Sliding Mode Control Methodology Research Articles

Distributed consensus and formation control of multi-AUV systems under actuator faults and switching topology

This note presents the distributed consensus and formation control for a group of AUVs, comprising one leader and three followers arranged in a diamond formation. The study addresses significant control challenges, including external disturbances, noise, model uncertainties, actuator faults, stochastic switching topologies, time-varying communication delays, and positional information between agents. Stochastic switching topologies are assumed to follow a Markov chain. To effectively address these challenges and ensuring satisfactory performance levels, two control architectures have been formulated to facilitate the imposition of desired trajectories upon the system states. The initial architecture amalgamates sliding mode control methodology with adaptive algorithms, designed explicitly for tracking missions in the presence of fully functional actuators. In response to potential actuator failures, the second control architecture integrates passive fault-tolerant techniques, significantly enhancing system reliability under such circumstances as well as switching topology. The proposed framework demonstrates its effectiveness in managing the high nonlinearity and coupled dynamics of AUVs. Simulation results validate the efficacy of the developed strategy. It successfully establishes a desired consensus and formation among agents, reduces chattering phenomena, accurately tracks reference trajectories, handles disturbances and uncertainties within an unknown domain, and achieves finite-time convergence.

Enhancing grid-connected photovoltaic system performance with novel hybrid MPPT technique in variable atmospheric conditions

This paper proposes an innovative approach to improve the performance of grid-connected photovoltaic (PV) systems operating in environments with variable atmospheric conditions. The dynamic nature of atmospheric parameters poses challenges for traditional control methods, leading to reduced PV system efficiency and reliability. To address this issue, we introduce a novel integration of fuzzy logic and sliding mode control methodologies. Fuzzy logic enables the PV system to effectively handle imprecise and uncertain atmospheric data, allowing for decision-making based on qualitative inputs and expert knowledge. Sliding mode control, known for its robustness against disturbances and uncertainties, ensures stability and responsiveness under varying atmospheric conditions. Through the integration of these methodologies, our proposed approach offers a comprehensive solution to the complexities posed by real-world atmospheric dynamics. We anticipate applications in grid-connected PV systems across various geographical locations and climates. By harnessing the synergistic benefits of fuzzy logic and sliding mode control, this approach promises to significantly enhance the performance and reliability of grid-connected PV systems in the presence of variable atmospheric conditions. On the grid side, both PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) algorithms were employed to tune the current controller of the PI (Proportional-Integral) current controller (inverter control). Simulation results, conducted using MATLAB Simulink, demonstrate the effectiveness of the proposed hybrid MPPT technique in optimizing the performance of the PV system. The technique exhibits superior tracking efficiency, achieving a convergence time of 0.06 s and an efficiency of 99.86%, and less oscillation than the classical methods. The comparison with other MPPT techniques highlights the advantages of the proposed approach, including higher tracking efficiency and faster response times. The simulation outcomes are analyzed and demonstrate the effectiveness of the proposed control strategies on both sides (the PV array and the grid side). Both PSO and GA offer effective methods for tuning the parameters of a PI current controller. According to considered IEEE standards for low-voltage networks, the total current harmonic distortion values (THD) obtained are considerably high (8.33% and 10.63%, using the PSO and GA algorithms, respectively). Comparative analyses with traditional MPPT methods demonstrate the superior performance of the hybrid approach in terms of tracking efficiency, stability, and rapid response to dynamic changes.

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.

Optimal sliding mode control for frequency stabilization of hybrid renewable energy systems

AbstractThe constant changes in the load power lead permanently to a power mismatch between the power generation and the power consumption. So, the system frequency due to the power imbalance deviates from the nominal value. Consequently, a control loop should be implemented to stabilize the system frequency whenever a load change occurs. This paper presents a new super‐twisting sliding mode control methodology for obtaining an optimal frequency performance in a multi‐pool system. The paper presents a three‐pool system for frequency deviation problems using an optimal gain Super Twisting Sliding Mode Controller (STSMC), which regulates the frequency change and the line power change to zero in a minimal time. The extent of the excellence of the study proposed is evaluated by comparing it with three Benchmark classical controllers, which are the Tilt‐Integral‐Derivative (TID), Proportional‐Integral‐Derivative (PID), and Fractional‐Order PID (FOPID). The parameters of the four controllers are determined by a proposed physical meta‐heuristic optimization technique called Transient Search Optimizer (TSO), inspired by the dynamic behaviour in the electrical circuits comprising storage elements such as capacitors and inductors during the switching actions. The system simulation is performed, and the STSMC proved overwhelming superiority over other controllers, as it deals better with the transient interval of the system response. Renewable Energy sources (RESs) like photovoltaic and wind energy systems are established, and the STSMC is tested with industrial and residential load models. Finally, energy storage devices such as batteries and superconducting magnetic energy storage are implemented to suppress the rapid fluctuations in the system response, and it succeeded in doing that as the system oscillations are greatly damped with the energy storage devices.

A finite-time sliding mode control technique for synchronization chaotic fractional-order laser systems with application on encryption of color images

In recent years, fractional order Laser chaotic systems have gained popularity in both theory and applications, and various classes of these systems have been introduced. This paper presents a dynamic-free sliding mode control (SMC) methodology to synchronize a class of unknown fractional order (FO) Laser chaotic systems with input saturation. The proposed method uses a defined continuous function instead of the discrete sign function and is based on the FO version of the Lyapunov stability theorem. The result is a novel finite-time SMC (FTSMC) methodology that effectively suppresses chaotic behavior in FO Laser chaotic systems without undesirable chattering. This approach is designed to take advantage of the boundedness feature of the FO chaotic system. The efficacy of the FTSMC is demonstrated by applying the method to a chaotic FO Laser system at two different non-integer orders, and its practical applicability is demonstrated by using it to encrypt/decrypt color pictures. The suggested encryption/decryption methodology uses an adaptation of the pre-diffusion permutation-diffusion structure to increase security. Performance and security analyses, including histogram analysis, neighboring pixel correlation analysis, and information entropy analysis, provide further support for the suggested encryption system's superiority.

Hybrid Approaches-Based Sliding-Mode Control for pH Process Control.

This paper presents two hybrid control topologies; the topologies are designed by combining artificial intelligence approaches and sliding-mode control methodology. The first topology mixes the learning algorithm for multivariable data analysis (LAMDA) approach with sliding-mode control. The second offers a Takagi-Sugeno multimodel approach, internal model, and sliding-mode control. The process under study is a nonlinear pH neutralization process with high nonlinearities and time-varying parameters. The pH process is simulated for multiple reference changes, disturbance rejection, and noise in the transmitter. Performance indices are used to compare the proposed approaches quantitatively. The hybrid control topologies enhance the performance and robustness of the pH process under study.

A hybrid sliding mode controller approach for level control in the nuclear power plant steam generators

This work presents a hybrid sliding mode controller approach for level control in the nuclear power plant steam generators. In a nuclear power plant, the steam generator is one of the essential pieces of equipment. Therefore, this paper aims at a robust hybrid scheme that merges internal model control concepts, sliding mode control methodology, and gain scheduling using Takagi–Sugeno multimodel fuzzy systems. Since the process presents integrating and inverse response with dead time and a highly dependent response associated with the operating power variability, this work considers process identification like an optimization problem. Hence, parallel processing algorithms such as particle swarm optimization are used. The performance achieved with the new proposal is suitable for set-point tracking and disturbance rejection.

Multiple Spacecraft Formation Flying Control around Artificial Equilibrium Point Using Propellantless Approach

This paper demonstrates a detailed analysis of the feasibility for compact formation system around an L2-type artificial equilibrium point by means of continuous low-thrust propulsion in the hybrid form of solar sail and Coulomb force propulsion. Firstly, in view of non-ideal solar sail, the position of L2-type artificial equilibrium point and numerical periodic orbits around L2 utilized as leader’s nominal trajectory are given. Secondly, considering the external disturbances in the deep space environment, the nonlinear dynamic model of the spacecraft formation system based on the circular restricted three-body problem (CRTBP) is derived, under the assumption that the leader covers the nominal trajectory and each follower adjusts its propulsive acceleration vector (that is, both its sail attitude and electrostatic charge) in order to track a desired relative trajectory. Thirdly, based on a new double power combination function reaching law, a fast integral terminal sliding mode control methodology (MFITSM) is ameliorated to achieve orbital tracking rapidly, which has better robustness against external disturbances and the buffeting effect during spacecraft propulsion simultaneously. To properly allocate control inputs, a novel optimal allocation scheme is designed to calculate the charge product of the spacecrafts and sail attitude angles, which can make the magnitude of the acceleration required from the Coulomb propulsion system minimum and avoid formation geometry instabilities by balancing electrostatic interaction between adjacent spacecraft. Finally, several numerical examples are conducted to validate the superiority of the proposed control algorithm.

Barrier function-based adaptive nonsingular sliding mode control of disturbed nonlinear systems: A linear matrix inequality approach

In this study, a novel barrier function-based adaptive non-singular terminal sliding mode control methodology is suggested for robust stability of disturbed nonlinear systems. It is proved that the barrier function-based control method can force the state trajectories to converge to a region near origin in the finite time. A sufficient criterion is derived using Lyapunov stability theorem and linear matrix inequalities (LMIs) to satisfy the asymptotic stability of state trajectories. In addition, the design eliminates the necessity to have any knowledge about the upper bounds of external disturbances; a common requirement in sliding mode control implementation. The stability analysis verifies that the system states, under the designed control scheme, can asymptotically converge to a pre-defined region. Lastly, simulation studies are presented to confirm the efficacy and robustness of proposed approach.

Robust Output-Feedback Control for Spacecraft Proximity Operations With Forbidden Zone

This article seeks to address the robust output-feedback motion tracking control problem for spacecraft close-range proximity maneuvers under the influence of forbidden zone, external disturbances, and input saturation. First, two superquadric cuboids are constructed in the body-fixed frame of the target to represent the forbidden zone in final proximity. Then, an adaptive output-feedback control scheme is proposed under the framework of extended state observer technique and sliding mode control methodology. The presented scheme can achieve concurrent position and attitude tracking without prior information of the velocity-level states, and avoid any unwanted collisions between the two spacecraft. Finally, simulation scenarios are investigated to show the effectiveness of the proposed control scheme.

Intelligent fuzzy logic-based sliding mode control methodologies for pick and drop operation of robotic manipulator

Intelligent fuzzy logic-based sliding mode control methodologies for pick and drop operation of robotic manipulator

Intelligent fuzzy logic-based sliding mode control methodologies for pick and drop operation of robotic manipulator

Intelligent fuzzy logic-based sliding mode control methodologies for pick and drop operation of robotic manipulator

Three-dimensional time-varying sliding mode guidance law against maneuvering targets with terminal angle constraint

This paper deals with the problem of intercepting maneuvering targets with terminal angle constraints for missiles subjected to three-dimensional non-decoupling engagement geometry. To achieve the finite-time interception and satisfactory overload characteristics, a time varying sliding mode control methodology is developed based on a time base generator function. The main feature of the proposed guidance law guarantees the Line-of-Sight (LOS) angles to converge to small neighborhoods of the desired values at the interception time. First, a fractional power extended state observer is used to estimate the unknown target acceleration, which can significantly reduce the adaptive switching gain. The fractional power extended state observer enjoys the advantage of better noise tolerance. Then, a newly designed sliding mode surface is constructed by introducing a time base generator function and the time-varying sliding mode guidance law is developed based on this time-varying sliding surface. The proposed guidance law significantly reduces the overload magnitudes. Numerical simulations are carried out to verify the performance of the proposed guidance law.

Practical finite time vibration suppression of mechatronic systems using proportional–integral–derivative variable structure controls with dead-band nonlinearity

Vibration is an intrinsic phenomenon in many mechanical and mechatronic applied devices and undesirable vibration can either degrade the performance of the system or lead to unpredictable outputs. The main purpose of this article is to introduce a novel second-order proportional–integral–derivative sliding mode control methodology to suppress the undesirable vibrations of a class of applied dynamical systems with applications to mechatronic and mechanical devices. After designing a nonlinear proportional–integral–derivative terminal sliding manifold, rigorous mathematics are provided to guarantee that the origin is a practical finite time stable equilibrium point. Consequently, two efficient control laws are proposed to ensure the occurrence of the sliding motion with and/or without system unknown parameters. Motivated by situations encountered in practice, unknown lumped uncertainties are also added to the system and their impacts are tackled using adaptive control techniques. Furthermore, a hard nonlinear dead-band function is utilized in the control input and its effects such as lags and delays appeared on the control signals as well as on the system outputs are dealt with by the proposed proportional–integral–derivative variable structure controller. The proposed second-order variable structure controller not only utilizes the simple effective design approach of the proportional–integral–derivative controllers to ensure a reasonable transient performance, but also displays fast convergence properties demonstrated in non-singular terminal sliding modes. Finally, through simulation studies, it is confirmed that the proposed control strategy is effective in vibration attenuation of microelectromechanical resonators.

Fixed-Time Adaptive Robust Synchronization with a State Observer of Chaotic Support Structures for Offshore Wind Turbines

The chaotic support structures for offshore wind turbines are often subjected to a severe environment. A robust control scheme needs to be considered to maintain them in a safe operational limit. Robust sliding mode control (SMC) scheme can provide an excellent robust controller against this severe and challenging environment for these chaotic structures. This paper proposes a novel fixed-time adaptive sliding mode control scheme with a state observer to synchronize chaotic support structures for offshore wind turbines in the presence of matched parametric uncertainties. The proposed controller is a new integration of adaptive control concept, SMC method, fixed-time stability concept and a state observer. A fixed-time stability concept is used to provide stability for the system within a presented time regardless of initial conditions. The adaptive concept is utilized to provide an online estimator of the uncertain upper bound. Also, a nonlinear observer is employed to provide an online estimator of an unmeasured state in the controller. Lyapunov stability theorem is used to analyze fixed-time stability of the system based on SMC methodology. The simulation results demonstrate that the proposed controller is able to ensure fixed-time synchronization along with providing precise means to estimate the unmeasured state as well as uncertainty upper bound.

Twofold Sliding Controller Design for Uncertain Switched Nonlinear Systems

This paper deals with the problem of controller design for normal nonlinear switched systems with unknown dynamics. The situation assumes that the nonlinear component of the system dynamics is unknown and there are extra uncertain terms and external perturbations affecting the system responses. Unlike previous methods that usually apply artificial neural networks to obtain an approximate model for an unknown dynamics, we use simple adaptive laws to surmount such fluctuations as well as to circumvent the steady state errors in the approaches provided by neural networks or fuzzy logics. No information on the bounds and parameters of the uncertain parts is needed. We design a twofold sliding mode control methodology to stabilize the whole switched system with arbitrary switching signals. To handle the consequences of the inherent chattering, a smooth integral type control signal is constructed. It is proved that once the system states attain the developed sliding manifold, the system becomes insensitive to both the lumped uncertainties and the dynamics of the switched system. The common assumption of a known Lyapunov functions for the subsystems is relaxed and the derived adaptive approach provides nonconservative circumstances for guaranteeing the global stability of the equilibrium state. The theoretical results of this paper are generalized for the canonical nonlinear systems with mismatched uncertainties and a novel adaptive sliding manifold is proposed to suppress the effects of the system mismatching uncertain parts. A comparative computer simulation is developed to examine the effective performance of the introduced controllers.

Minimax sliding mode control design for linear evolution equations with noisy measurements and uncertain inputs

Abstract We extend a sliding mode control methodology to linear evolution equations with uncertain but bounded inputs and noise in observations. We first describe the reachability set of the state equation in the form of an infinite-dimensional ellipsoid, and then steer the minimax center of this ellipsoid toward a finite-dimensional sliding surface in finite time by using the standard sliding mode output-feedback controller in equivalent form. We demonstrate that the designed controller is the best (in the minimax sense) in the class of all measurable functionals of the output. Our design is illustrated by two numerical examples: output-feedback stabilization of linear delay equations, and control of moments for an advection–diffusion equation in 2D.

A nonlinear observer-based adaptive robust control approach for a class of uncertain asymmetric hysteretic systems

This article presents a robust control scheme for a class of asymmetric hysteretic systems with both parametric uncertainties and external disturbances, where an asymmetric Bouc–Wen model is adopted to represent the hysteretic behavior. A novel adaptive non-singular terminal sliding mode control methodology with hysteretic state estimation is proposed to achieve finite-time stabilization of such systems for vibration suppressions. In the proposed control framework, a hysteresis observer is constructed to capture the unmeasurable hysteretic force, and the adaptive control technique is used to accommodate the hysteretic uncertainties and unknown system parameters. Moreover, a fast terminal sliding mode controller without the singularity problem is designed to improve the robustness and dynamic performance of such systems, where the terminal sliding mode function is proposed to guarantee the finite-time convergence of the system states, and the reaching law with fractional power is constructed to accelerate the occurrence of the corresponding terminal sliding mode surface. Meanwhile, the finite-time stability of the whole closed-loop system is also analyzed. Finally, numerical simulation results deployed on a magnetorheological elastomer vibration isolation system are provided to validate the effectiveness of the proposed control algorithm.

Modeling and design of the improved D-STATCOM control for power distribution grid

The distribution static compensator (D-STATCOM) is a power quality compensator, which can be utilized for improving the power quality of the distribution power grid by managing the flow of reactive power and unbalanced caused by variable and unbalanced loads. This paper develops the concept of regulating the D-STATCOM scheme to improve the dynamic proficiency of the power distribution network during electrical network defects, such as voltage drops and voltage swells. Furthermore, the methodology adopted in this research paper is established to utilize the sliding mode control (SMC) for the proper working of D-STATCOM. The simulation of the suggested SMC methodology has been carried out by employing the MATALB/Simulink software and compared the results with traditional proportional integrator regulator. The results show that the suggested approach controlling the D-STATCOM achieves sinusoidal and symmetrical grid current with less harmonics; moreover, it can efficiently eliminate the oscillations produced in active and reactive power. Hence, the proposed strategy is helpful in mitigating the voltage flicker and improving the overall efficiency of the distribution grid.

Exploiting Parallel Computing to Control Uncertain Nonlinear Systems in Real-Time

Control is a critical element in many applications and research such as experimental testing in real-time. Linear approaches for control and estimation have been widely applied to real-time hybrid simulation (RTHS) techniques in tracking the physical domain (plant). However, nonlinearities and highly uncertainties of the plant impose challenges that must be properly addressed using nonlinear control procedures. In this study, a controller is developed for such an uncertain nonlinear system by integrating a robust control approach with a nonlinear Bayesian estimator. A sliding mode control methodology synthesizes the nonlinear control law to provide stability and accurate tracking performance, and a particle filter algorithm estimates the full state of the plant using measured signals such as displacement. The Hybrid Simulation Management (HSM) code is developed to implement dynamic systems and the improved nonlinear robust controller. The HSM is integrated in a novel run-time substrate named CyberMech, which is a platform developed to enhance the performance of real-time cyber-physical experiments that supports parallel execution. A set of experiments with a highly uncertain nonlinear dynamic system demonstrates that the combination of advanced control techniques and high performance computation enhances the quality of real-time experimentation and potentially expands RTHS techniques capabilities.