Output feedback model predictive control of hydraulic systems with disturbances compensation

Gu, Wenjin; Yao, Jianyong; Yao, Zhikai; Zheng, Jingzhong

doi:10.1016/j.isatra.2018.12.007

Cited by 48 publications

(23 citation statements)

References 23 publications

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“…In fact, as a model-based method, MPC relies on accurate models to predict the future evolution of state variables to generate the optimal control sequence, so unavoidable time-varying parameters and large external interference will affect the accuracy of MPC controllers. In [22], Gu and Yao et al developed a method combining extended state observer (ESO) and unconstrained MPC based on prior model to achieve improved tracking performance for state and large disturbance estimation. However, not only the complex parameter adjustment of ESO requires a certain amount of time and experience to try it out, but also once the prior model parameters used in ESO change, the estimated state and disturbance have large errors.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Trajectory Tracking Control of Electro-Hydraulic Actuator in Legged Robot With Multi-Scale Online Estimator

Huang

et al. 2020

IEEE Access

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This paper addresses the trajectory tracking problem for constrained high dynamic electrohydraulic actuator in the presence of time-varying parameters, high frequency external load interference, measurement noise and some unmeasurable states. An adaptive robust optimal control scheme is proposed for the electro-hydraulic actuator in legged robot. The framework of our presented scheme is based on a linear time-varying model predictive controller (LTV-MPC) embedded with a multi-scale online estimator (MEKF). With fast-varying and slow-varying time scales, the MEKF part is used not only for measurable states filtering and unmeasurable states estimation, but also for time-varying parameters and external load interference estimation, which will be integrated into the mpc model in real time. The LTV-MPC part is a trajectory tracking controller designed by constrained MPC with an approximate high-precision real-time model and a rapidly solved cost function, which guarantees that the input and output constraints are satisfied during the receding horizon and optimal control process. Finally, with a series of highly dynamic conditions, the comparison experiment results show that the proposed controller has a simple design process, strong adaptive robust performance and trajectory tracking performance, which verifies the effectiveness of the control scheme. INDEX TERMS Multi-scale online estimator, linear time-varying model predictive controller, electrohydraulic actuator.

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Section: Introductionmentioning

confidence: 99%

Model Predictive Trajectory Tracking Control of Electro-Hydraulic Actuator in Legged Robot With Multi-Scale Online Estimator

Huang

et al. 2020

IEEE Access

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show abstract

“…In [30], the study addressed uncertainties which decay as function of the system states. In [28], an output feedback model predictive controller (MPC) with the integration of an extended state observer (ESO) is proposed for hydraulic systems. The experimental application shows an enhancement of the robusteness.…”

Section: Introductionmentioning

confidence: 99%

RMPC for Uncertain Nonlinear Systems With Non-Additive Dynamic Disturbances and Noisy Measurements

El-Férik

2020

IEEE Access

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In this paper, we present a robust, model-predictive control scheme for the general class of uncertain and constrained discrete-time nonlinear systems subject to noisy measurements. The relationships between the system's dynamics, uncertainties, disturbances and the measurement noise are nonlinear and not necessarily additive. In particular, the disturbance is the output of an uncertain system with an unknown input. This study serves the threefold ultimate objective of ensuring robust satisfaction of the state constraints, recursive feasibility and stability. To satisfy state constraints, the proposed algorithms adopt a constraints tightening approach using the restricted constraint sets computed online. Several bounds on the prediction level and rate are derived and the size of the terminal region is maximized using polytopic linear differential inclusions (PLDI). An explicit bound on the maximum allowable disturbance for recursive feasibility is also derived based on optimization of the one-step ahead controllable set to the terminal region. The disturbance and uncertainties are non-vanishing and therefore only Input-to-state practical stability (ISpS) can be ensured. A simulation example demonstrates the efficacy of the mathematical framework and algorithms developed in this work. INDEX TERMS Nonlinear MPC, robust MPC, constraint tightening, convex optimization.

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“…Up to now, some studies based on the output feedback control have been applied to DC Motors [12], hydraulic actuators [14,15], flight actuation system [16] and hydraulic loading system [17]. However, since the dynamics of pneumatic systems are highly nonlinear due to gas compressibility, the aforementioned output feedback controllers cannot be applied directly to the pneumatic systems.…”

Section: Introductionmentioning

confidence: 99%

Output feedback motion control of pneumatic servo systems with desired compensation approach

Wei-ping

Meng

2020

J Braz. Soc. Mech. Sci. Eng.

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In this study, an output feedback control strategy for the pneumatic asymmetric cylinder is established by integrating a robust controller with the proposed desired compensation adaptive law and extended sliding mode observer (ESMO). Specifically, in order to attenuate the parametric uncertainties, a desired compensation indirect-type estimation method, based on physical model and desired system states, is designed to achieve estimates of model parameters, and the parameter estimation error can be regarded as part of the lumped uncertainties. Since only displacement signal is available, both the unmeasured system states and lumped uncertainties are estimated by the proposed ESMO, and the global stability is guaranteed by the presented robust control law. As a result, structured (i.e., parametric uncertainties) and unstructured (i.e., lumped uncertainties such as unmodeled dynamics, external disturbance and parameter estimation error) uncertainties can be handled and compensated, respectively, in one controller. The comparative experimental results indicate that the prescribed tracking trajectory can be achieved by the proposed controller in the presence of time-varying uncertainties.

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Output feedback model predictive control of hydraulic systems with disturbances compensation

Cited by 48 publications

References 23 publications

Model Predictive Trajectory Tracking Control of Electro-Hydraulic Actuator in Legged Robot With Multi-Scale Online Estimator

Model Predictive Trajectory Tracking Control of Electro-Hydraulic Actuator in Legged Robot With Multi-Scale Online Estimator

RMPC for Uncertain Nonlinear Systems With Non-Additive Dynamic Disturbances and Noisy Measurements

Output feedback motion control of pneumatic servo systems with desired compensation approach

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