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Shrivijay B. Phadke

Bio: Shrivijay B. Phadke is an academic researcher from College of Engineering, Pune. The author has contributed to research in topics: Sliding mode control & Control theory. The author has an hindex of 21, co-authored 68 publications receiving 1989 citations. Previous affiliations of Shrivijay B. Phadke include Defence Institute of Advanced Technology.


Papers
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Journal ArticleDOI
TL;DR: A control is proposed to handle a larger class of mismatched uncertainties by extending the disturbance observer and modifying and generalizing the sliding surface.
Abstract: This paper extends a recent result on sliding mode control for general n th order systems with mismatched uncertainties. In this paper, a control is proposed to handle a larger class of mismatched uncertainties by extending the disturbance observer and modifying and generalizing the sliding surface. The practical stability of the overall system is proved and the results are verified by simulation of an illustrative example.

495 citations

Journal ArticleDOI
TL;DR: 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 and the closed-loop stability of the system under the proposed observer-controller structure is established.
Abstract: 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.

424 citations

Journal ArticleDOI
TL;DR: In this paper, a scheme to reduce the acceleration of the sprung mass, used in combination with sliding mode control, is proposed to estimate the effects of the uncertain, nonlinear spring and damper, load variation and the unknown road disturbance.

126 citations

Journal ArticleDOI
TL;DR: In this paper, a new design of sliding mode control based on an uncertainty and disturbance estimator (UDE) is given, which does not require the knowledge of bounds of uncertainties and disturbances and is continuous.
Abstract: A new design of sliding mode control based on an uncertainty and disturbance estimator (UDE) is given. The control proposed does not require the knowledge of bounds of uncertainties and disturbances and is continuous. Thus, two main difficulties in the design of sliding mode control are overcome. Furthermore, the method of UDE is extended to plants having significant uncertainty in the control input matrix and subjected to disturbances that nonlinearly depend on states.

107 citations

Journal ArticleDOI
TL;DR: A novel formulation of sliding mode control (SMC) based proportional navigation (PN) guidance law does not need any knowledge of bounds of target acceleration and closed-loop stability for the guidance loop is established.
Abstract: A novel formulation of sliding mode control (SMC) based proportional navigation (PN) guidance law is presented. Unlike conventional SMC-based guidance laws, the law presented here does not need any knowledge of bounds of target acceleration. The target acceleration is estimated using the so-called inertial delay control (IDC). Closed-loop stability for the guidance loop is established. Simulations are carried out by considering highly-maneuvering targets and constant as well as varying missile velocity and the results are presented to demonstrate the effectiveness of the proposed formulation.

96 citations


Cited by
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Journal ArticleDOI
TL;DR: By appropriately choosing a disturbance compensation gain, a generalized ESOBC (GESOBC) method is proposed for nonintegral-chain systems subject to mismatched uncertainties without any coordinate transformations, able to extend to multi-input-multi-output systems with almost no modification.
Abstract: The standard extended state observer based control (ESOBC) method is only applicable for a class of single-input-single-output essential-integral-chain systems with matched uncertainties. It is noticed that systems with nonintegral-chain form and mismatched uncertainties are more general and widely exist in practical engineering systems, where the standard ESOBC method is no longer available. To this end, it is imperative to explore new ESOBC approach for these systems to extend its applicability. By appropriately choosing a disturbance compensation gain, a generalized ESOBC (GESOBC) method is proposed for nonintegral-chain systems subject to mismatched uncertainties without any coordinate transformations. The proposed method is able to extend to multi-input-multi-output systems with almost no modification. Both numerical and application design examples demonstrate the feasibility and efficacy of the proposed method.

637 citations

Journal ArticleDOI
TL;DR: Several breakthroughs for control of nonlinear uncertain systems, made possible by ADRC, are discussed and the latest results in theoretical analysis of the ADRC-based control systems are introduced.
Abstract: The methodology of ADRC and the progress of its theoretical analysis are reviewed in the paper. Several breakthroughs for control of nonlinear uncertain systems, made possible by ADRC, are discussed. The key in employing ADRC, which is to accurately determine the “total disturbance” that affects the output of the system, is illuminated. The latest results in theoretical analysis of the ADRC-based control systems are introduced.

629 citations

Journal ArticleDOI
TL;DR: The proposed controller theoretically guarantees a prescribed tracking transient performance and final tracking accuracy, while achieving asymptotic tracking performance in the absence of time-varying uncertainties, which is very important for high-accuracy tracking control of hydraulic servo systems.
Abstract: In this paper, an output feedback nonlinear control is proposed for a hydraulic system with mismatched modeling uncertainties in which an extended state observer (ESO) and a nonlinear robust controller are synthesized via the backstepping method. The ESO is designed to estimate not only the unmeasured system states but also the modeling uncertainties. The nonlinear robust controller is designed to stabilize the closed-loop system. The proposed controller accounts for not only the nonlinearities (e.g., nonlinear flow features of servovalve), but also the modeling uncertainties (e.g., parameter derivations and unmodeled dynamics). Furthermore, the controller theoretically guarantees a prescribed tracking transient performance and final tracking accuracy, while achieving asymptotic tracking performance in the absence of time-varying uncertainties, which is very important for high-accuracy tracking control of hydraulic servo systems. Extensive comparative experimental results are obtained to verify the high-performance nature of the proposed control strategy.

586 citations

Journal ArticleDOI
TL;DR: 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 and the closed-loop stability of the system under the proposed observer-controller structure is established.
Abstract: 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.

424 citations

Journal ArticleDOI
TL;DR: The stability of the whole closed-loop system is rigorously proved via the Lyapunov analysis method, and the satisfactory tracking performance is guaranteed under the integrated effect of unknown hysteresis, unmeasured states, and unknown external disturbances.
Abstract: In this paper, an adaptive neural output feedback control scheme is proposed for uncertain nonlinear systems that are subject to unknown hysteresis, external disturbances, and unmeasured states. To deal with the unknown nonlinear function term in the uncertain nonlinear system, the approximation capability of the radial basis function neural network (RBFNN) is employed. Using the approximation output of the RBFNN, the state observer and the nonlinear disturbance observer (NDO) are developed to estimate unmeasured states and unknown compounded disturbances, respectively. Based on the RBFNN, the developed NDO, and the state observer, the adaptive neural output feedback control is proposed for uncertain nonlinear systems using the backstepping technique. The first-order sliding-mode differentiator is employed to avoid the tedious analytic computation and the problem of “explosion of complexity” in the conventional backstepping method. The stability of the whole closed-loop system is rigorously proved via the Lyapunov analysis method, and the satisfactory tracking performance is guaranteed under the integrated effect of unknown hysteresis, unmeasured states, and unknown external disturbances. Simulation results of an example are presented to illustrate the effectiveness of the proposed adaptive neural output feedback control scheme for uncertain nonlinear systems.

352 citations