Angel Pérez de Madrid

Fractional-Order Generalized Predictive Control: Formulation and some properties

This paper deals with the formal formulation of Fractional-Order Generalized Predictive Control, a generalization of GPC that makes use of fractional-order operators in its cost function. A thorough mathematical description of FGPC is given and the main similarities and differences between GPC and FGPC are highlighted.

GPC Control of a Fractional-Order Plant: Improving Stability and Robustness

Abstract This work deals with the use of Generalized Predictive Control (GPC) with fractional order plants. Low integer–order discrete approximations will be used as models to design the controllers. The stability and robustness of the closed loop system will be studied with the Nyquist criterion. Three techniques will be proposed to enhance robustness: the improvement of the model response at low frequencies, the use of the prefilter T(z−-1), and a new recommendation to choose two of the parameters (the control horizon Nu and the error weighting sequence λ) of the GPC controller.

GPC strategies for the lateral control of a networked AGV

The performance of a Networked Control System (NCS) is affected directly and indirectly by transmission time delays and data losses in the communications network. Based on the communications network model, this paper presents the validity of two different predictive control strategies and the study of the network effects on the lateral (guidance) control of an Autonomous Guided Vehicle (AGV) in the presence of sensor noise. Simulation results are presented to validate the proposed strategies.

EXPERIENCES ON AN INTERNET LINK CHARACTERIZATION AND NETWORKED CONTROL OF A SMART WHEEL

The number of control systems connected by local or global communication networks is increasing. In this type of system, the effects of time-varying network-induced delays and data losses are major drawbacks, and in order to achieve an efficient closed-loop system performance, a simple and feasible strategy compensates for these undesirable effects based on the characterization of the experimental network by using real traffic measurements. This paper aims to control a platform called Smart Wheel through Internet by applying this compensation strategy to three different controllers, of fractional and integer orders, based on the previous analysis of the Internet link. Experimental and simulation results are given to show the effectiveness of the proposed control strategies and the advantages of the Internet link modeling.

Development of an inexpensive sensor network for recognition of sitting posture

The aim of this work is the development of a network of wireless devices to determine, along with a time-stamp, postural changes of users that are to be used in personalized learning environments. For this purpose, we have designed a basic low-cost pressure sensor that can be built from components easily available. Several of these basic sensors (of sizes and shapes chosen specifically for the task) are integrated into a posture sensor cushion, which is electronically controlled by an Arduino microcontroller board. This accounts for experiments involving either a single cushion to be used by an individual end-user setting approach or classroom approaches where several of these cushions make up a sensor network via ZigBee wireless connections. The system thus formed is an excellent alternative to other more expensive commercial systems and provides a low-cost, easy-to-use, portable, scalable, autonomous, flexible solution with free hardware and software, which can be integrated with other sensing devices into a larger affect detection system, customizable to cope with postural changes at required time intervals and support single and collective oriented experimentation approaches.

Application of Generalized Predictive Control to a Fractional Order Plant

This paper deals with the use of model predictive controllers (MPC) for controlling fractional order plants. MPC is an industry standard due to its intrinsic ability to handle input and state constraints for large scale multivariable plants. The method is illustrated with Generalized Predictive Control (GPC) and two low order discrete approximations of the fractional order plant (the so-called Chebyshev-Pade and Rational Chebyshev approximations) as model. It is shown how stability, performance and constraints handling can be achieved with ease when dealing with fractional order plants. It is also shown how robustness can be improved by means of a prefilter.Copyright

Explicit predictive control of a hybrid system: A case study: Control of the longitudinal dynamics of a comercial vehicle at very low speed

Many complex systems of theoretical and practical interest can be modeled as hybrid systems, i.e., systems that exhibit both continuous and discrete dynamics. This work focuses on the explicit predictive control of hybrid systems using two free Matlab/Simulink toolboxes designed specifically to synthesize and simulate controllers for this kind of systems. A case study is considered. The system is modeled, from experimental results, after the longitudinal dynamics of a commercial car at low speed. Simulation results are analyzed and a comparative study of both toolboxes is carried out.