Elyes Maherzi

An LMI-based robust dynamic controller design for the improvement of robot behavior walk, ZMP based

This work aims to design an optimal dynamic controller to stabilize the walk of a biped robot even in the presence of input and output constraints. In a first time, the robots trajectory is generated via the Zero Moment Point criterion based on the resolution of a convex optimization problem with Linear Matrix Inequalities. In a second time, the tracking of a reference trajectory is insured by the design of an optimal dynamic controller based on the predictive control theory. The synthesized dynamic controller allows for the Lyapunov stability of the robots walk. Moreover, it ensures the reducing of the overshoot and undershoot of the output signal that are difficult to be adjusted by classical methods based on solving the algebraic Riccati equation. This study is validated by a simulation via Matlab of some illustrative examples. Results are presented to prove the effectiveness of the proposed work.

A robust dynamic controller with observer for the tracking of a ZMP reference trajectory: A biped robot's walking under constraints

In this work, we propose a novel robust dynamic controller in order to stabilize a walking biped robot with input and output constraints. Firstly, the trajectory of the robot is generated via the Zero Moment Point method based on the resolution of a convex optimization problem with Linear Matrix Inequalities. Then, the tracking of a referential trajectory is insured by the design of an optimal dynamic controller with predictive control theory. The synthesized dynamic controller allows the Lyapunov stability of the robots walk. Moreover, it ensures the reducing of the overshoot and undershoot of the output signal, difficult to be adjusted by classical methods. This work is validated by a simulation via Matlab of some illustrative examples and results highlight the efficiency of the proposed study.

Development of monitoring algorithm for controlling a biped robot: norm bounded uncertainties system-based

It is well known that the biped walking gait is represented as a steady periodic gait. Investigation of such passive natural motion leads to different strategies of control; these strategies require a sharp mathematical model of the walking dynamics. One of the most used models is the Kajitas one. In this paper, we present an algorithm of controllers design used for the stabilisation of biped robots gait. Using the Kajitas model as a reference, we include a Norm bounded uncertainties to ensure a more realistic numerical model. The modified model allows us to include constraints on both inputs, outputs and states. The synthesis of the dynamic controller relies on the use of predictive control theory (MPC) and the resolution of a convex optimisation problem with linear matrix inequalities (LMIs) at every sampling period. The generated control law allows a real-time walking robot even in rough ground or unknown environment.

Robust walking control algorithm of biped robot in rough ground

This paper presents an algorithm of a robust controller used for the stabilization of biped robot walking gait. The robot is described by a kajitas model with norm bounded uncertainties to ensure a more realistic numerical model. The proposed robust dynamic controller relies on the use of predictive control theory (MPC) and the resolution of a convex optimization problem with Linear Matrix Inequalities (LMI) at every sampling period. The generated control law allows a realtime working robot even in rough ground or unknown environment.

Switched Control of a Time Delayed Compass Gait Robot

the analysis and control of delayed systems are becoming more and more research topics in progress. This is mainly due to the fact that the delay is frequently encountered in technological systems. Most control command laws are based on current digital computers and delays are intrinsic to the process or in the control loop caused by the transmission time control sequences, or computing time. In other hand, the controls of humanoid walking robot present a common problem in robotics because it involves physical interaction between an articulated system and its environment. This close relationship is actually a common set of fundamental problems such as the implementation of robust stable dynamic control. This paper presents acomplete approach, based on switched system theory, for the stabilization of a compass gait robot subject to time delays transmission. The multiple feedback gains designed are based on multiple linear systems governed by a switching control law. The establishment of control law in real time is affected by the unknown pounded random delay. The results obtained from this method show that the control law stabilize the compass robot walk despite a varying delay reaching six times sampling period.

Estimation of the State and the Unknown Inputs of a Multimodel with non Measurable Decision Variables

This paper treats the estimation of the state of a nonlinear system with unknown input. The nonlinear system is described by a multimodel with unknown function of activation but depending only on the state. The method of design of the multiobserver is described by using the second method of Lyapunov and their candidate functions. The sufficient obtained stability conditions are expressed in terms of Linear Matrix Inequalities (LMI) and are obtained first using the Lyapunov quadratic functions and secondly by using Lyapunov polyquadratic functions. This latter technique seems to be less conservative and less constraining than the first. Illustrative examples are presented in this paper.