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Hydraulic Control Systems

This paper studies the design of a robust discrete-time sliding mode control (DT-SMC) for a high precision electro-hydraulic actuator (EHA) system with nonlinear actuator friction. Nonlinear friction in the hydraulic actuator can greatly influence the performance and accuracy of the hydraulic actuators; however, it is difficult to accurately model nonlinear friction characteristics. In this paper, it is proposed to characterize frictions as an uncertainty in the system matrices. Indeed, the effects of variations of the nonlinear friction coefficients are considered as norm bounded uncertainties that span a bounded region to cover a wide range of real actuator friction. For such a discrete-time dynamic model for the EHA system with system matrices uncertainties and a nonlinear term, a sufficient condition for the existence of stable sliding surfaces is proposed by using the linear matrix inequality (LMI) approach. Based on this existence condition, a discrete-time sliding mode controller is developed such that the reaching motion satisfies the discrete-time sliding mode reaching condition for uncertain systems. Simulation and comparison studies on the EHA system model illustrate the effectiveness of the proposed method. The study is simulation based only as it is important to establish the feasibility and stability of the controller before attempting to apply the controller to a physical system.Copyright © 2009 by ASME

Modeling and Robust Discrete-Time Sliding Mode Control Design for a Fluid Power Electrohydraulic Actuator (EHA) System

The discrete cosine transform (DCT), introduced by Ahmed, Natarajan and Rao, has been used in many applications of digital signal processing, data compression and information hiding. There are four types of the discrete cosine transform. In simulating the discrete cosine transform, we propose a generalized discrete cosine transform with three parameters, and prove its orthogonality for some new cases. A new type of discrete cosine transform is proposed and its orthogonality is proved. Finally, we propose a generalized discrete W transform with three parameters, and prove its orthogonality for some new cases. Keywords: Discrete Fourier transform, discrete sine transform, discrete cosine transform, discrete W transform Nigerian Journal of Technological Research , vol7(1) 2012

On discrete cosine transform

This paper deals with the attitude tracking control of quadrotor unmanned aerial vehicles (UAV) with uncertainties and external disturbances. The control system is expressed on the special orthogonal group, SO(3), to avoid singularities and ambiguities associated with Euler angles and quaternions respectively. It is also the basis for achieving large angle tracking and complex UAV maneuver. Meanwhile, it greatly reducing the complexity of the controller design via variation-based linearization. And the approach of interval matrix is introduced to solve problems of controller online calculation and reduced control accuracy caused by uncertain parameters in model. The proposed robust H ∞ control system can exponential asymptotically follow a desired attitude trajectory in the presence of unstructured bounded disturbances. Finally, several simulation results are provided to validate the effectiveness, advantages and robustness of the proposed method.

Robust H∞ attitude tracking control of a quadrotor UAV on SO(3) via variation-based linearization and interval matrix approach

In this paper, a multiple model adaptive fault tolerant control scheme is proposed based on mixing of the control signals generated by a set of linear quadratic state feedback controllers. Each of these controllers are designed considering closed loop system performance for a particular range of fault. Stability analysis of the proposed scheme is provided. The paper further presents specific design and implementation for motion control of quadrotor unmanned aerial vehicles (UAVs). The designed mixing adaptive controller is tested via real-time experiments on Quanser Qball-X4 UAVs. The experimental results verify the efficiency of the proposed scheme.

Mixing Adaptive Fault Tolerant Control of Quadrotor UAV

This paper addresses the trajectory tracking problem for constrained high dynamic electro-hydraulic 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.

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

Hill musculoskeletal model (HMM) is commonly used to estimate human motion intentions. HMM utilizes electromyography (EMG) signals as the nonlinear model input to obtain muscle forces or torques. However, due to the fact that it contains many physiological parameters that are difficult to measure, HMM is generally applied in simple continuous intention estimation of a single joint. In this work, we aimed at recognizing shoulder and elbow joints angles and their angular velocities continuously in real time. Firstly, we used MYO armband as the EMG sensor. Then, a reasonable prediction model was deduced based on HMM and human dynamics to realize online continuous recognition of the four angles and angular velocities of shoulder and elbow joints. Nonlinear autoregressive with external input neural network (NARX) replaced the prediction equation. In addition, the framework of state space model was completed by constructing an observation equation. Thus, the closed-loop characteristic was realized to eliminate the influence of cumulative error and ensure good estimation performance. Experimental results verified the feasibility and accuracy of the algorithm. For predefined trajectory and random trajectory separately, the RMSE were 0.955 and 1.15 (degree) for angles estimation and 2.8, 3.40 for angular velocities (degree/s). Compared with the normally used back-propagation neural network (BPNN), the method proposed in this paper obviously got more accurate and smooth results.

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Real-Time Human Intention Recognition of Multi-Joints Based on MYO

In order to satisfy the real-time need of model-based controllers for model parameters and full states feedback, this paper has conducted in-depth research on the states and parameters estimation of electro-hydraulic actuator in legged robot with three problems for time-varying parameters estimation (including system parameters and external load force), non-measurable states estimation and measurable states filtering. The first-order trajectory sensitivity method based on the dynamic model is used to determine the parameter set to be estimated, and the parameter fast and slow characteristics are analyzed in detail to obtain the generalized states and slow-varying parameters. Then, the combined algorithm with a fast-varying time scale (composed of a fusion kalman filter and a fast-varying time scale extended kalman filter) and a slow-varying time scale (composed of a slow-varying time scale extended kalman filter) is innovatively proposed to realize the data-driven multi-scale online joint estimation of states and parameters for the actuator system. Finally, the results of three comparative experiments show that the proposed algorithm has better stability, faster convergence speed and more accurate estimation than the dual extended kalman filter algorithm, and the states and parameters estimated by the proposed algorithm accurately reflect the actual characteristics of actuator. Moreover, the algorithm has strong adaptability and robustness in different actuator hardware environment and strong convergence ability for different initial values of states and parameters.

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A Data-Driven Multi-Scale Online Joint Estimation of States and Parameters for Electro-Hydraulic Actuator in Legged Robot

The body weight support method of exoskeletons is useful for the rehabilitation of patients with lower limb dyskinesia and performance augmentation of elders. Rather than enhancing the human joint strength directly, the body weight support exoskeleton provides assistance by supporting part of the human body weight and thus releasing the burden experienced by human legs. This paper proposes a two-level hierarchical control method aiming to achieve task-free and strong system robustness. A scale force control method, which can be simply described as making the supporting force of the robot several times the magnitude of a human leg, is developed as the high-level controller. The low-level controller is designed as a fuzzy cerebellar model articulation controller (CMAC)-based adaptive control to enhance the system robustness. The proposed method is applied to a squat movement and a single leg stance movement and is simulated in a combined simulation environment. The results show that the exoskeleton can always provide improved support according to the foot reaction force that is controlled by the user and that the system handles model errors and external disturbances well.

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Fuzzy CMAC-Based Adaptive Scale Force Control of Body Weight Support Exoskeletons

The energy consumption of different gait parameters in quadrupedal trotting gaits is studied in this paper. A method is developed, which is structured upon the single leg dynamics model and combining the support period and swing period. According to the results of energy analysis, the gait parameter design method with the minimum energy consumption at a given speed is determined. Firstly, a single leg model of a quadruped robot with three degrees of freedom is constructed. Its kinematic and dynamic analysis are carried out. The energy consumption of different gait parameters is calculated through the dynamic model. Then the relationship between energy consumption and gait parameters is obtained. Finally, through the energy graph, the design approach of gait parameters with minimum energy consumption at a given speed is given.

Honglei An

Papers

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

Real-Time Human Intention Recognition of Multi-Joints Based on MYO

A Data-Driven Multi-Scale Online Joint Estimation of States and Parameters for Electro-Hydraulic Actuator in Legged Robot

Fuzzy CMAC-Based Adaptive Scale Force Control of Body Weight Support Exoskeletons

Gait Parameters Design Method of Trotting Gait Based On Energy Consumption