PID autotuning using neural networks and model reference adaptive control

This paper describes the application of artificial neural networks for automatic tuning of PID controllers using the Model Reference Adaptive Control approach. The effectiveness of the proposed method is shown through a simulated application.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.

Advanced methods in adaptive control for industrial applications

This volume is based on a seminar concerned with advanced methods in adaptive control for industrial applications which was held in Prague in May 1990 and which brought together experts in the UK and Czechoslovakia in order to suggest solutions to specific current and anticipated problems faced by industry.

Mediterranean agriculture under climate change: adaptive capacity, adaptation, and ethics

In the coming decades, the Mediterranean region is expected to experience various climate impacts with negative consequences on agricultural systems and which will cause uneven reductions in agricultural production. By and large, the impacts of climate change on Mediterranean agriculture will be heavier for southern areas of the region. This unbalanced distribution of negative impacts underscores the significance and role of ethics in such a context of analysis. Consequently, the aim of this article is to justify and develop an ethical approach to agricultural adaptation in the Mediterranean and to derive the consequent implications for adaptation policy in the region. In particular, we define an index of adaptive capacity for the agricultural systems of the Mediterranean region on whose basis it is possible to group its different sub-regions, and we provide an overview of the suitable adaptation actions and policies for the sub-regions identified. We then vindicate and put forward an ethical approach to agricultural adaptation, highlighting the implications for the Mediterranean region and the limitations of such an ethical framework. Finally, we emphasize the broader potential of ethics for agricultural adaptation policy.