Nonlinear Model Based Coordinated Adaptive Robust Control of Electro-Hydraulic Robotic Manipulators: Methods and Comparative Studies

2001 ◽  
Author(s):  
Fanping Bu ◽  
Bin Yao
Keyword(s):  
Robust Control ◽  
Comparative Studies ◽  
Adaptive Robust Control ◽  
Robot Arm ◽  
Tracking Accuracy ◽  
Output Tracking ◽  
Model Based ◽  
Acceleration Feedback ◽  
Hydraulic Cylinders ◽  
Electrical Motors

Abstract Compared to conventional robot manipulators driven by electrical motors, hydraulic robot arms have richer nonlinear dynamics and stronger couplings among various joints (or hydraulic cylinders). This paper focuses on the physical model based coordinated adaptive robust control (ARC) strategies that explicitly take into account the strong coupling among various hydraulic cylinders (or joints). In our recent studies, two such methods were proposed to avoid the need of acceleration feedback in doing ARC backstepping designs. The first method uses an observer to recover the state needed for the ARC backstepping design. The second method utilizes the property that the adjoint matrix and the determinant of the inertial matrix can be linearly parametrized by certain suitably selected parameters and employ certain over-parametrizing techniques. Theoretically, both the resulting ARC controllers guarantee a prescribed output tracking transient performance and final tracking accuracy while achieving asymptotic output tracking in the presence of parametric uncertainties only. This paper focuses on the comparative studies of these two methods under various practical constraints. Extensive simulation results which are based on a three degree-of-freedom (DOF) hydraulic robot arm are presented to illustrate the advantages and drawbacks of each method.

Integrated Direct/Indirect Adaptive Robust Control of Multi-DOF Hydraulic Robotic Arms

2007 ◽  
Author(s):  
Amit Mohanty ◽  
Bin Yao
Keyword(s):  
Parameter Estimation ◽  
Robust Control ◽  
Adaptive Robust Control ◽  
Least Square ◽  
Parametric Uncertainties ◽  
Robot Arm ◽  
Transient Performance ◽  
Seamless Integration ◽  
Output Tracking ◽  
Indirect Adaptive Robust Control

In a general DIARC framework [13], the emphasis is always on the guaranteed transient performance and accurate trajectory tracking in the presence of uncertain nonlinearity and parametric uncertainties along with accurate parameter estimation for secondary purpose such as system health monitoring and prognosis. Need for accurate parameter estimation calls for the use of Least Square Estimation (LSE) type of algorithms for such a seamless integration of good tracking performance and accurate parameter estimation. This paper presents a physical model based integrated direct/indirect adaptive robust control (DIARC) strategy for a hydraulically actuated 3-DOF robotic arm. To avoid the need of acceleration feedback for DIARC back-stepping design, the property, that the adjoint matrix and the determinant of the inertial matrix could be linearly parameterized by certain suitably selected parameters is utilized. Unlike gradient-type parameter estimation law, which used overparamterization, there is no multiple estimation of the single parameter. Theoretically, the resulting controller is able to take into account not only the effect of parametric uncertainties coming from the payload and various hydraulic parameters but also the effect of uncertain nonlinearities. Furthermore, the proposed DIARC controller guarantees a prescribed output tracking transient performance and final tracking accuracy while achieving asymptotic output tracking in the presence of parametric uncertainties only. Simulation results based on a three degree-of-freedom (DOF) hydraulic robot arm (a scaled down version of an industrial back-hoe/excavator arm) are presented to illustrate the proposed control algorithm.

Indirect Neural Network Adaptive Robust Control of Linear Motor Drive System

2002 ◽  
Author(s):  
J. Q. Gong ◽  
Bin Yao
Keyword(s):  
Neural Network ◽  
Robust Control ◽  
Tracking Error ◽  
Linear Motor ◽  
Adaptive Robust Control ◽  
Operating Conditions ◽  
Tracking Performance ◽  
Motor Drive ◽  
Output Tracking ◽  
On Line

In this paper, an indirect neural network adaptive robust control (INNARC) scheme is developed for the precision motion control of linear motor drive systems. The proposed INNARC achieves not only good output tracking performance but also excellent identifications of unknown nonlinear forces in system for secondary purposes such as prognostics and machine health monitoring. Such dual objectives are accomplished through the complete separation of unknown nonlinearity estimation via neural networks and the design of baseline adaptive robust control (ARC) law for output tracking performance. Specifically, recurrent neural network (NN) structure with NN weights tuned on-line is employed to approximate various unknown nonlinear forces of the system having unknown forms to adapt to various operating conditions. The design is actual system dynamics based, which makes the resulting on-line weight tuning law much more robust and accurate than those in the tracking error dynamics based direct NNARC designs in implementation. With a controlled learning process achieved through projection type weights adaptation laws, certain robust control terms are constructed to attenuate the effect of possibly large transient modelling error for a theoretically guaranteed robust output tracking performance in general. Experimental results are obtained to verify the effectiveness of the proposed INNARC strategy. For example, for a typical point-to-point movement, with a measurement resolution level of ±1μm, the output tracking error during the entire execution period is within ±5μm and mainly stays within ±2μm showing excellent output tracking performance. At the same time, the outputs of NNs approximate the unknown forces very well allowing the estimates to be used for secondary purposes such as prognostics.

Adaptive Robust Control for Hydraulic Actuators With Disturbance Estimation

2015 ◽  
Author(s):  
Z. B. Xu ◽  
J. Y. Yao ◽  
Z. L. Dong ◽  
Y. Zheng
Keyword(s):  
Robust Control ◽  
Finite Time ◽  
Disturbance Observer ◽  
High Performance ◽  
Adaptive Robust Control ◽  
Parametric Uncertainties ◽  
Tracking Accuracy ◽  
Robust Controller ◽  
Hydraulic Actuators ◽  
Disturbance Estimation

In this paper, an adaptive robust control for hydraulic actuators with disturbance estimation is proposed for a hydraulic system with mismatched generalized uncertainties (e.g., parameter derivations, external disturbances, and/or unmodeled dynamics), in which a finite time disturbance observer and an adaptive robust controller are synthesized via backstepping method. The finite time disturbance observer is designed to estimate the mismatched generalized uncertainties. The adaptive robust controller is designed to handle parametric uncertainties and stabilize the closed loop system. The proposed controller accounts for not only the parametric uncertainties, but also the mismatched generalized uncertainties. Furthermore, the controller theoretically guarantees a prescribed tracking transient performance and final tracking accuracy while achieving asymptotic tracking performance after a finite time T0, which is very important for high accuracy tracking control of hydraulic servo systems. Simulation results are obtained to verify the high performance nature of the proposed control strategy.

Adaptive Robust Control for Mirror-Stabilized Platform With Input Saturation

2018 ◽  
Vol 140 (9) ◽  
Author(s):  
Jiangpeng Song ◽  
Di Zhou ◽  
Guangli Sun
Keyword(s):  
Control System ◽  
Robust Control ◽  
Input Saturation ◽  
Adaptive Robust Control ◽  
Kinematics And Dynamics ◽  
Tracking Accuracy ◽  
External Disturbances ◽  
Unknown Disturbances ◽  
The Stability ◽  
Stabilized Platform

The line-of-sight (LOS) kinematics and dynamics of a mirror-stabilized platform are derived using the virtual mass stabilization method. Accounting for the coupled and nonlinear kinematics and dynamics, the uncertainty of external disturbances, and the actuator input saturation in the mirror-stabilized platform, a modified adaptive robust control (ARC) scheme is proposed based on the command filtered method and the extended state observer (ESO). The command-filtered approach is used to ensure the stability and tracking performance of the adaptive control system under the input saturation. In the proposed scheme, the ESO is designed to observe the modeling error and unknown external disturbances. The stability of the control system is proved using the Lyapunov method. Simulation results and experimental results proved that the proposed control scheme can effectively reduce the occurrence of input saturation, attenuate the effect of unknown disturbances, and improve the position tracking accuracy.

scholarly journals T-S Fuzzy Model Based H-Infinity Control for 7-DoF Automobile Electrohydraulic Active Suspension System

2017 ◽  
Vol 2017 ◽  
pp. 1-14
Author(s):  
Chenyu Zhou ◽  
Qiang Yu ◽  
Xuan Zhao ◽  
Guohua Zhu
Keyword(s):  
Fuzzy Model ◽  
Active Suspension ◽  
Adaptive Robust Control ◽  
Linear Matrix ◽  
Tracking Accuracy ◽  
H Infinity ◽  
Model Based ◽  
Loop Design ◽  
H Infinity Control ◽  
Suspension Performance

This paper presents a double loop controller for a 7-DoF automobile electrohydraulic active suspension via T-S fuzzy modelling technique. The outer loop controller employs a modified H-infinity feedback control based on a T-S fuzzy model to provide the actuation force needed to ensure better riding comfort and handling stability. The resulting optimizing problem is transformed into a linear matrix inequalities solution issue associated with stability analysis, suspension stroke limit, and force constraints. Integrating these via parallel distributed compensation method, the feedback gains are derived to render the suspension performance dependent on the perturbation size and improve the efficiency of active suspensions. Adaptive Robust Control (ARC) is then adopted in the inner loop design to deal with uncertain nonlinearities and improve tracking accuracy. The validity of improvements attained from this controller is demonstrated by comparing with conventional Backstepping control and a passive suspension on a 7-DoF simulation example. It is shown that the T-S fuzzy model based controller can achieve favourable suspension performance and energy conservation under both mild and malevolent road inputs.

scholarly journals Simplified Adaptive Robust Motion Control with Varying Boundary Discontinuous Projection of Hydraulic Actuator

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Cungui Yu ◽  
Xianwei Qi
Keyword(s):  
Robust Control ◽  
Motion Control ◽  
High Performance ◽  
Simple Algorithm ◽  
Adaptive Robust Control ◽  
Hydraulic Systems ◽  
Hydraulic Actuator ◽  
Tracking Accuracy ◽  
Rotary Actuator ◽  
Robust Motion Control

This paper deals with the high performance adaptive robust motion control of electrohydraulic servo system driven by dual vane hydraulic rotary actuator. The recently developed adaptive robust control theory is used to handle the nonlinearities and modelling uncertainties in hydraulic systems. Aside from the difficulty of handling parametric variations, the traditional adaptive robust controller (ARC) is also a little complicated in practice. To address these challenging issues, a simplified adaptive robust control with varying boundary discontinuous projection is developed to enhance the robustness of the closed-loop system, based on the features of hydraulic rotary actuator. Compared with previous ARC controller, the resulting controller has a simple algorithm for more suitable implementation and can handle parametric variations via nonlinear robust design. The controller theoretically achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities. Extensive simulation results are obtained for a hydraulic rotary actuator to verify the high performance nature of proposed control strategy.

Energy-Efficient Adaptive Robust Control of Vector Thrust UAVs With Unknown Inertia Parameters

2018 ◽  
Author(s):  
Caiwu Ding ◽  
Lu Lu ◽  
Cong Wang
Keyword(s):  
Robust Control ◽  
Energy Efficient ◽  
Control Method ◽  
Thrust Force ◽  
Center Of Mass ◽  
Adaptive Robust Control ◽  
Parametric Uncertainties ◽  
Tracking Accuracy ◽  
Robust Tracking Control ◽  
Linear Equality Constraints

This paper proposes an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. We consider a novel vector thrust UAV with all propellers able to tilt about two perpendicular axes, so that the thrust force generated by each propeller is a fully controllable vector in 3D space, based on which an adaptive robust control is designed for accurate trajectory tracking in the presence of inertial parametric uncertainties and uncertain nonlinearities. Theoretically, the resulting controller achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities. In addition, in the presence of only parametric uncertainties, the controller achieves asymptotic output tracking. To resolve the redundancy in actuation, a thrust force optimization problem minimizing power consumption while achieving the desired body force wrench is formulated, and is shown to be convex with linear equality constraints. Simulation results are also presented to verify the proposed solution.

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