The development of an experimental environment with interactive features, suitable both for the reinforcement of undergraduate level teaching of control theory and also for graduate-level research work in the field of intelligent control is described. The students are prepared for the experiment by an interactive session on the Internet before coming into the laboratory. The hardware and the so...

In this paper, a simple and effective scheme for tuning of fuzzy PI-PD controller based on fuzzy logic is proposed. Here the input scaling factors are tuned online by gain updating factors where values are determined by rule base with error and change in error as inputs according to the required controlled process. The performance comparison of conventional fuzzy logic controller, auto-tuned fu...

Neuro-fuzzy classi cation systems make it possible to obtain a suitable fuzzy classi er by learning from data. Nevertheless, in some cases the derived rule base is hard to interpret. In this paper we discuss some approaches to improve the interpretability of neuro-fuzzy classi cation systems. We present modi ed learning strategies to derive fuzzy classi cation rules from data, and some methods ...

In this paper, a fuzzy logic control system was constructed for controlling the green time length for a real single intersection with multiple lanes, turns, and two pedestrian crossings. Control of pedestrian crossingd was achieved by assigning pedestrian crossingd into related light phases, which were controlled by a fuzzy logic controller. An evolutionary algorithm was employed to generate th...

We propose a flexible decision support scheme which could be used in managing the wage negotiation between employers and employees. This scheme uses fuzzy inference systems and game theory concepts in arriving at decisions on future wage increase which could be more mutually agreeable. For example, rather than specifying 5% yearly increase of wages, we propose that the uncertain factors which a...

Fuzzy set theory allows for the inclusion of vague human assessments in computing problems. Also, it provides an effective means for conflict resolution of multiple criteria and better assessment of options. Fuzzy rule interpolation offers a useful means for enhancing the robustness of fuzzy models by making inference possible in sparse rule-based systems. However, in real-world applications of...

Weather operations play an important and integral part of planning, execution and sustainment of mission operations. In this paper, a neuro-fuzzy hybridization technique is applied to model the weather operations and predict its impact on the effectiveness of air tasking operations and missions. Spatiotemporal weather data from various meteorological sources are collected and used as the input ...

Interpretable fuzzy systems are very desirable for human users to study complex systems. To meet this end, an agent based multi-objective approach is proposed to generate interpretable fuzzy systems from experimental data. The proposed approach can not only generate interpretable fuzzy rule bases, but also optimize the number and distribution of fuzzy sets. The trade-off between accuracy and in...

This paper proposes a rule base simplification method for fuzzy systems. The method is based on aggregation of rules with different linguistic values of the output for identical permutations of linguistic values of the inputs which are known as inconsistent rules. The simplification removes the redundancy in the fuzzy rule base by replacing each group of inconsistent rules with a single equival...