turbine.

Design and control of a lower limb rehabilitation robot considering undesirable torques of the patient's limb.

This research introduces a new exoskeleton-type rehabilitation robot, which can be used in lower limb rehabilitation therapy for post-stroke patients. A novel design of a typical knee and ankle rehabilitation robot is proposed. The kinematic and dynamic models of the knee and ankle rehabilitation robot are derived. Furthermore, a super-twisting nonsingular terminal sliding mode control is developed to achieve the desired training missions and its results are compared with those of an adaptive sliding mode control. To reduce undesired interaction torques between knee and ankle rehabilitation robot and patient, an admittance control algorithm is added to the controller to guarantee a safe therapy session. The admittance super-twisting nonsingular terminal sliding mode control structure is considered as the novelty of this article. Taking into account the dynamic uncertainties, external disturbances, and the interaction torques, the validity of the admittance super-twisting nonsingular terminal sliding mode control controller is approved by various numerical simulations over the admittance adaptive sliding mode control.

Nonlinear disturbance observer based adaptive super-twisting sliding mode control for generic hypersonic vehicles with coupled multisource disturbances

In practical, there often exist structural uncertainties, measurement errors, and the aerodynamic perturbations in the flight control systems of the hypersonic vehicles (HSVs). The control performance degradation and loss of stability may be induced if the coupled multisource uncertainties are ignored. To address this problem, this paper develops a novel multivariable robust adaptive sliding mode control structure. Benefiting from the second-order characteristics of the super-twisting controller, the uncertainties from the unknown nonlinearities and the lumped disturbances can be surmounted respectively. Meanwhile, the finite time convergence can be obtained and the continuity of the control signals can be guaranteed. Moreover, to cope with the unknown upper bounds of lumped uncertainties, a novel update law is developed by analyzing the connection between the control gains and the boundaries. Moreover, for the purpose of compensating the mismatched uncertainties in HSVs, a robust disturbance observer is introduced into the sliding surface such that the sliding-mode dynamics are stable with L2−L∞ performance. The closed-loop control system is proved to be globally ultimately stable. Simulation results indicate that the proposed control scheme works well compared with the existing methods.

Variable structure power control under different operating conditions of PM synchronous generator wind farm connected to electrical network

The enlarged penetration of wind power into electrical network brings challenges to control strategies of variable speed wind energy conversion systems (VS-WECS). In this study, a nonlinear control scheme for wind farm system (WFS) is proposed. The control technique is realised using variable structure sliding mode control (VSSMC). The generator side rectifiers control is used to keep the generator rotor velocities at an optimal value obtained from the maximum power point tracking (MPPT) algorithm to maximise the total extracted power. The grid-side inverter injects the generated power into the AC network, regulates DC-link voltage and it is used to achieve unity power factor. The simulation results demonstrate the effectiveness of the proposed VSSMC strategy in different scenarios, and their advantages are shown in comparison with a conventional proportional integral (PI) control approach under grid fault conditions and the possible presence of uncertainties.

Designing observer based fuzzy terminal sliding mode controller for nonlinear dynamical model of vehicles: fixed time approach

In this paper, an observer based fuzzy fixed time terminal sliding mode controller is proposed for nonlinear dynamic of vehicle model. A novel fixed time terminal sliding mode control structure is proposed to develop the efficiency of the sliding mode controller, where the convergence of tracking error to zero achieves in finite time. A fuzzy logic controller is utilized to tune parameters of the fixed time terminal sliding controller to decrease the chattering phenomena. Variations of vehicle parameters are considered as bounded uncertainties, which are estimated and compensated through the design of developed observer (ESO) controller. Compare to researches that concentrate on robust controller, the proposed method distillates (1) the convergence of the tracking error in finite time (2) the reduction of the chattering by the fuzzy gain (3) designing stable robust observer for the proposed complicated system. Simulation results verify that performance of the suggested methodology to improve in comparison with both the classic PID and sliding mode controller design procedure.