Robust uncertainty compensation in MagLev by using extended state observer

In this paper, a novel adaptive interval type-2 fuzzy sliding mode control (AIT2FSMC) methodology is proposed based on the integration of sliding mode control and adaptive interval type-2 fuzzy control for chaotic system. The AIT2FSMC system is comprised of a fuzzy control design and a hitting control design. In the fuzzy control design, an interval type-2 fuzzy controller is designed to mimic a feedback linearization (FL) control law. In the hitting control design, a hitting controller is designed to compensate the approximation error between the FL control law and the interval type-2 fuzzy controller. The parameters of the interval type-2 fuzzy controller, as well as the uncertainty bound of the approximation error, are tuned adaptively. The adaptive laws are derived in the sense of Lyapunov stability theorem, thus the stability of the system can be guaranteed. The proposed control system compared to adaptive fuzzy sliding mode control (AFSMC). Simulation results show that the proposed control systems can achieve favorable performance and robust with respect to system uncertainties and external disturbances.

In this paper, advanced interval type-2 fuzzy sliding mode control (AIT2FSMC) for robot manipulator is proposed. The proposed AIT2FSMC is a combination of interval type-2 fuzzy system and sliding mode control. For resembling a feedback linearization (FL) control law, interval type-2 fuzzy system is designed. For compensating the approximation error between the FL control law and interval type-2 fuzzy system, sliding mode controller is designed, respectively. The tuning algorithms are derived in the sense of Lyapunov stability theorem. Two-link rigid robot manipulator with nonlinearity is used to test and the simulation results are presented to show the effectiveness of the proposed method that can control unknown system well.

In this paper, a feedback linearization (FL)-based control law made implementable using an extended state observer (ESO) is proposed for the trajectory tracking control of a flexible-joint robotic system. The FL-based controller cannot be implemented unless the full transformed state vector is available. The design also requires exact knowledge of the system model making the controller performance sensitive to uncertainties. To address these issues, an ESO is designed, which estimates the state vector, as well as the uncertainties in an integrated manner. The FL controller uses the states estimated by ESO, and the effect of uncertainties is compensated by augmenting the FL controller with the ESO-estimated uncertainties. The closed-loop stability of the system under the proposed observer-controller structure is established. The effectiveness of the ESO in the estimation of the states and uncertainties and the effectiveness of the FL + ESO controller in tracking are demonstrated through simulations. Lastly, the efficacy of the proposed approach is validated through experimentation on Quanser's flexible-joint module.

This article describes the design of a linear observer–linear controller-based robust output feedback scheme for output reference trajectory tracking tasks in the case of nonlinear, multivariable, nonholonomic underactuated mobile manipulators. The proposed linear feedback scheme is based on the use of a classical linear feedback controller and suitably extended, high-gain, linear Generalized Proportional Integral (GPI) observers, thus aiding the linear feedback controllers to provide an accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and perturbation inputs. This information is used in the proposed feedback controller in (a) approximate, yet close, cancelations, as lumped unstructured time-varying terms, of the influence of the highly coupled nonlinearities, and (b) the devising of proper linear output feedback control laws based on the approximate estimates of the string of phase variables associated with the flat outputs simultaneously provided by the disturbance observers. Simulations reveal the effectiveness of the proposed approach.

A position-disturbing force servo loading system consisting of two opposing hydraulic cylinders, a hydraulic loading cylinder and a bearing hydraulic cylinder, is the most common loading form. Aiming at the problem that the bearing hydraulic cylinder would bring superfluous force to the loading system, a solution to the ADRC controller is proposed. Based on the analysis of the mathematical model of the position disturbance type electro-hydraulic servo force loading mechanism, a first-order linear active disturbance rejection controller is designed according to the relative order of the system. The total disturbance of the system, including the superfluous force, is estimated by the extended state observer, and the linear error feedback control law is used for real-time compensation. The simulation results show that compared with the PID controller, the ADRC controller has better tracking accuracy, higher response speed and stronger robustness, and has the stronger anti-interference ability when the bearing system moves.

Two new active disturbance rejection control (ADRC) structures for nonlinear systems are introduced: a locally linearized variant and a fully nonlinear formulation. Both approaches incorporate model knowledge to enhance performance but differ in how nonlinear dynamics are integrated into the control and observer design. The first proposed structure employs a state-dependent local approximation of the nonlinear model to generate dynamic controller and observer gains, aiming to balance robustness and accuracy. In contrast, the second one directly embeds the full nonlinear dynamics into both the control law and extended state observer, tightly coupling performance to model fidelity. The proposed methods were experimentally validated on a magnetic levitation system, known for its strong nonlinearity, and compared with a classical linear ADRC (LADRC). Furthermore, stability analysis of the methods was conducted using Lyapunov theory. Results show that the linearized structure consistently improves regulation performance over LADRC and, in most cases, achieves similar results to nonlinear ADRC with lower computational effort. However, the performance of the nonlinear approach may degrade under modeling inaccuracies and limited observer bandwidth. This study highlights that the way model information is integrated–rather than its level of detail–has a decisive impact on control quality. Finally, practical design guidelines are provided to assist in selecting an appropriate ADRC structure for nonlinear applications where robustness, computational efficiency, and limited model knowledge must be balanced.

Recently, magnetic telemanipulation devices have shown a great deal of promise in such areas as semi-conductor manufacturing, wind tunnels, drug delivery, and many more. However, these devices are generally associated with problems caused by payload variation and uncertainties in the parameters of the system which in turn, have limited the development and application of magnetic telemanipulation technology to its full capacity. This paper addresses and deals with these issues by implementation of a precise position control method for a magnetic telemanipulation system with high level of uncertainties in its parameters. The levitation system used in this study is primarily designed for performing remote pick and place operations. The levitated object is a 28 gr microrobot capable of grasping and releasing payloads as heavy as 8 gr. To cope with the uncertainties in the modeling and payload variation, a model reference adaptive feedback linearization (MRAFL) controller is designed and its performance compared with an ordinary feedback linearization (FL) controller. Through experimental results it is shown that the MRAFL controller enables the microrobot to grasp and transport a payload as heavy as 30% of its own weight without a considerable effect on its positioning accuracy. In the presence of the payload, the MRAFL controller resulted in a RMS positioning error of 8 μm} compared with 27.9 μm} of the FL controller. The approach presented in this work is versatile as it leads to the modeling and control of a highly nonlinear system through a modular approach that can be applied to a variety of magnetic levitation and telemanipulation systems.

The flatness-based active disturbance rejection control (ADRC) approach via online algebraic parameter identification is proposed to deal with the double tank problem. The control task is to maintain the lower tank level at a desired value by manipulating the inlet regulating valve. Firstly, the double tank problem is formulated based on the designed double tank platform, where the process input and output data are available in real-time in Matlab software installed in the upper monitor and the ABB AC800M in the lower computer. Then, the algebraic parameter identification algorithm is proposed to identify the unknown parameters of a typical second-order process, which was a flatness system with the lower tank level as the flat output. All the unmodelled dynamics, as well as the external disturbances are regarded as the total disturbance. Based on the identified model parameters of the process, an extended state observer is constructed to estimate the the flat output and its time derivative, as well as the total disturbance in real-time. A linear feedback control law is then designed to steer the lower tank level following the desired trajectory of the flat output, and thus the flatness-based ADRC approach is designed. The effectiveness of the proposed approach is validated by the simulation results based on the practical process input and output data in the platform.

The robust H∞ control problem for time-varying uncertain linear systems with time-varying state, and control delays is considered. Based on the Riccati equation approach, we design a robust H∞ linear time-invariant state feedback control law, which stabilizes the system and reduces the effect of the disturbance input on the controlled output to a prescribed level for all admissible uncertainties. A sufficient condition for the existence of the. robust H∞ controller is derived and two synthesis methods are presented for a robust H∞ control law to uncertain time-delay systems. One is to construct a robust H∞ control law by an equivalent linear time-invariant structural description for the sufficient condition and the control law can be obtained by solving an algebraic Riccati equation (ARE). The other method is to transform the sufficient condition into a linear matrix inequality (LMF) problem and the control law can be obtained by solving the LMI. A numerical example is presented to illustrate the obtained results.

Introduction Dynamics and control of tethered satellites during deployment and retrieval phases have been studied by numerous authors. Following the suggestion of the tension control law by Hupp, many nonlinear feedback tension control laws based on Liapunov functions have been proposed. Determination of the tension control law through this route is possible only by trial and error because Liapunov functions are nonunique. In this paper an alternate method, a linear state variable feedback control law is proposed for retrieval of tethered satellites. The control gains are determined by using theorems in analytical mechanics. This method results in a minimum number of state variables that need to be fed back to stabilize the system because it is possible to set some of the controller gains to zero. Simulation of the nonlinear system over the nonzero gain space results in a robust controller that meets the performance specifications set by the designer. The study concludes with the effect of structured uncertainties in the initial conditions. All the initial conditions are perturbed and the simulations are carried out once again with the same control law. The result is very encouraging: large variations in the initial conditions can be tolerated before degradation in the system response. 'presently. Engineer, Vikram Sarabhai Space Centre, Thiruvananthapuram, India t Assistant Professor, Member, AIAA '•presently, Engineer, Vikram Sarabhai Space Centre, Thiruvananthapuram, India Copyright ©1998 by the American Institute of Aeronautics and Astronautics, Inc., All rights reserved. Tethered satellites deployed from the Space Shuttle have been proposed for diverse applications such as creation of artificial gravity, gravity gradient stabilization, minimization of impact loads during spacecraft docking, electrodynamic drives and power generators for spacecraft, exploration of the upper atmosphere, orbital transfer, retrieval of stranded astronauts and ailing satellites, aerodynamic deceleration of satellites to prepare for reentry, as part of space escalators, creation of artificial gravity in the Space Station and long wavelength radio astronomy interferometry. A fundamental issue in the utilization of tethers is quick deployment/retrieval of the attached payload. Inordinate librations of the tether during deployment/retrieval are undesirable. The structural damping present in the system is too low to contain the librations. Deployment and retrieval of tethers are difficult to deal with analytically, because they lead to coupled nonlinear time varying differential equations. Rupp in 1975 proposed to control the tether reel located in the parent spacecraft to alter the tension in the tether, which in turn changes the stiffness and the damping of the system. Implementation of such a tension control law requires sensing the tether tension, rate of tether deployment/retrieval and the tether length. The control law will determine the amount of tension required to augment the requiste amount of stiffness and damping. Baker applied the tension control law to a model which included out of plane motion. Modi

The new nonlinear control technology-active disturbance rejection control is introduced, and the novel unit ADRC coordinated control scheme for thermal power generation unit is proposed. The key element of ADRC is extended state observer (ESO). The real-time dynamic linearization is implemented by disturbance estimation via ESO and disturbance compensation via control law, instead of differential geometry based feedback linearization and direct feedback linearization theory which need accurate mathematical model of plant. The decoupling for MIMO coordinated system of boiler-turbine unit is also easily implemented by employing ADRC. The simulation results on STAR-90 show that the ADRC coordinated control scheme can effectively solve problems of strong nonlinearity, uncertainty, coupling, large time delay. And it can improve greatly the control performance of coordinated control system. The structure of ADRC coordinated control scheme is simple and clear. It is evident that the proposed scheme lends itself well in providing innovative solutions to practical unit coordinated system problems.

This paper presents the real time control of Magnetic Levitation System using feedback linearization and online learning using Radial Basis function neural networks. It starts with the comparison between adaptive linear controller and neurocontroller used here. Both the controllers uses feedback linearization method and Lyapunov's stability theory to derive update laws to control the nonlinear system. Simulation results justify the use of neurocontroller over adaptive linear controller. Magnetic Levitation System which is open loop unstable is stabilized using feedback linearization approach which relies on canceling the nonlinearities, whereas the online learning is implemented via function approximation in which the radial basis function neural network is used as a function approximator. The combination of feedback linearizing control law and adaptive laws ensures that the closed-loop system is stable.

Digital Control of Bilinear Continuous Processes. Application to a Chemical Pilot Plant.

Objective: This paper implies a comparison between sliding mode control and linear state feedback controller. When the linear systems are given bounded disturbance their robustness properties are studied. Method: Pole placement, classical sliding mode control using constant rate reaching law and constant plus proportional rate reaching law, super-twisting controller. Findings: Finite time asymptotic convergence is not achieved in linear feedback controller, Sliding Mode Control when used produced finite time asymptotic convergence. The measure of the control variable is obtained by taking norm of the control input. Applications: Process Control, Aerodynamics.

In order to improve the convergence speed and disturbance immunity of the linear maglev synchronous motor (LMLSM) maglev system, this paper proposes a dual sliding mode control strategy based on a novel expanded state observer (NESO). Firstly, a dual terminal sliding mode (DTSM) surface is designed, which exhibits the desired dynamic and steady state performance. The problem of the TSM singularity is solved by the dual sliding mode technique, which turns the control signal into a continuous switching control through the filtering function and effectively reduces the jitter problem. Since the maglev system is susceptible to uncertainties such as nonlinearity, strong coupling and external perturbations, which affect its tracking accuracy, a continuous smooth ESO is designed to estimate and compensate for these uncertainty perturbations, thus solving the problem that the traditional ESO is continuous but not derivable at the switching point. Then, it is proved that the DTSM control strategy based on NESO converges to the equilibrium point in finite time by Lyapunov function. Finally, the effectiveness and superiority of the proposed strategy are verified on the LMLSM maglev system platform.