Alberto Herreros

Design of PID-type controllers using multiobjective genetic algorithms

The design of a PID controller is a multiobjective problem. A plant and a set of specifications to be satisfied are given. The designer has to adjust the parameters of the PID controller such that the feedback interconnection of the plant and the controller satisfies the specifications. These specifications are usually competitive and any acceptable solution requires a tradeoff among them. An approach for adjusting the parameters of a PID controller based on multiobjective optimization and genetic algorithms is presented in this paper. The MRCD (multiobjective robust control design) genetic algorithm has been employed. The approach can be easily generalized to design multivariable coupled and decentralized PID loops and has been successfully validated for a large number of experimental cases.

Age-related changes in P wave morphology in healthy subjects

BackgroundWe have previously documented significant differences in orthogonal P wave morphology between patients with and without paroxysmal atrial fibrillation (PAF). However, there exists little data concerning normal P wave morphology. This study was aimed at exploring orthogonal P wave morphology and its variations in healthy subjects.Methods120 healthy volunteers were included, evenly distributed in decades from 20–80 years of age; 60 men (age 50+/-17) and 60 women (50+/-16). Six-minute long 12-lead ECG registrations were acquired and transformed into orthogonal leads. Using a previously described P wave triggered P wave signal averaging method we were able to compare similarities and differences in P wave morphologies.ResultsOrthogonal P wave morphology in healthy individuals was predominately positive in Leads X and Y. In Lead Z, one third had negative morphology and two-thirds a biphasic one with a transition from negative to positive. The latter P wave morphology type was significantly more common after the age of 50 (P < 0.01). P wave duration (PWD) increased with age being slightly longer in subjects older than 50 (121+/-13 ms vs. 128+/-12 ms, P < 0.005). Minimal intraindividual variation of P wave morphology was observed.ConclusionChanges of signal averaged orthogonal P wave morphology (biphasic signal in Lead Z), earlier reported in PAF patients, are common in healthy subjects and appear predominantly after the age of 50. Subtle age-related prolongation of PWD is unlikely to be sufficient as a sole explanation of this finding that is thought to represent interatrial conduction disturbances. To serve as future reference, P wave morphology parameters of the healthy subjects are provided.

MRCD: a genetic algorithm for multiobjective robust control design

Abstract A genetic algorithm (GA) for the class of multiobjective optimization problems that appears in the design of robust controllers is presented in this paper. The design of a robust controller is a trade-off problem among competitive objectives such as disturbance rejection, reference tracking, stability against unmodeled dynamics, moderate control effort and so on. However, general methodologies for solving this class of design problems are not easily encountered in the literature because of the complexity of the resultant multiobjective problems. In this paper, a recently developed class of GAs, multiobjective GAs, are used to solve robust control design problems. Here, a new algorithm, called multiobjective robust control design, has been proposed. The structure and operators of this algorithm have been specifically developed for control design problems. The performace of the algorithm is evaluated by solving several test cases and is also compared to the standard algorithms used for the multiobjective design of robust controllers.

Analysis of changes in the beat-to-beat P-wave morphology using clustering techniques

Several pathologies related to the atrial electrical activity can be detected in the electrocardiogram P-wave. A study on the beat-to-beat P-wave morphology changes of 89 ECG signals is performed in this article. An algorithm based on the embedding space techniques has been used to extract the P-wave information of the ECG. The P-waves obtained in several of these ECGs exhibit intermittent morphology changes. The morphologies have been classified by using the K-means clustering algorithm. The mechanism behind different P-wave morphologies and its possible pathophysiological importance remains to be clarified.

Design of PID Controllers Using Multiobjective Genetic Algorithms

Abstract The design or a PID controller is a multiobjective problem. A plant and a set of specifications to be satisfied are given. The designer has to determine a controller such that the feedback interconnection of the plant and the PID controller satisfies the specifications. The specifications are usually competitive and any acceptable solution requires a trade-off between the conflicting objectives. In this paper, we present an approach for the design of PID controllers with multiple objectives using genetic algorithms.

Interpretability-accuracy improvement in a neuro-fuzzy ART based model of a DC motor

Abstract The aim of this paper is to propose a general methodology applicable to any rule based fuzzy model generated by any precise or linguistic fuzzy algorithm to improve the linguistic-accuracy trade-off. Here, the neuro-fuzzy system FasArt (Fuzzy Adaptive System ART based) is used for its proven model capabilities, as shown in previous papers and works. If does, however, have the usual drawbacks, from the linguistic point of view, of most fuzzy modeling methods found in the scientific literature. A fuzzy model of a DC motor is generated by FasArt, whose performance is a good estimation of the motors behavior, then this performance is improved by a better interpretability of the knowledge attained and stored by this fuzzy model. The main idea behind this approach is to find a fuzzy model with enough accuracy and an adequate capacity of explanation or interpretability of its data acquired knowledge. The modeling process can thus be seen as knowledge extraction in human or linguistic terms: from a numeric level (data) to a symbolic one (linguistic fuzzy rules).

An Algorithm for Phase-Space Detection of the P Characteristic Points

A new algorithm, based on embedding phase space, to detect the P-wave characteristic points of an ECG signal is reported in this paper. The multi-lead ECG is transformed into points of an embedding phase space where similar ECG morphologies are converted into phase space points that are close using some distance measure. The algorithm is robust with respect to the type of selected characteristic points (onset, peak and end), morphology changes, baseline oscillations and high frequency noise. The performance of the algorithm has been successfully validated using both simulated and real ECG signals.

A Direct Search Algorithm for Global Optimization

A direct search algorithm is proposed for minimizing an arbitrary real valued function. The algorithm uses a new function transformation and three simplex-based operations. The function transformation provides global exploration features, while the simplex-based operations guarantees the termination of the algorithm and provides global convergence to a stationary point if the cost function is differentiable and its gradient is Lipschitz continuous. The algorithm’s performance has been extensively tested using benchmark functions and compared to some well-known global optimization algorithms. The results of the computational study show that the algorithm combines both simplicity and efficiency and is competitive with the heuristics-based strategies presently used for global optimization.

PARAMETER IDENTIFICATION OF A CAR SUSPENSION SYSTEM USING NON-INTRUSIVE SIGNALS

Abstract The suspension system of a car is of vital importance for the safety of its occupants. Therefore, it is very important to develop reliable tests for inspecting the condition of its components. A simple model to identify the parameters of a car suspension system is proposed in this paper. It is proven that these parameters are identifiable by using only non-intrusive signals. Unfortunately, the application of conventional identification methods produces suspension parameters without physical meaning. The reason is the loss of consistency of the estimators due to the presence of unknown noise and unmodeled dynamics. In order to avoid this effect, the distance between the magnitude of the true and the predicted power spectrum density of the output signal is chosen as the objective to be minimized on a bounded search space with physical meaning. The optimization problem is solved using the MRCD genetic algorithm. Promising results have been obtained for several real-world cases.

Design of controllers for parametric uncertain systems. A two-step approach using genetic algorithms

Abstract Most industrial processes are modeled as linear time invariant systems with parametric uncertainties. The design of a robust controller for these plants is formulated as a multiobjective min-max problem where certain performance objectives are minimized with respect to the controller and maximized with respect to the uncertainties. The solution of such a problem is extremely difficult. An approximated two-step approach is proposed in this paper. In the first step, an auxiliary multiobjective minimization problem is solved. The solution to this problem is the set of Pareto optimal controllers. In the second step, these controllers are checked for the worst case of parametric uncertainty by solving a multiobjective maximization problem. The MRCD genetic algorithm is used to solve both multiobjective optimization problems.