Composite Learning Control With Application to Inverted Pendulums

Composite adaptive control (CAC) that integrates direct and indirect adaptive control techniques can achieve smaller tracking errors and faster parameter convergence compared with direct and indirect adaptive control techniques. However, the condition of persistent excitation (PE) still has to be satisfied to guarantee parameter convergence in CAC. This paper proposes a novel model reference composite learning control (MRCLC) strategy for a class of affine nonlinear systems with parametric uncertainties to guarantee parameter convergence without the PE condition. In the composite learning, an integral during a moving-time window is utilized to construct a prediction error, a linear filter is applied to alleviate the derivation of plant states, and both the tracking error and the prediction error are applied to update parametric estimates. It is proven that the closed-loop system achieves global exponential-like stability under interval excitation rather than PE of regression functions. The effectiveness of the proposed MRCLC has been verified by the application to an inverted pendulum control problem.Comment: 5 pages, 6 figures, conference submissio

Mobility design and control of personal mobility aids for the elderly

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2002.Includes bibliographical references (p. 127-130).Delaying the transition of the elderly to higher level of care using assistive robotic devices could have great social and economic significance. The transition, necessitated by the degradation of physical and cognitive capability of the elderly, results in drastic increase of cost and rapid decrease of quality of life. A Personal Aid for Mobility and Health Monitoring system (PAMM) has been developed at MIT Field and Space Robotics Laboratory for the elderly living independently or in senior assisted living facilities so as to delay their transition to nursing homes. This thesis research addresses the mobility design and control issues of such devices. Eldercare environments are semi-structured, usually congested, and filled with static and/or dynamic obstacles. Developing effective mobility designs to achieve good maneuverability is a great challenge. An omni-directional mobility concept using conventional wheels has been developed independently in this research. Mobility systems based on this concept are simple, lightweight, energy efficient, and capable of operating on a range of floor surfaces. Assistive mobility devices work in shared workspace and interact directly with their users with limited physical and cognitive capabilities. The users may not be well trained, nor fully understand system. The challenge is to design an ergonomic and intuitive human machine interaction and a control system that can properly allocate control authority between the human and the machine. For this purpose, the admittance-based control methodology is used for the human machine interaction control. An adaptive shared control framework allocates control based on metrics of the demonstrated human performance has been developed.(cont.) Substantial amount of field experiments have been conducted with the actual users to validate control system design. The mobility design and control system implemented and tested on PAMM, will also be applicable to other cooperative mobile robots working in semi-structured indoor environments such as a factory or warehouse.by Haoyong Yu.Ph.D

Composite learning adaptive backstepping control using neural networks with compact supports

© 2019 John Wiley & Sons, Ltd. The ability to learn is crucial for neural network (NN) control as it is able to enhance the overall stability and robustness of control systems. In this study, a composite learning control strategy is proposed for a class of strict-feedback nonlinear systems with mismatched uncertainties, where raised-cosine radial basis function NNs with compact supports are applied to approximate system uncertainties. Both online historical data and instantaneous data are utilized to update NN weights. Practical exponential stability of the closed-loop system is established under a weak excitation condition termed interval excitation. The proposed approach ensures fast parameter convergence, implying an exact estimation of plant uncertainties, without the trajectory of NN inputs being recurrent and the time derivation of plant states. The raised-cosine radial basis function NNs applied not only reduces computational cost but also facilitates the exact determination of a subregressor activated along any trajectory of NN inputs so that the interval excitation condition is verifiable. Numerical results have verified validity and superiority of the proposed approach

A Sliding Mode Force and Position Controller Synthesis for Series Elastic Actuators

This paper deals with the robust force and position control problems of Series Elastic Actuators. It is shown that a Series Elastic Actuator's force control problem can be described by a second-order dynamic model which suffers from only matched disturbances. However, the position control dynamics of a Series Elastic Actuator is of fourth-order and includes matched and mismatched disturbances. In other words, a Series Elastic Actuator's position control is more complicated than its force control, particularly when disturbances are considered. A novel robust motion controller is proposed for Series Elastic Actuators by using Disturbance Observer and Sliding Mode Control. When the proposed robust motion controller is implemented, a Series Elastic Actuator can precisely track desired trajectories and safely contact with an unknown and dynamic environment. The proposed motion controller does not require precise dynamic models of the actuator and environment. Therefore, it can be applied to many different advanced robotic systems such as compliant humanoids and exoskeletons. The validity of the motion controller is experimentally verified.Comment: Accepted by Robotica in 201

High-order based revelation of bifurcation of novel Schatz-inspired metamorphic mechanisms using screw theory

The revelation of mechanism bifurcation is essential in the design and analysis of reconfigurable mechanisms. The first- and second-order based methods have successfully revealed the bifurcation of mechanisms. However, they fail in the novel Schatz-inspired metamorphic mechanisms presented in this paper. Here, we present the third- and fourth-order based method for their bifurcation revelation using screw theory. Based on the constraint equations derived from the first- and second-order kinematics, only one linearly independent relationship between joint angular velocities at the singular configuration of the new mechanism can be generated, which means the bifurcation cannot be revealed in this way. Therefore, we calculate constraint equations from the third- and fourth-order kinematics, and attain two linearly independent relationships between joint angular accelerations at the same singular configuration that correspond to different curvatures of the kinematic curves of two motion branches in the configuration space. Moreover, motion branches in Schatz-inspired metamorphic mechanisms are demonstrated