Robust Adaptive Sliding Mode Control Research Articles

A Robust Adaptive Sliding Mode Control for PMLSM with Variable Velocity Profile Over Wide Range

An adaptive robust variable structure speed controller is designed for wide range of desired velocity control of a Permanent Magnet Linear Synchronous Motor (PMLSM). This is performed for comprehensive nonlinear model of PMLSM including non-idealities such as detent force, parameter uncertainty, unpredicted disturbance and nonlinear friction. The proposed method is based on the robust Sliding Mode Control (SMC) in combination with an adaptive strategy for a wide range of velocity. The simulation results are provided for the above mentioned comprehensive model of PMLSM with a variable velocity profile. Moreover, as an evaluation criterion, a Proportional-Integral (PI) controller is designed whose parameters are optimally tuned by the Particle Swarm Optimization (PSO) algorithm for better comparison.

Synchronization and circuit design of a chaotic system with coexisting hidden attractors

This paper investigates an unusual example of a three- dimensional dissipative chaotic flow with quadratic nonlinearites in which there is no equilibrium. This system belongs to a newly introduced category of chaotic systems: systems with hidden attractors which have important and potentially problematic engineering consequences. It is more interesting when we show there are coexisting hidden attractors for some range of parameters. We investigate this system through some analysis, circuit design and finally we use it as a benchmark for synchronization using a Robust Adaptive Sliding Mode Control (RASMC). This synchronization is performed through a nonlinear controller based on Lyapunov Stability Theory to stabilize the error dynamics.

Multivariable robust adaptive sliding mode control of an industrial boiler–turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller

To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler–turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler–turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input–output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions.

Robust adaptive sliding mode control of a photovoltaic water pumping system using fuzzy wavelet network and PSO algorithm

This paper presents a novel method that combines fuzzy wavelet network with sliding mode control (FWNSM) to track the maximum power point (MPPT) for a photovoltaic pumping system. For the best use, the photovoltaic (PV) generator must operate at its maximum power point (MPP). Traditional sliding mode control (SMC) can be used to achieve the robust tracking. However, in the presence of large uncertainties the SMC produces the chattering phenomenon due to the higher needed switching gain. In order to reduce this gain, fuzzy wavelet network (FWN) is used for the estimation of model unknown parts and hence enable a lower switching gain to be used. This FWN is trained online using the back-propagation (BP) algorithm. A second robust control term is added to compensate the FWN errors. Particle swarm optimisation (PSO) algorithm is used in this study to optimise the learning rate of BP algorithm in order to improve the network performance in term of the speed of convergence. The stability and effectiveness of the proposed method are proved by Lyapunov method and the simulations are given to demonstrate the performance of the proposed approach by the comparison with traditional SMC.

Adaptive robust control of fully-constrained cable driven parallel robots

In this paper, adaptive robust control (ARC) of fully-constrained cable driven parallel robots is studied in detail. Since kinematic and dynamic models of the robot are partly structurally unknown in practice, in this paper an adaptive robust sliding mode controller is proposed based on the adaptation of the upper bound of the uncertainties. This approach does not require pre-knowledge of the uncertainties upper bounds and linear regression form of kinematic and dynamic models. Moreover, to ensure that all cables remain in tension, proposed control algorithm benefit the internal force concept in its structure. The proposed controller not only keeps all cables under tension for the whole workspace of the robot, it is chattering-free, computationally simple and it does not require measurement of the end-effector acceleration. The stability of the closed-loop system with proposed control algorithm is analyzed through Lyapunov second method and it is shown that the tracking error will remain uniformly ultimately bounded (UUB). Finally, the effectiveness of the proposed control algorithm is examined through some experiments on a planar cable driven parallel robot and it is shown that the proposed controller is able to provide suitable tracking performance in practice.

Robust Adaptive Trajectory Tracking Sliding mode control based on Neural networks for Cleaning and Detecting Robot Manipulators

This paper proposes an robust adaptive control method based on Radial Basis Function Neural networks (RBFNN) to investigate the joint position control for periodic motion and predefined trajectory ...

Effective Torque Ripple Compensation in Feed Drive Systems Based on the Adaptive Sliding-Mode Controller

Rotary or linear permanent magnet servo motor systems are widely used in mechatronics applications. When used in direct-drive configuration without any mechanical transmission, one of the bottlenecks in achieving precision positioning is the rejection of torque ripples, which are in the form of high-frequency harmonic disturbances varying with the operating condition of the servos. When attached to mechanical transmission, ripple disturbances occur due to misalignments, repetitive contact, or the process forces itself. In this paper, a robust adaptive sliding-mode control is proposed to reject harmonic disturbances in servo systems and attain accurate positioning. The overall sliding-mode control law is derived from the Lyapunov function without the switching condition allowing convenient implementation in a PID-like form. Effectiveness of the controller is demonstrated experimentally, where the ripple forces that occur due to mechanical contact in spur and worm-gear feed drive servo systems are compensated successfully.

The improved results with Mathematica and effects of external uncertainty and disturbances on synchronization using a robust adaptive sliding mode controller: a comparative study

In this computational article, the improved results when different chaotic systems are synchronized using robust adaptive sliding mode controller (RASMC) has been presented in which the simulation is based on Mathematica as well as the effects of external uncertainties (EU) and external disturbances (ED) have been studied in the synchronization of two different chaotic systems. For the same pairs (master and slave systems) of considered chaotic systems (Lorenz, Chen and Liu) and implemented technique (RASMC), a comparative study has been done between the results obtained using Mathematica and MATLAB, as well as the effects of EU and ED on the convergence of synchronization have been studied.

Robust adaptive sliding mode control based on wavelet kernel principal component for offshore steel jacket platforms subject to nonlinear wave-induced force

This paper is concerned with adaptive integral sliding mode control (AISMC) based on a wavelet kernel support vector machine for offshore steel jacket platform subject to nonlinear wave-excited force and parameter perturbations. The sliding mode control technique is combined with adaptive control algorithm and wavelet support vector machine to achieve the desired attenuation on the wave-induced vibration and to limit the displacement of offshore platforms. In this method, wavelet kernel support vector machine is used to establish the adaptive controller and an on-line learning rule for the weighting vector and bias is derived. The most important feature of the proposed control strategy is its inherent robustness and its ability to handle the nonlinear behavior of the offshore platform. By means of this control scheme the performance of the AISMC has been improved. The performance of the proposed control strategy is compared with some existing control schemes. It is demonstrated that the proposed control scheme in this paper is more effective in improving the control performance of the offshore platform. This controller is designed based on solving a set of linear matrix inequalities. It has been illustrated through simulation results that the proposed control scheme is effective in improving the control performance of offshore platforms.

Robust Adaptive Fuzzy Sliding Mode Control Based on Fuzzy Compensation for Ammunition Auto-loading Robot

Aimed at the problems of low control accuracy and weak robustness influenced by external disturbance, friction, load changes, modeling errors and other issues in ammunition auto-loading robot control system, a new robust adaptive fuzzy sliding mode controller based on fuzzy compensation is proposed. The control architecture employs fuzzy systems to compensate adaptively for plant uncertainties to distinguish different disturbance compensation terms and approximate each of them respectively. The stability of the robust adaptive fuzzy sliding mode control (SMC) and the convergence of the tracking errors are ensured by using the Lyapunov theory. By analyzing and comparing the simulation results, it is obviously shown that the control system can lighten the effect on the control system caused by different disturbance factors and eliminate the system chattering instead of traditional SMC. As a result, the control system has great dynamic features and robust stability and meets the requirement that the actual motion of ammunition auto-loading robot quickly tracks the scheduled trajectory. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4342

Robust adaptive sliding mode control of MEMS gyroscope using T–S fuzzy model

In this paper, a multi-input multi-output Takagi–Sugeno (T–S) fuzzy model is proposed to represent the nonlinear model of micro-electro mechanical systems (MEMS) gyroscope and improve the tracking and compensation performance. A robust adaptive sliding mode control with on-line identification for the upper bounds of external disturbances and an adaptive estimator for the model uncertainty parameters are proposed in the Lyapunov framework. The adaptive algorithm of model uncertainty parameters could compensate the error between the optimal T–S model and the designed T–S model, and decrease the chattering of the sliding surface. Based on Lyapunov methods, these adaptive laws can guarantee that the system is asymptotically stable. For the purpose of comparison, the designed controller is also implemented on the nonlinear model of MEMS gyroscope. Numerical simulations are investigated to verify the effectiveness of the proposed control scheme on the T–S model and the nonlinear model.

PWM-based adaptive sliding mode control for the boost converter with unknown parameters

In this paper, a pulsewidth modulation (PWM) based robust adaptive sliding mode control (SMC) is designed for a boost converter subject to unknown parameters. An estimator is used to design the adaptation laws to estimate the converter parameters. The controller designed tightly regulates the output voltage despite the unknown parameters. The robustness of this controller is validated experimentally and tested against large input voltage variations and step load changes.

Adaptive Robust Sliding Mode Vibration Control of a Flexible Beam Using Piezoceramic Sensor and Actuator: An Experimental Study

This paper presents an experimental study of an adaptive robust sliding mode control scheme based on the Lyapunov’s direct method for active vibration control of a flexible beam using PZT (lead zirconate titanate) sensor and actuator. PZT, a type of piezoceramic material, has the advantages of high reliability, high bandwidth, and solid state actuation and is adopted here in forms of surface-bond patches for vibration control. Two adaptive robust sliding mode controllers for vibration suppression are designed: one uses a discontinuous bang-bang robust compensator and the other uses a smooth compensator with a hyperbolic tangent function. Both controllers guarantee asymptotic stability, as proved by the Lyapunov’s direct method. Experimental results verified the effectiveness and the robustness of both adaptive sliding mode controllers. However, from the experimental results, the bang-bang robust compensator causes small-magnitude chattering because of the discontinuous switching actions. With the smooth compensator, vibration is quickly suppressed and no chattering is induced. Furthermore, the robustness of the controllers is successfully demonstrated with ensured effectiveness in vibration control when masses are added to the flexible beam.

Attitude Analysis and Robust Adaptive Backstepping Sliding Mode Control of Spacecrafts Orbiting Irregular Asteroids

Attitude stability analysis and robust control algorithms for spacecrafts orbiting irregular asteroids are investigated in the presence of model uncertainties and external disturbances. Rigid spacecraft nonlinear attitude models are considered and detailed attitude stability analysis of spacecraft subjected to the gravity gradient torque in an irregular central gravity field is included in retrograde orbits and direct orbits using linearized system model. The robust adaptive backstepping sliding mode control laws are designed to make the attitude of the spacecrafts stabilized and responded accurately to the expectation in the presence of disturbances and parametric uncertainties. Numerical simulations are included to illustrate the spacecraft performance obtained using the proposed control laws.

Adaptive robust sliding mode control for ship straight-line tracking in random waves

Since complex controllers do not suit for application, we design a simple controller with robustness in changeable sea state. The characteristics of ship motion are large inertia, strong nonlinearity and large time delay. This paper employs adaptive sliding mode technique. We focus on a class of underactuated ship systems with parametric uncertainties and wave effects. Random wave effects are seldom considered in former studies. Various simulations validate the adaptive characteristics and robustness of the proposed controller. The closed-loop system is stable and tracking error can be arbitrarily small by Lyapunov approach.

PWM-Based Adaptive Sliding-Mode Control for Boost DC–DC Converters

In this paper, a robust adaptive sliding-mode controller is designed for a boost converter with an unknown resistive load and external input voltage. Adaptation laws are designed using state observers. The closed-loop system for the boost converter is shown to be asymptotically stable. Finally, the robustness of the adaptive controller to input voltage and load uncertainties and variations is tested experimentally.

Robust adaptive sliding-mode control of condenser-cleaning mobile manipulator using fuzzy wavelet neural network

This paper presents a robust adaptive sliding-mode control (RASMC) scheme for a class of condenser-cleaning mobile manipulator (CCMM) in the presence of parametric uncertainties and external disturbances. The development of control system is based on the fuzzy wavelet neural network (FWNN). First, a dynamic model is obtained in view of the practical CCMM system. Second, the FWNN is used to identify the unstructured system dynamics directly due to its ability to approximate a nonlinear continuous function to arbitrary accuracy. Using learning ability of neural networks, RASMC can coordinately control the condenser-cleaning mobile platform and the mounted manipulator with different dynamics efficiently. The implementation of the control algorithm is dependent on the adaptive sliding-mode control. Finally, based on the Lyapunov stability theory, the stability of the whole control system, the boundedness of the neural networks weight estimation errors, and the uniformly ultimately boundedness of the tracking error are all strictly guaranteed. Moreover, simulation results validate the superior control performance of the proposed adaptive control method.

An efficient robust adaptive sliding mode control approach with its application to secure communications in the presence of uncertainties, external disturbance and unknown parameters

The present research attempts to extend the available literature in the area of secure communications to provide an efficient robust adaptive sliding mode control approach in the presence of uncertainties, external disturbances and unknown parameters. It is obvious that the proposed control approach aims to synchronize two hyper-chaotic systems through secure communication. In order to assure the security of signal sending and receiving, the technique of chaotic parameter modulation is taken into consideration. The stability performance of the present approach is accurately guaranteed via the Lyapunov theorem. Numerical simulation results are carried out to illustrate the proposed approach performance, which is easily able to follow the control objectives.

Synchronization of circular restricted three body problem with lorenz hyper chaotic system using a robust adaptive sliding mode controller

In this computational study, we synchronize the Circular Restricted Three Body Problem (CRTBP) with Lorenz Hyper Chaotic System (LHCS) using a Robust Adaptive Sliding Mode Controller (RASMC) together with uncertainties, external disturbances and fully unknown parameters. A simple suitable sliding surface, which includes synchronization errors, is constructed and appropriate update laws are used to tackle the uncertainties, external disturbances and unknown parameters. All simulations to achieve the synchronization for the implemented technique for the two non‐identical systems under consideration are being done using Mathematica. © 2013 Wiley Periodicals, Inc. Complexity 18: 58‐64, 2013

Robust adaptive first–second-order sliding mode control to stabilize the uncertain fin-roll dynamic

Controlling the roll motion involves several problems including incomplete measurements, external disturbances, and the model uncertainties. In this paper, the perturbed model for the roll-fin dynamics is extracted by considering the problems influencing the fin stabilizer system during ship sailing. The sliding mode control provides robust performance for the mentioned factors. Therefore, a sliding mode controller is designed based on the information about the upper bound of perturbations and wave excitation force. Inasmuch as the uncertainty bound is not usually known, a robust adaptive sliding mode controller is proposed. Although it has been proven that the proposed method is robust, the chattering phenomenon is accounted as a drawback of the sliding mode control. In order to overcome the chattering phenomenon, a second-order sliding mode is replaced by the first-order one to create an adaptive second-order sliding mode control. The simulation results show that the control strategy is effective to decrease the roll motion and robust to overcome the uncertainties and random waves.