Adaptive Terminal Sliding Mode Control of Hyper-Chaotic Uncertain 4-Order system with One Control Input

In recent decades, controller design has been attracted a great deal of interest of many researchers in control community which can make the job of many other researchers in different area of research easier. The present study aims to design a finite time adaptive control input for a high-order nonlinear system in presence of a variety of mismatched uncertainties and external disturbances. Adaptive terminal sliding mode control (ATSMC) method is used to design robust controller in a finite time. Also, adaptive concept is employed in ATSMC to estimate the upper bound of mismatched uncertainties and external disturbances and their estimations are used in control input. The finite time stability proof is performed by defining a proper candidate Lyapunov function. Numerical simulation results are carried out in Simulink/MATLAB to reveal the correctness of proposed design in this research. Finally, the performance criterion, integral of the square value (ISV), is defined to provide a numerical comparison between the proposed adaptive controller and non-adaptive controller.

We propose a novel data‐driven model‐free adaptive terminal sliding mode control (SMC) for a class of discrete nonlinear systems with perturbations in which tracking error constraints are taken into account in improving tracking accuracy. The goal of this design is that the tracking error trajectory is maintained within the prescribed convergence region which is defined by the performance function, while the disturbances exist. In explaining the advantage of this proposed control scheme, at first, by theoretical calculation, it is proved theoretically that the quasi‐sliding mode can be achieved in a limited time under the specified tracking performance. Furthermore, comparative investigation results are given to validate the effectiveness of the proposed control scheme. Simulation results show that the proposed strategy is superior to model‐free adaptive control, model‐free adaptive terminal SMC, and data‐driven adaptive SMC with prescribed performance control algorithms in terms of tracking accuracy and response speed, which demonstrates the efficiency of the proposed scheme.

This paper presents a robust adaptive sliding mode control strategy using radial basis function (RBF) neural network for a kind of value controlled asymmetric cylinder electro-hydraulic servo system of an ammunition transfer arm in the presence of uncertain nonlinearity and parameter uncertainty. On the premise of setting the expected trajectory, using RBF neural networks to approximate unknown parameters, by setting appropriate neural network parameters and adaptive terms, the change trend of position parameter was estimated. The stability of close loop system is verified by the Lyapounov theory. Compared with the simulation results of PID control method and expected trajectory, RBF Neural Net sliding mode control method has smaller system tracking error, faster response and better tracking performance.

This paper aims to design a control input by using of adaptive terminal sliding mode control (ATSMC) method to ensure finite time stability for single input-multi output (SIMO) fuzzy system with T-S model at the same time by estimate unknowns and external disturbances upper bounds. The upper bound of the uncertainties and external disturbances is assumed to be unknown, which is estimated by using adaptive laws. The advantages of this method are robustness against uncertainties and external disturbances and guarantee finite time stability. The control strategy is designed and simulated on a ball and plate system in Simulink/MATLAB to show correctness of the suggested method.

In recent years, there has been a significant focus on synchronous reluctance motors (SynRM) owing to their impressive efficiency and absence of magnetic material. Although the SynRM shows great potential for use in electric vehicles, its widespread adoption is limited by unmodeled dynamics and external disturbances. Moreover, the uncertainty factor significantly restricts SynRM's peak efficiency and superior control performance, leading to an unjustifiable current loop reference command. To address these issues, this work presents various new research contributions which focus on the robust control of SynRM to optimize performance through the novel reaching law-based sliding mode control. Initially, a novel advanced sliding mode control reaching law (ASMCRL) with adaptive gain is proposed, to enhance the acceleration of the system state reaching the sliding surface. After that, an extended state observer (ESO) is designed to estimate and compensate for the overall disturbances of the system. Finally, the ASMCRL and ESO are integrated to design two nonlinear controllers namely, the disturbance-rejection sliding mode controller (DRSMC) and the disturbance-rejection sliding mode speed regulator (DRSMSR) for SynRM. The proposed DRSMSR eliminates the steady-state error and eradicates inherent chattering in DRSMC. Moreover, this yields a system trajectory that converges to a predetermined proximity of the sliding surface, irrespective of any lumped disturbances. The steady-state error of DRSMSR is less as compared to DRSMC. Furthermore, the speed response of this technique is 22.62% faster as compared to the state-of-the-art finite-time adaptive terminal sliding mode control. Additionally, the asymptotic stability of the proposed system is validated using Lyapunov's theorem. Thus the experimental results demonstrate the effectiveness and robustness of the proposed approach.

In this paper, the problem of the robust optimal control (ROC) for a class of nonlinear systems with uncertainties and external disturbances is studied. For this purpose, the State Dependent Riccati Equation (SDRE) is considered as a solution of the ROC. The proposed method is to transform a robust control problem into an optimal control problem, where the uncertainties and disturbances are reflected in the performance index. Hence, the performance index is selected as an energy function and using the proposed constraints in this paper the Lyapunov stability for this class of nonlinear systems is proved and the robust optimal controller is designed. In order to illustrate the high capability of the ROC method in optimal control of complex systems such as Hyper-chaotic system, the time response of state variables in the proposed method and the Global Robust Optimal Sliding Mode Control (GROSMC) method are compared together. The simulation results show that the time response of state variables in the ROC method is more sufficient than the GROSMC method.

To deal with complex disturbances and the presence of partial loss of propeller effectiveness in work-class remotely operated vehicles (ROVs), a method of robust fault tolerant control is proposed, which is based on adaptive sliding mode control. In this approach, adaptive technique is employed to estimate the bounds’ information of external complex disturbances and the effectiveness loss of the propeller. And a sliding mode controller is then designed to achieve fault tolerant control and external disturbance rejection. Corresponding stability of the closed-loop control system is analyzed using Lyapunov stability theory. Apply this method to trajectory tracking control of work-class ROVs, the simulation results validate that great fault tolerant capability and a good performance of external disturbance rejection can be achieved even under partial loss of propeller effectiveness.

This paper investigates finite-time attitude tracking control strategies for hypersonic flight vehicles (HFVs) with parameter uncertainties, external disturbances, and actuator saturations by applying sliding model control, adaptive mechanism, and nonlinear disturbance observer techniques. A nonlinear dynamic model of HFV attitude system in reentry flight phase is established. Then, a basic attitude control method of the HFV system is designed based on a terminal sliding mode control (TSMC) scheme to accommodate the system-lumped disturbance torques and guarantee the finite-time stability. To relax the prior knowledge of bounded lumped disturbance of the TSMC-based HFV attitude system, an adaptive TSMC (ATSMC) scheme is proposed. In order to relax the limit of compound uncertainties and attenuate chattering phenomenon of the TSMC-based HFV attitude system, a nonlinear disturbance observer-based TSMC (DO-TSMC) scheme is presented, which enhances the disturbance attenuation and robust tracking performance. Finally, simulation results of a generic X-33 nonlinear model exhibit the effectiveness of the proposed TSMC, ATSMC, and DO-TSMC schemes.

Two-Wheeled Self-Balancing Robots are widely used in various fields today. These systems have a highly unstable nature due to their underactuated structures. On the other hand, parameter uncertainties and external disturbances significantly affect their control performance. The best way to deal with parameter uncertainties that can easily lead controllers to instability is to use robust control methods. Dealing with these uncertainties is particularly crucial in control of underactuated and unstable systems such as Two-Wheeled Self-Balancing Robots. In this study, trajectory tracking control of a two wheeled self-balancing robot by using Sliding Mode Control (SMC) was realized. The chattering problem inherent in the SMC method was eliminated by employing tangent hyperbolic (tanh) switching function instead of signum function. The performance of the SMC controller has been examined under five different cases including external disturbance and various parameter uncertainties and compared with PID and LQR methods. The results showed that the SMC method is much more insensitive to parameter changes than the PID and LQR methods. It has also been observed that all three controllers maintain their stability against disturbance inputs, but the SMC method offers a better control performance.

The depth tracking issue of underactuated autonomous underwater vehicle (AUV) in vertical plane is addressed in this paper. Considering the complicated dynamics and kinematics model for underactuated AUV, a more simplified model is obtained based on assumptions. Then a nonlinear disturbance observer (NDO) is presented to estimate the external disturbance acting on AUV, and an adaptive terminal sliding mode control (ATSMC) based on NDO is applied to enhance the depth tracking performance of underactuated AUV considering both internal and external disturbance. Compared with the traditional sliding mode controller, the static error and chattering problem of the depth tracking process have been clearly improved by adopting NDO-based ATSMC. The stability of control system is proven to be guaranteed according to Lyapunov theory. In the end, simulation results imply that the proposed controller owns strong robustness and satisfied control effectiveness in comparison with the traditional controller.

PurposeThe purpose of this paper is to achieve high-precision sliding mode control without chattering; the control parameters are easy to adjust, and the entire controller is easy to use in engineering practice.Design/methodology/approachUsing double sliding mode surfaces, the gain of the control signal can be adjusted adaptively according to the error signal. A kind of sliding mode controller without chattering is designed and applied to the control of ultrasonic motors.FindingsThe results show that for a position signal with a tracking amplitude of 35 mm, the traditional sliding mode control method has a maximum tracking error of 0.3326 mm under the premise of small chattering; the boundary layer sliding mode control method has a maximum tracking error of 0.3927 mm without chattering, and the maximum tracking error of continuous switching adaptive sliding mode control is 0.1589 mm, and there is no chattering. Under the same control parameters, after adding a load of 0.5 kg, the maximum tracking errors of the traditional sliding mode control method, the boundary layer sliding mode control method and the continuous switching adaptive sliding mode control are 0.4292 mm, 0.5111 mm and 0.1848 mm, respectively.Originality/valueThe proposed method not only switches continuously, but also the amplitude of the switching signal is adaptive, while maintaining the robustness of the conventional sliding mode control method, which has strong engineering application value.

In this paper, an adaptive fuzzy PI-sliding mode control (AFPISMC) is proposed for induction motor (IM) speed control. First, an adaptive sliding-mode controller (APISMC) with a proportional plus integral equivalent control action is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameters. The proposed control design uses the fuzzy logic techniques to dynamically control parameter settings of the SMC equivalent control action. The theoretical analyses for the proposed fuzzy PI sliding-mode controller are described in detail. Simulated results show that the proposed controller provides high-performance dynamic characteristics and is robust with regard to plant parameter variations and external load disturbance.

In this paper, a new robust position controller is proposed for Series Elastic Actuators (SEAs) by using Sliding Mode Control (SMC) and a second order Disturbance Observer (DOb). The latter estimates not only disturbances but also their first and second order successive derivatives. A simple yet efficient dynamic model of the position control system is derived by using the analogy of a two-mass-spring-damper system. It is of fourth order and suffers from collocated and non-collocated disturbances. The former is directly cancelled by feeding-back its estimation through control input. The latter is suppressed by treating the estimations of disturbances and their first and second order time derivatives in the design of the SMC-based robust position controller. By cancelling disturbances via their estimations, not only the robustness of the position control system is improved but also the control signal chattering is lowered. The proposed robust controller significantly improves the position control performance of SEAs by suppressing plant uncertainties and external disturbances, such as friction, backlash, inertia variation and load. The validity of the proposed robust position controller is verified by giving experimental results of an SEA.

Due to the large consumption and dispersed processing of food, therefore, the study of food processing robots have been widely concerned. The food processing robot control system is susceptible to the extreme dynamic characteristics and the influence of external disturbance parameters. Combining fuzzy theory with sliding mode control, Adaptive sliding mode control is proposed based on the theory of fuzzy, in order to improve control accuracy and stability. The simulation results show that compared with the conventional sliding mode control method, the control is not only the external disturbance and parameter perturbation with stronger adaptability and robustness, but also has fast dynamic response and good tracking performance. Key words-Food processing; fuzzy theory; adaptive sliding mode control; robustness

This contribution deals with an adaptive sliding mode control for a hybrid actuator consisting of a piezo, a mechanicacal and a hydraulic part that can be used for camless engine motor applications. The control structure comprises a feedforward controller and a sliding mode controller. The general approach of this actuator is to use the advantages of both systems, the high precision of the piezoelectric actuator and the force of the hydraulic part. In fact, piezoelectric actuators (PEAs) are commonly used for precise positioning, despite PEAs present nonlinearities, such as hysteresis, saturations, and creep. A sliding mode control is proposed and for deriving the structure of such a controller a Lyapunov approach is used. An adaptive self-tuning algorithm is realised. The conceived sliding mode control takes the hydraulic actuator in a resonance operating point which corresponds to the rotational speed of the engine. When the engine speed changes, the sliding mode controller adapts its parameter in a way that the resonance frequency of the controlled hydraulic part of the actuator changes and corresponds to the working frequency of the engine. The resulting controller is therefor totally self-tuning and robust with respect to the model parameter variation. Asymptotic tracking is shown using Lyapunov approach. Moreover, the proposed technique avoids a switching function for the calculation of the equivalent signal of the sliding mode controller. In this way the chattering problem is completely avoided. Simulations with real data of a camless engine are presented.