LPV control and virtual-sensor-based fault tolerant strategies for a three-axis gimbal system

This paper deals with the LPV control of a three-axis gimbal including fault-tolerant capabilities. First, the derivation of an analytical model for the considered system based on the robotics Serial-Link (SL) theory is derived. Then, a series of simplifications that allow obtaining a quasi-LPV model for the considered gimbal is proposed. Gain scheduling LPV controllers with PID structure are designed using pole placement by means of linear matrix inequalities (LMIs). Moreover, exploiting the sensor redundancy available in the gimbal, a virtual-sensor-based fault tolerant control (FTC) strategy is proposed. This virtual sensor uses a Recursive Least Square (RLS) estimation algorithm and an LPV observer for fault detection and estimation. Finally, the proposed LPV control scheme including the virtual sensor strategy is tested in simulation in several scenarios.Peer ReviewedPostprint (published version

Control of posture with FES systems

One of the major obstacles in restoration of functional FES supported standing in paraplegia is the lack of knowledge of a suitable control strategy. The main issue is how to integrate the purposeful actions of the non-paralysed upper body when interacting with the environment while standing, and the actions of the artificial FES control system supporting the paralyzed lower extremities. In this paper we provide a review of our approach to solving this question, which focuses on three inter-related areas: investigations of the basic mechanisms of functional postural responses in neurologically intact subjects; re-training of the residual sensory-motor activities of the upper body in paralyzed individuals; and development of closed-loop FES control systems for support of the paralyzed joints

Modelica - A Language for Physical System Modeling, Visualization and Interaction

Modelica is an object-oriented language for modeling of large, complex and heterogeneous physical systems. It is suited for multi-domain modeling, for example for modeling of mechatronics including cars, aircrafts and industrial robots which typically consist of mechanical, electrical and hydraulic subsystems as well as control systems. General equations are used for modeling of the physical phenomena, No particular variable needs to be solved for manually. A Modelica tool will have enough information to do that automatically. The language has been designed to allow tools to generate efficient code automatically. The modeling effort is thus reduced considerably since model components can be reused and tedious and error-prone manual manipulations are not needed. The principles of object-oriented modeling and the details of the Modelica language as well as several examples are presented