Sliding Mode Concept Research Articles

Automatic Gain Tuning for Robust PID Control Using Time-Delay Control

Auto-tuning of robust PID Control is presented. To this end, we propose the equivalence condition between the modified TDC using sliding mode concept and the PID controller in a discrete-time domain. To realize auto-tuning of the PID control gains, we have synergistically combined the sliding mode concept and adaptive control. The desired error dynamics is described by using sliding mode concept, and the adaptive gain dynamics is proposed using the sliding variable. A leakage term is used for the gain dynamics to cope with the noise effect. The gain automatically increases when the sliding mode error is large, and decreases when sliding mode error is relatively small. The tracking errors of the proposed method are almost identical compared with those of well-tuned constant gains. Consequently, auto-tuning of the gains for the PID controller is realized instead of manual tuning.

Advances of the smooth variable structure filter: square-root and two-pass formulations

The smooth variable structure filter (SVSF) has seen significant development and research activity in recent years. It is based on sliding mode concepts, which utilize a switching gain that brings an inherent amount of stability to the estimation process. In an effort to improve upon the numerical stability of the SVSF, a square-root formulation is derived. The square-root SVSF is based on Potter’s algorithm. The proposed formulation is computationally more efficient and reduces the risks of failure due to numerical instability. The new strategy is applied on target tracking scenarios for the purposes of state estimation, and the results are compared with the popular Kalman filter. In addition, the SVSF is reformulated to present a two-pass smoother based on the SVSF gain. The proposed method is applied on an aerospace flight surface actuator, and the results are compared with the Kalman-based two-pass smoother.

An adaptive nonlinear control strategy for a stand-alone permanent magnet synchronous generator driven by a variable speed wind turbine

This paper presents a simple control structure using rotor flux oriented vector technique for a stand-alone permanent magnet synchronous generator (PMSG) associated to PWM rectifier, PWM DC–DC converter and PWM inverter. The DC–DC converter feeding an electronic load is controlled to maintain the dc-bus voltage at a desired constant value. The isolated PMSG is assumed to be driven by a variable speed wind turbine. A sliding mode control strategy has been developed to regulate the direct axis current, ensure maximum power tracking issue as well dc-bus voltage regulation. The online estimation of the rotor flux using sliding mode concept is provided. The control and estimator stability analysis is based on Lyapunov theory. Simulation results, carried out in Matlab/Simulink software, are presented to demonstrate the effectiveness of the proposed control method when the control system operates under load variations and parameters uncertainties. The proposed adaptive control can be used in remote area where wind speed is low.

Adaptive Fast Terminal Sliding Mode Control of Magnetic Levitation System

Adaptive sliding mode control schemes are proposed for the control problem of a magnetic levitation system. Two control laws based on sliding mode concepts are developed to deal with this problem. For the first controller, an adaptive sliding mode controller is designed to control a magnetic levitation system. The other controller is also developed by combining a fast terminal sliding mode control method with an adaptive technique. Both controllers can guarantee finite-time reachability of a given desired position of a magnetic levitation system. The stability of the controlled system under presented controllers is proved by using the Lyapunov stability theorem. An example of a magnetic levitation system is given and simulation results are included to verify the performance of the proposed controllers.

Output feedback second order sliding mode control for spacecraft attitude and translation motion

This paper studies an output feedback control problem for spacecraft position and attitude control when uncertainties related to system parameters and external disturbances are present. Firstly, a new finite-time control law is designed using second order sliding mode concepts. In the presence of external disturbances and inertia uncertainties, the new control law provides finite-time convergence and high tracking precision. Secondly, a new sliding-mode-based filter is developed to estimate the first time derivatives of attitude and position in finite time. Instead of the translational and angular velocity variables, the estimated derivative values are used for the controller design. The proposed controller with this filter is an output feedback controller since translational and angular velocity measurements are not required. The closed-loop system under this controller is non-homogeneous and the stability is proven by using concepts of a strong Lyapunov function and Lyapunov stability theory. The trajectories of the closed-loop system can be controlled to converge to a ball centered at the origin that can be made as small as desired. Numerical simulations of position and attitude control of spacecraft are given to demonstrate the performance of the proposed controller and filter.

Adaptive robust controller based on integral sliding mode concept

ABSTRACTThis paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results.

Damping interarea oscillations in power systems using finite time terminal sliding mode control of the unified power flow controller

This paper presents a new nonlinear controller for unified power flow controller (UPFC) based on the Lyapunov's finite time terminal sliding mode concept. Further instead of controlling the direct and quadrature-axis currents of the series voltage source converter (VSC), the instantaneous real-and reactive power components are used as control variables. This mode of control dispenses the unmodelled dynamics of the VSC phase-locked loop system and produces a robust control for the active-reactive power, and dc voltage excursions. Computer simulation results are obtained for a variety of operating conditions for 3-machine 6-bus power system using the finite time terminal sliding mode control and the results are compared with a standard input-output feedback linearisation approach to validate the superiority of the proposed controller.

Artificial neural network training utilizing the smooth variable structure filter estimation strategy

A multilayered neural network is a multi-input, multi-output nonlinear system in which network weights can be trained by using parameter estimation algorithms. In this paper, a novel training method is proposed. This method is based on the relatively new smooth variable structure filter (SVSF) and is formulated for feed-forward multilayer perceptron training. The SVSF is a state and parameter estimation that is based on the sliding mode concept and works in a predictor---corrector fashion. The SVSF training performance is tested on three benchmark pattern classification problems. Furthermore, a study is presented comparing the popular back-propagation method, the extended Kalman filter, and the SVSF.

Automotive Internal-Combustion-Engine Fault Detection and Classification Using Artificial Neural Network Techniques

In this paper, an engine fault detection and classification technique using vibration data in the crank angle domain is presented. These data are used in conjunction with artificial neural networks (ANNs), which are applied to detect faults in a four-stroke gasoline engine built for experimentation. A comparative study is provided between the popular backpropagation (BP) method, the Levenberg–Marquardt (LM) method, the quasi-Newton (QN) method, the extended Kalman filter (EKF), and the smooth variable structure filter (SVSF). The SVSF is a relatively new estimation strategy, based on the sliding mode concept. It has been formulated to efficiently train ANNs and is consequently referred to as the SVSF-ANN. The accuracy of the proposed method is compared with the standard accuracy of the Kalman-based filters and the popular BP algorithms in an effort to validate the SVSF-ANN performance and application to engine fault detection and classification. The customizable fault diagnostic system is able to detect known engine faults with various degrees of severity, such as defective lash adjuster, piston chirp (PC), and chain tensioner (CT) problems. The technique can be used at any dealership or assembly plant to considerably reduce warranty costs for the company and manufacturer.

Robust Nonlinear Observer And Observer‐Backstepping Control Design For Surface Ships

AbstractA robust passive non‐linear observer, utilizing the sliding mode concept and acceleration feedback (AFB) technique, is developed for ships. The main advantage of the proposed observer is that it is robust and that it takes the Coriolis‐centripetal matrix (C‐matrix) into account. The observer reconstructs velocities of ships and bias from slowly varying environmental disturbances. It also filters out the noise and wave frequency data from measurements to protect the actuators from wear and excessive fuel consumption. The sliding mode technique is introduced to improve robust performance against neglected disturbances, uncertainties, and unmodeled dynamics. The acceleration feedback technique and coordinate transformation are used for reshaping the inertia matrix and removing the C‐matrix from the mathematical model. Then, the observer design and stability analysis become simpler. An output feedback controller using observer backstepping and the Lyapunov redesign technique is derived, and the global stability of the observer and observer‐controller system is shown by Lyapunov stability theory. A set of simulations was carried out to verify the performance of the proposed observer and controller.

Finite time control for MIMO nonlinear system based on higher-order sliding mode

Considering a class of MIMO uncertain nonlinear system, a novel finite time stable control algorithm is proposed based on higher-order sliding mode concept. The higher-order sliding mode control problem of MIMO nonlinear system is firstly transformed into finite time stability problem of multivariable system. Then continuous control law, which can guarantee finite time stabilization of nominal integral chain system, is employed. The second-order sliding mode is used to overcome the system uncertainties. High frequency chattering phenomenon of sliding mode is greatly weakened, and the arbitrarily fast convergence is reached. The finite time stability is proved based on the quadratic form Lyapunov function. Examples concerning the triple integral chain system with uncertainty and the hovercraft trajectory tracking are simulated respectively to verify the effectiveness and the robustness of the proposed algorithm.

Nonsingular terminal sliding mode based finite-time control for spacecraft attitude tracking

This paper studies finite-time attitude tracking control problem of a rigid spacecraft system with external disturbances and inertia uncertainties. Firstly, a new finite-time attitude tracking control law is designed using nonsingular terminal sliding mode concepts. In the absence and presence of external disturbances and inertia uncertainties, this controller can drive the attitude and angular velocity tracking errors to reach zero in finite time. Secondly, a finite-time disturbance observer is introduced to estimate the disturbance, and a composite controller is developed which consists of a feedback control based on nonsingular terminal sliding mode method and compensation term based on finite-time disturbance observer. Finite-time convergence of attitude tracking errors and the stability of the closed-loop system is ensured by the Lyapunov approach. Numerical simulations on attitude control of spacecraft are also given to demonstrate the performance of the proposed controllers.

Robust online roll dynamics identification of a vehicle using sliding mode concepts

This paper proposes a robust observer concept for joint estimation of system states and model parameters related to the roll dynamics of a vehicle. Using sliding mode concepts introduces robustness to parametric uncertainties and also allows reconstruction of the latter. These model parameters are of interest for vehicle dynamics assessment and estimation of the roll angle. A novel classification concept exploits these parameter estimates for assessing the roll dynamics. An additional benefit of the proposed method is the minimal requirement of measurement equipment as it only relies on cost-efficient angular rate and acceleration sensors. Evaluation of the framework is performed in simulations and real-world using an experimental vehicle.

Sliding Mode Control of Distributed Parameter Processes: Application to a Solar Power Plant

The theory of sliding mode control is applied to a solar power plant described by a system of hyperbolic partial differential equations. The method of characteristics is used to extend the sliding mode concepts for application to partial differential equations. The main purpose of the controller is to manipulate the oil flow rate to maintain the field outlet temperature around the desired reference value, and, at the same time, to attenuate the disturbances effects. Through simulations the method is shown to be effective in controlling a solar power plant under real disturbances data.

An adaptive solution for robust control based on integral high‐order sliding mode concept

SummaryA new high‐order sliding mode controller is proposed. The main features are gain adaptivity and the use of integral sliding mode concept. The gain adaptation allows a reduction of the chattering and gives a solution to control uncertain nonlinear systems whose the uncertainties/perturbations have unknown bounds. The concept of real high‐order sliding mode detector is introduced given that it plays a key role in the adaptation law of the gain. This new control approach is applied by simulation to an academic example to evaluate its efficiency. Copyright © 2014 John Wiley & Sons, Ltd.

Novel Model-Based Estimators for the Purposes of Fault Detection and Diagnosis

The interacting multiple model (IMM) strategy is particularly useful for systems that behave according to a number of different operating modes. In this strategy, each operating mode is described by a model and has its own filter. The filters are run in parallel, and an overall operating mode probability is calculated that provides an indication of the current operating regime of the system. The smooth variable structure filter (SVSF) is a relatively new estimation method based on the sliding mode concept, formulated in a predictor-corrector form. For systems with modeling uncertainties, the SVSF has shown to be more accurate and robust when compared with other methods such as the extended Kalman filter (EKF). A newer form of the SVSF makes use of a time-varying smoothing boundary layer (SVSF-VBL). This paper introduces new model-based estimators; based on the IMM strategy combined with the SVSF and SVSF-VBL, referred to as the IMM-SVSF and IMM-SVSF-VBL, respectively. The new strategies are applied to a type of aerospace actuator referred to as an electrohydrostatic actuator, which provides a comprehensive system for fault detection and diagnosis. The results are compared with the popular IMM-EKF strategy.

Switching Gain Reduction in Adaptive Sliding Mode Control for Rigid Spacecraft Attitude Maneuvers

This paper investigates the overadaptation problem in current adaptive sliding mode control (ASMC) for rigid spacecraft attitude maneuvers. The inertia matrix uncertainty and external disturbance are taken into account, and an adaptive scheme is employed for the switching gain calculation. A detailed analysis of existing ASMC design reveals the fact that the switching gain would be overestimated if the ASMC algorithm is developed in the framework of conventional sliding mode control (SMC), owing to the unrelated adaptation caused by initial tracking error. The global sliding mode concept of integral sliding mode control (ISMC) is exploited to solve such a problem. The advantages of the proposed strategy are twofold. First, a much smaller switching gain is generated as compared to conventional ASMC. Second, the resulting small switching gain would not slow down the system response. The advantages of the proposed strategy are verified by both theoretical analysis and simulation results.

An efficient control of rigid robotic manipulator with uncertainties using higher order sliding mode control

A robotic manipulator is a highly non-linear system with uncertainties. Sliding mode control provides a method for reliable tracking for such uncertain non-linear systems. In this work, we present an algorithm based on higher order sliding mode concept for tracking and finite time error convergence for articulated robotic manipulators.

Kalman filtering strategies utilizing the chattering effects of the smooth variable structure filter

The Kalman filter (KF) remains the most popular method for linear state and parameter estimation. Various forms of the KF have been created to handle nonlinear estimation problems, including the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). The robustness and stability of the EKF and UKF can be improved by combining it with the recently proposed smooth variable structure filter (SVSF) concept. The SVSF is a predictor–corrector method based on sliding mode concepts, where the gain is calculated based on a switching surface. A phenomenon known as chattering is present in the SVSF, which may be used to determine changes in the system. In this paper, the concept of SVSF chattering is introduced and explained, and is used to determine the presence of modeling uncertainties. This knowledge is used to create combined filtering strategies in an effort to improve the overall accuracy and stability of the estimates. Simulations are performed to compare and demonstrate the accuracy, robustness, and stability of the Kalman-based filters and their combinations with the SVSF.

Robust adaptive second-order sliding-mode control with fast transient performance

A robust adaptive second-order sliding-mode control scheme with finite reaching time is proposed for a class of uncertain non-linear systems. It is shown that the problem is equivalent to the finite-time stabilisation of a second-order input-output dynamics with bounded uncertainties. The controller is designed by using geometric homogeneity and adaptive sliding-mode concept. It contains two parts: one part achieves finite-time stabilisation of the second-order input-output dynamics without uncertainties; the other part rejects bounded uncertainties, and the upper bounds of uncertainties are not required to be known in advance. As a result, a finite-time convergent second-order sliding mode is established. The convergence rate of the second-order sliding mode can be hastened through tuning the controller parameters, and the robustness is ensured. The method is evaluated in simulations on an academic example.