Adaptive Sliding Mode Control Approach Research Articles

Stick–Slip Suppression in Drill String Systems Using a Novel Adaptive Sliding Mode Control Approach

A novel control technique is presented in this paper, which is based on a first-order adaptive sliding mode that ensures convergence in a finite time without any prior information on the upper limits of the parametric uncertainties and/or external disturbances. Based on an exponent reaching law, this controller uses two dynamically adaptive control gains. Once the sliding mode is reached, the dynamic gains decrease in order to loosen the system’s constraints, which guarantees minimal control effort. The proof of convergence was demonstrated according to Lyapunov’s criterion. The proposed algorithm was applied to a drill string system to evaluate its performance because such systems present variable operating conditions caused by, for example, the type of rock. The effectiveness of the proposed controller was evaluated by conducting a comparative study that involved comparing it against a commonly used sliding mode controller, as well as other recent adaptive sliding mode control techniques. The different mathematical performance measures included energy consumption. The proposed algorithm had the best performance measures with the lowest energy consumption and it was able to significantly improve the functioning of the drill string system. The results indicated that the proposed controller had 20% less chattering than the classic SM controller. Finally, the proposed controller was the most robust to uncertainties in system parameters and external disturbances, thus demonstrating the auto-adjustable features of the controller.

Tracking control of a flexible‐link manipulator based on an improved barrier function adaptive sliding mode

AbstractIn this paper, a novel controller designed for robust tracking control of a flexible‐link manipulator operating in the presence of parameter uncertainties and external disturbances within the joint space is introduced. The proposed controller employs an adaptive sliding mode control approach, incorporating an improved barrier function, to ensure that trajectory errors remain within predefined performance bounds. This design enhances the tracking performance without overestimating control‐switching gains. Additionally, a fixed‐time adaptive sliding mode control, featuring a rapid nonsingular terminal sliding mode variable, is introduced to expedite the convergence rate of the system state during the initial stages. The efficacy of the proposed control scheme is established through the Lyapunov method, demonstrating finite‐time convergence of the trajectory error to a specified neighborhood of zero. Experimental validation on a flexible‐link system supports the effectiveness and advantages of the proposed control strategy, as evidenced via comparisons with two existing adaptive control schemes.

Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment.

This study develops an adaptive sliding mode control approach for a drilling tool attitude adjustment system, aiming at solving the problems of model uncertainties and insufficient ability of disturbance suppression during the regulation behavior. To further improve the performance of the position-tracking loop in terms of response time, tracking accuracy, and robustness, a state observer based on an improved radial basis function is designed to approximate the model uncertainties, a valve dead-zone compensate controller is used to reduce control deviation, an adaptive sliding mode controller is designed to improve the position-tracking precision and attenuate sliding mode chattering. Finally, simulation and experimental results are carried out to verify the observability of the model uncertainties and position-tracking errors of the drilling tool attitude adjustment system, which can effectively improve the position-tracking performance and robustness of the drilling tool attitude adjustment system.

Nonlinear Robust Adaptive Sliding Mode Control Strategies Involve a Fractional Ordered Approach to Reducing Dengue Vectors

This study presents an innovative approach by integrating adaptive sliding mode control strategies with fractional order modeling to address the challenge of reducing Aedes aegypti mosquito populations, the primary vector of Dengue - a widespread and debilitating disease. By employing the Atangana-Baleanu-Caputo fractional operator to model the dynamics of the mosquito population, we achieve a more precise representation of complex and non-linear behaviors. The motivation behind adopting the Adaptive Sliding Mode Control (ASMC) approach lies in the critical need to efficiently control Aedes aegypti mosquito populations, a key step in combating the prevalence of dengue. The ASMC method dynamically adjusts control parameters based on evolving conditions, enhancing its adaptability to the changing dynamics of mosquito populations.The Lyapunov stability theorem ensures the reliability of tracking convergence and control structure. Additionally, we implement the Toufik Atangana method to solve both state and adjoint fractional differential equations using the ABC derivative operator. This incorporation adds a novel dimension to the study, providing a comprehensive framework for addressing the intricate dynamics inherent in the Aedes aegypti mosquito population. To assess the effectiveness of the proposed strategy, a numerical performance index is introduced at the end of the abstract. This index justifies the controller’s efficacy by comparing it to other conventional controllers. The inclusion of this quantitative measure reinforces the significance of the proposed strategy in the context of dengue prevention and control efforts.

Adaptive finite-time fault-tolerant control for nano-satellite attitude tracking under actuator constraints

In this paper, a finite-time fault-tolerant control method is developed for attitude tracking of a nano-satellite with three magnetorquers and one reaction wheel in the presence of actuator faults, inertia uncertainties, external distribution, and actuator constraints. For this purpose, the modified non-singular fast terminal sliding mode control is used due to the ability of robustness against uncertainties and finite-time convergence. In this approach, the modified sliding surface variable is constructed based on angular velocity and attitude error to converge the attitude error to zero in a finite time. In addition, three adaptive parameters are employed to reduce the adverse effect of uncertain expressions and to track the attitude commands with high control accuracy. The adaptive parameters and sliding surface variable are used in the reaching phase of the controller to decrease the chattering phenomenon. The dynamics of adaptive parameters, with regard to the angular velocities of the nano-satellite and reaction wheel and the sliding surface variable, are obtained during the stability proof of the closed-loop system. Also, the finite-time convergence of sliding surface and attitude variables are proved by the extended Lyapunov condition, and the convergence regions of attitude tracking errors are obtained. The simulations are accomplished and compared with an existing adaptive sliding mode control approach to evaluate the performance of the proposed controller. The results verify that the proposed controller performs better than the mentioned controller in terms of finite-time convergence, the accuracy of attitude tracking, and the reduction of the chattering phenomenon.

Novel finite-time adaptive sliding mode tracking control for disturbed mechanical systems

In this paper, the finite-time tracking control problem of mechanical systems subject to model uncertainties and external disturbances is investigated. A new type of finite-time adaptive sliding mode control approach is proposed based on a novel integral sliding mode surface and a novel parametric adaptation mechanism. The integral sliding mode surface is originally designed by utilizing the adding a power integrator technique. The parametric adaptation mechanism is developed by using a single adaptive updating law to estimate the square of the upper bound of the lumped uncertain term. As compared with the most existing studies, the distinctive features of the proposed controller are threefold. (1) Benefiting from the novel integral sliding mode surface, the proposed controller has no singularity problem inherently existing in the terminal sliding mode control. (2) Owing to the use of novel parametric adaptation mechanism, the proposed controller is smooth and the unexpected chattering phenomenon is significantly attenuated. Moreover, the proposed controller is structurally simple and requires relatively few online calculations, which makes it affordable for practical applications. (3) The practical finite-time stability of the overall closed-loop system is strictly proved. The proposed controller can ensure the position and velocity tracking errors stabilize to the adjustable small neighborhoods around the origin in finite time. Lastly, the effectiveness and advantages of the proposed control approach are illustrated through simulations and comparisons.

Optimization of Grid-Connected Photovoltaic Power Generation Technology Based on Nonlinear Back-Stepping Controller

To address the issue of energy scarcity and to use solar photovoltaic energy as a renewable source, a three-phase grid-connected photovoltaic inverter system with uncertain system model parameters is investigated, which converts DC power into AC power, feeds it into the grid, and maintains the grid-connected part’s quality. An enhanced back-stepping approach is proposed to explore the control strategy of three-phase solar grid-connected inverter, which includes adaptive control, dissipative theory, sliding mode control, and rapid terminal sliding mode control, respectively. It is verified that the system is subjected to external interference F = 5 during 0.5 s–0.8 s. As per the simulation results, the improved adaptive terminal sliding mode control method can suppress the interference to a certain extent and has strong robustness to the external interference. When compared with the adaptive sliding mode control approach, the anti-interference ability is better, and the system stability is improved. Then, to improve the above approach, a high speed terminal sliding mode control method is proposed, which can swiftly converge in finite time and the estimated value of uncertain parameters is closer to the actual value, thereby boosting the system’s robustness.

Adaptive sliding mode control with guaranteed performance based on monitoring and barrier functions

SummaryThis paper proposes a new adaptive sliding mode control approach via output feedback for a class of nonlinear systems. The sliding‐mode based controller can deal with parametric uncertainties and (un)matched disturbances with unknown upper bounds. Finite‐time convergence of the tracking error to a predefined neighborhood of the origin of the closed‐loop system is proved with guaranteed transient and steady‐state performance. Basically, the novelty of our result lies on combining two important adaptation tools: monitoring and barrier functions. The adaptation process is divided into two stages, where an appropriate monitoring function allows for the specification of performance criteria during the transient phase, while the barrier function ultimately confines the tracking error within a small residual set in steady state. Simulation results including an application to Anti‐lock Braking System illustrate the advantages of the proposed adaptive control strategy.

Human-robot skills transfer interface for UAV-based precision pesticide in dynamic environments

Purpose Nowadays, the global agricultural system is highly dependent on the widespread use of synthetic pesticides to control diseases, weeds and insects. The unmanned aerial vehicle (UAV) is deployed as a major part of integrated pest management in a precision agriculture system for accurately and cost-effectively distributing pesticides to resist crop diseases and insect pests. Design/methodology/approach With multimodal sensor fusion applying adaptive cubature Kalman filter, the position and velocity are enhanced for the correction and accuracy. A dynamic movement primitive is combined with the Gaussian mixture model to obtain numerous trajectories through the teaching of a demonstration. Further, to enhance the trajectory tracking accuracy under an uncertain environment of the spraying, a novel model reference adaptive sliding mode control approach is proposed for motion control. Findings Experimental studies have been carried out to test the ability of the proposed interface for the pesticides in the crop fields. The effectiveness of the proposed interface has been demonstrated by the experimental results. Originality/value To solve the path planning problem of a complex unstructured environment, a human-robot skills transfer interface is introduced for the UAV that is instructed to follow a trajectory demonstrated by a human teacher.

Linearized Bregman iteration based model‐free adaptive sliding mode control for a class of non‐linear systems

There is a growing demand for robust data-driven control methods particularly for industrial process control. This paper presents a new model-free adaptive sliding mode control approach for a class of discrete-time, multiple input and multiple output non-linear systems. The proposed methodology seeks to address issues with the computation of inverse matrices and problems with singularity in existing methods while at the same time seeking to enhance robustness. A Majorization–Minimization technique and the L1 norm are used within the proposed optimization and an online iterative approach is described for update of the control law. The closed-loop system response is proved to be stable. The effectiveness of the proposed control is validated by extensive simulation and also experimental results, with the performance obtained by the proposed approach being compared throughout with a well-known approach from the established literature.

Adaptive Finite-Time Control for Spacecraft Rendezvous under Unknown System Parameters

In this study, we investigated the sliding mode control (SMC) technology for the spacecraft rendezvous maneuver under unknown system parameters and external disturbance. With no knowledge of the mass and inertial matrix of the pursuer spacecraft, an adaptive SMC approach was devised using the hyperbolic tangent function to realize the control objective of reducing the chattering problem. In addition, the finite-time stability of the relative dynamics and the boundedness of the signals in the closed-loop system were derived under proposed method. The effectiveness and advantages of the proposed method were verified through theoretical analysis and numerical simulations.

Fuzzy neural network-based chaos synchronization for a class of fractional-order chaotic systems: an adaptive sliding mode control approach

This paper deals with chaos synchronization problem between two different uncertain fractional-order (FO) chaotic systems with disturbance based on FO Lyapunov stability analysis method. A T–S fuzzy neural network model as a universal approximator is constructed to approximate those uncertain terms and unknown parameters. An adaptive sliding mode control scheme is established, and the adaptive sliding mode control design procedure is proposed, which not only guarantees the stability and robustness of the proposed control method, but also guarantees that the external disturbance on the synchronization error can be attenuated. Finally, simulation results show applicability and feasibility of the proposed control strategy.

Adaptive sliding mode control of regenerative chatter and stability improvement in boring manufacturing process with model uncertainties

In the machining processes, vibration suppression is crucial in order to achieve the high precision as well as high-quality surface and increase of the material removal rate. In this paper, an adaptive sliding mode control approach is presented to supress the chattering phenomenon in the boring process in the presence of model uncertainties and unmodeled dynamics. The boring bar is modeled as a cantilever Euler–Bernoulli beam, which is actuated by a piezo-actuator located at the bar's end. As a more realistic model, the cutting tool is modeled as an added mass at the bar's end. In order to derive the equations of motion, mode summation method with inclusion the first three modes of vibration is applied. After formulation of the problem, an adaptive sliding mode control scheme is used and an effective control law is derived, which eliminates the chatter vibration. Moreover, a full state observer is designed to estimate three dominant modes of the boring bar. The simulation results demonstrate the effectiveness of the proposed control strategy against the model uncertainties and unmodeled dynamics. Also, it is observed that adaptive sliding mode control acts effectively in improving the stability lobes diagram. Consequently, after implementation of adaptive sliding mode control, more material removal rate can be obtained without stability loss.

Adaptive Neural Network-Based Backstepping Sliding Mode Control Approach for Dual-Arm Robots

The paper introduces an adaptive strategy to effectively control a nonlinear dual-arm robot under external disturbances and uncertainties. By the use of the backstepping sliding mode control (BSSMC) method, the proposed algorithm first allows the manipulators to be able to robustly track the desired trajectories. Furthermore, due to the nonlinear, uncertain and unmodeled dynamics of the dual-arm robot, it is proposed to employ the radial basis function network (RBFN) to adaptively estimate the robot’s dynamic model. Though the estimation of the dynamics is approximate, the adaptation law is derived from the Lyapunov theory, which provides the controller with ability to guarantee stability of the whole system in spite of its nonlinearities, parameter uncertainties and external load variations. The effectiveness of the proposed RBFN–BSSMC approach is demonstrated by implementation in a simulation environment with realistic parameters, where the obtained results are highly promising.

Neural network-based adaptive sliding mode control design for position and attitude control of a quadrotor UAV

In this paper, a novel method is suggested for the position and attitude tracking control of a quadrotor UAV in the presence of parametric uncertainties and external disturbance. The proposed method combines neural network adaptive scheme with sliding mode control, which preserves the advantages of the two methods. Firstly, dynamic model of quadrotor is divided into two fully actuated and under actuated subsystems. Secondly, sliding mode controllers are corresponding designed for each subsystem, and their coefficients in sliding manifolds are adaptively tuned by the neural network method. In each section, using Lyapunov theory, stability of closed loop system is proven.Finally, the method is examined for a square path tracking and a maximum overshoot of 7.5133% and a settling time 5.6648 s are obtained. By comparing the results obtained through different methods, it is concluded that the proposed controller provides the following main advantages: (1) good transient and steady state behaviors, (2) insensitivity to parameter variations, (3) disturbance rejection capability, and (4) remarkable stability and performance robustness. Hence, for operational purposes in which the fast and accurate response are of crucial importance, using the neural network-based adaptive sliding mode control approach is recommended.

An adaptive sliding mode actuator fault tolerant control scheme for octorotor system

In this article, an adaptive sliding mode control is used in the framework of fault tolerant control to mitigate the effects of actuator faults without requiring the actuator health information. Since unmanned aerial vehicles are being used in multiple fields such as military, surveillance, media, agriculture, communication and trading sector, therefore it is of vital importance to overcome the effects of actuator faults that can decline system performance and can even lead to some serious accidents. The proposed adaptive sliding mode control approach can handle actuator faults directly without requiring any faults information and adaptively adjusts controller gains to maintain acceptable level of performance. To validate the effectiveness of the proposed adaptive fault tolerant control scheme, it has been tested in simulations using non-linear Benchmark model of Octorotor system and its performance is compared with the optimal LQR control approach.

A novel adaptive sliding mode control approach for electric vehicle direct yaw-moment control

Direct yaw-moment control systems have been proven effective in enhancing vehicle stability and handling. The existing direct yaw-moment control designs commonly involve computation of tire side-slip angles, which is susceptible to measurement and estimation errors. The fixed control gain of the conventional sliding mode direct yaw-moment control design cannot adapt to variations and uncertainties in vehicle parameters. As a result, its robustness against parametric variations and uncertainties is limited. To improve the control performance, a novel adaptive sliding mode direct yaw-moment control approach is proposed in this article for electric vehicles with independent motors. The proposed method utilizes a varying control gain to adapt to the variations of front and rear tire side-slip angles. Comparative simulation results show that the proposed scheme outperforms the conventional method with inaccurate tire side-slip angle feedback. With the proposed direct yaw-moment control system on-board, the adverse effects of inaccuracies on tire side-slip angles are suppressed and the vehicle’s robustness against parametric variations and uncertainties is enhanced.

Unknown ground moving target tracking using multiple unmanned aerial vehicles

This paper investigates the problem of robust guidance law design for multiple unmanned aerial vehicles to achieve desired formation pattern for standoff tracking of an unknown ground moving target. The proposed guidance law consists of two main parts: relative range regulation and space angle control. For the first mission, a novel control law is proposed to regulate the relative distance between the unmanned aerial vehicle and the ground moving target to zero asymptotically based on adaptive sliding mode control approach. Considering the discontinuous property of the sign function, which is often used in traditional sliding mode control and will result in high-frequency chattering in the control channel, the proposed controller adopts the continuous saturation function for chattering elimination. Besides the continuous property, convergence to the origin asymptotically can be guaranteed theoretically with the proposed controller, which is quite different from traditional boundary layer technique, where only bounded motion around the sliding manifold can be ensured. For asymptotic stability, it is only required that the lumped uncertainty is bounded, but the upper bound may be unknown by virtue of the designed adaptive methodology. For space angle control, a new multiple leader–follower information architecture is introduced and an acceleration command is then derived for each unmanned aerial vehicle to space them about the loiter circle defined by the first controller. Simulation results with different conditions clearly demonstrate the superiority of the proposed formulation.

Adaptive sliding mode control approach

The main goal of the present research is to deal with two non-identical hyperchaotic master–slave systems based on an efficient adaptive sliding mode control algorithm, namely the adaptive sliding mode control approach. As long as both non-identical systems are synchronized, the systems mentioned need to be handled through the proposed control algorithm. Since the effect of the external disturbance and uncertainty may truly be ignored, the whole of the chosen states of the slave system should be followed by the corresponding states of the master system in a very careful manner. The proposed adaptive sliding mode control approach has been realized to cope with the synchronization error, in a reasonable amount of time, in order to drive the applicable hyperchaotic systems. Finally, the performance of the proposed control scheme is verified via the simulation results.

Smooth finite-time fault-tolerant attitude tracking control for rigid spacecraft

This paper investigates the problem of attitude tracking control for a rigid spacecraft subject to parametric uncertainties, external disturbances, actuator faults and actuator saturation constraints. By combining the finite-time passivity technique into adaptive sliding mode control approach, a novel smooth fault-tolerant control algorithm with finite time convergence is proposed. Then, the finite-time convergence of the relative attitude errors will be achieved by implementing the proposed smooth fault-tolerant controller, even under actuator faults and magnitude constraints. In particular, a solution to the unwinding phenomenon, arising from the usage of the redundant four-parameter attitude representation, is explored in the sense of finite-time passivity. Besides detailed controller design procedures and rigorous theoretical proofs of all related closed-loop finite-time stability, numerical simulation results are exhibited to demonstrate the effectiveness and superior control performance of the proposed control scheme.