Robust control for nonlinear discrete-time systems with quantitative input to state stability requir

In this paper, we consider state feedback robust control problems for discrete-time nonlinear systems subject to disturbances. The objective of the control is to minimize a performance function while guaranteeing a prescribed quantitative input to state stability (ISS) property for the closed-loop systems. By introducing the concept of ISS control invariant set, a sufficient condition for the problem to be feasible is given. Built on the sufficient condition, a computationally efficient control design algorithm based on one-step min-max optimization is developed. An example is given to illustrate the proposed strategy. Copyright © 2007 International Federation of Automatic Control All Rights Reserved

Conditions for triangular decoupling control

The main purpose of this article is to explore the relationship of two existing conditions for the triangular decoupling problem. The first one is the triangular-diagonal-dominance condition proposed by Hung and Anderson. The second one is the stable coprime factorisation-described condition proposed by Gomez and Goodwin, which has been proven as a necessary and sufficient condition for the triangular decoupling problem. This article proves that the two conditions are actually equivalent. It also provides easy-to-use criteria for assessment of the solvability of the triangular decoupling problem

Influence of the microvasculature on oxygen transport in human brain tissue

This paper was presented at the 2nd Micro and Nano Flows Conference (MNF2009), which was held at Brunel University, West London, UK. The conference was organised by Brunel University and supported by the Institution of Mechanical Engineers, IPEM, the Italian Union of Thermofluid dynamics, the Process Intensification Network, HEXAG - the Heat Exchange Action Group and the Institute of Mathematics and its Applications.Two numerical methods are presented for simulating a micro-stroke: a discretised model and a continuum model, both developed for simulating coupled flow and oxygen transport to the microvasculature. The discrete model treats the microvasculature and the tissue perfusion as two coupled sub-systems governed by Poiseulle flow and mass transport equation respectively. The continuum model regards the blood passage as a porous media flow and deals with mass transport in terms of a two phase flow system. In our simulations, it has been shown that the microvascular structure has a strong influence on the localized oxygen transport behaviour, contributing to more complex patterns in the tissue oxygen concentration than those found by assuming continuum behaviour

Optimum Experimental Design applied to MEMS accelerometer calibration for 9-parameter auto-calibration model

© 2015 IEEE. Optimum Experimental Design (OED) is an information gathering technique used to estimate parameters, which aims to minimize the variance of parameter estimation and prediction. In this paper, we further investigate an OED for MEMS accelerometer calibration of the 9-parameter auto-calibration model. Based on a linearized 9-parameter accelerometer model, we show the proposed OED is both G-optimal and rotatable, which are the desired properties for the calibration of wearable sensors for which only simple calibration devices are available. The experimental design is carried out with a newly developed wearable health monitoring device and desired experimental results have been achieved

Control of multivariable Hammerstein systems by using feedforward passivation

This paper presents a new control method for processes which can be described by Hammerstein models. The control design is based on the concept of passive systems. The proposed method is based on feedforward passivation and thus can be applied to nonminimum phase processes and/or processes of high relative degree. A synthesis technique for marginally stable positive real systems has been developed to achieve offset free control. The new control design can be easily implemented by solving a set of linear matrix inequalities. The proposed approach is illustrated using the example of an acid-base pH control problem

A new approach to applying discrete sliding mode control to 2D systems

Sliding mode control has been applied previously to a specific form of 2D systems (Roesser model). In this paper a new approach (ID vectorial form) is introduced for this problem. Using ID form to represent 2D systems can be used as an alternative strategy to reduce the inherent complexity of 2D systems and their applications. Unlike Wave Advanced Model (WAM) form (proposed by Porter and Aravena), the suggested ID vectorial form, in this paper, has invariable dimension and consequently can be converted to regular form for sliding mode control (SMC). In this paper, the first Fornasini and Marchesini (FM) model of 2D systems which is a second order recursive form is considered. Meantime, the suggested method can be simply deployed to other first or second order 2D models. ©2013 IEEE

Laboratory demonstration for model predictive multivariable control with a coupled drive system

Teaching multivariable control usually involves a certain level of mathematical sophistication and hence requires some labaratorial exemplification of the material given in formal lectures. This paper reports on a hands-on approach to multivariable control education via the implementation of a model predictive controller on a two-input, two output coupled drive apparatus. This scaled-down system represents many industrial processes while provides an excellent set-up for demonstrating the cross-coupled effects in multi-input multi-output systems. Here, a model predictive controller (MPC) is developed and implemented on the basis of a constrained optimization problem to show control performance via the belt tension and velocity outputs, demonstrate the decoupling capability, and also illustrate such issues as control input saturation, the selection of operating point, reference inputs, and system robustness to external disturbance and varying parameters. The implementation is based on Labview and MATLAB Model Predictive Control Toolbox. ©2010 IEEE. Model predictive Control

Integral controller design for nonlinear systems using inverse optimal control

This paper proposes an integral controller design scheme for nonlinear systems based on optimal control and the passivity theorem in order to suppress the effect of external disturbances. The main strategy is to augment an optimal controller with a PI type controller. To guarantee the proposed controller has a desired stability margin, the passivity-based design method is introduced. Here, the inverse optimal control technique is employed to avoid the need of solving a Hamilton-Jacobi equation. An illustrative example is given to show the design procedure and the controller effectiveness. © 2008 IEEE

Design of a Variable Reactor for Load Balancing and Harmonics Elimination

This paper presents the design of a variable inductor with a rotational magnetic core whose position is controlled in a closed-loop system. This magnetic structure facilitates the impedance changes which may be used for load balancing, harmonics elimination, transient response improvement, and as a controlled reactor in static VAr compensation (SVC). The design of the inductor and analysis of its impedance change caused by positioning a movable element are carried out by using the finite element method. As a result, the variation range of the impedance is determined. The proposed variable inductor is compared with a typical SVC reactor. The results show good performances in static var compensation with higher reliability and no harmonics generated. For closed-loop control, a secondorder sliding mode controller is designed for position control of the rotating core via a DC motor. Simulation results of the proposed system present highly robust and accurate responses without control chattering in face of nonlinearities and disturbances

Neural Network Based Diagonal Decoupling Control of Powered Wheelchair Systems

This paper proposes an advanced diagonal decou- pling control method for powered wheelchair systems. This control method is based on a combination of the systematic diagonaliza- tion technique and the neural network control design. As such, this control method reduces coupling effects on a multivariable system, leading to independent control design procedures. Using an obtained dynamic model, the problem of the plants Jacobian calculation is eliminated in a neural network control design. The effectiveness of the proposed control method is verified in a real-time implementation on a powered wheelchair system. The obtained results confirm that robustness and desired performance of the overall system are guaranteed, even under parameter uncertainty effects