This paper focuses on the development of a tool to design nonlinear controllers automatically. This is done by means of an automatic stochastic search: a coevolutive algorithm, inspired by the competitive and symbioti...
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In the high speed range, vector control of rotor flux orientation of an induction machine implements good performance. However, the performance in low speed rang deteriorates because of the inaccurate estimation of ro...
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Applications of bifurcation theory have been employed in all engineering branches, especially in control. In this paper we analyse one control application to delay differential equations based on mentioned bifurcation...
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This paper addresses the optimization of safety instrumented systems design based on a RAMS+C approach using a multi-objective genetic algorithm. The design includes optimization of safety and reliability measures aga...
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In this paper, fusion of neural networks (NNs), genetic algorithms (GAs) and fuzzy logic (FL) is considered by taking account of the advantages of each. In this process neural networks are used for universal approxima...
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In this paper, fusion of neural networks (NNs), genetic algorithms (GAs) and fuzzy logic (FL) is considered by taking account of the advantages of each. In this process neural networks are used for universal approximation, genetic algorithms are used for optimisation of the structure and weights of the neural network and fuzzy logic is used to give directional and priority approach to genetic evolution. Hierarchical fuzzy approach can simultaneously provide a priority and direction of search to a chromosome so as to achieve an optimal or near optimal set of solutions. The proposed approach dynamically adopts the chromosome and maintains uniformity and diversity in the population to simultaneously provide local and global search. Modelling of flexible manipulator is used to demonstrate the performance of the proposed approach.
This paper describes loading polices for the scheduling problem on a multi - product batching processing machine(BPM) which can process a batch of jobs simultaneously with a known and fixed number of jobs and their re...
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This paper describes loading polices for the scheduling problem on a multi - product batching processing machine(BPM) which can process a batch of jobs simultaneously with a known and fixed number of jobs and their ready time. The different jobs are dispatched and sequenced in order to minimize the makespan and maximize the utilization of the servers. As an extension to the basic model of previous work (Fanti et al, 1997)) for BPM scheduling, we build up the model to schedule n jobs on m identical servers in which the optimization procedure results in a complex NP-hard combinatorial problem. Genetic Algorithms(GAs) are applied to solve this scheduling problem where we apply the features of elitist strategy GAs to develop a group of MATLAB functions for solving the BPM scheduling problem. This result is the optimal solution. This experiment demonstrates that GAs can provide a robust search procedure in the optimization of scheduling problem which has high dimensionality, multi-modality, discontinuity and noise (DeJong, 1975).
This paper focuses on the development of a control strategy of a compact stair climbing wheelchair to maintain stable and balance while negotiating staircases in confined spaces for the elderly and disabled. The Visua...
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This paper focuses on the development of a control strategy of a compact stair climbing wheelchair to maintain stable and balance while negotiating staircases in confined spaces for the elderly and disabled. The Visual Nastran 4D is used to develop a simulation models and linked with Matlab platform for control and visual assessment purposes. The challenges are to control front and rear motors as well as tilt angle to ensure system stability and maintain smoothness of the climbing process. PD-Fuzzy controls are developed, tested and associated performances are assessed through intensive visual approach.
This paper present the development of paraplegic quadriceps muscle model based on Functional Electrical Stimulation (FES). A type of modeling, Artificial Neural Network (ANN) were used to investigate the impact of dif...
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This paper present the development of paraplegic quadriceps muscle model based on Functional Electrical Stimulation (FES). A type of modeling, Artificial Neural Network (ANN) were used to investigate the impact of different stimulation frequency, pulse width, pulse duration and settling time on the movement of quadriceps muscle with paraplegia due to a spinal cord injury. 361 training data and 300 testing data set are used in the development of muscle model. Two type of learning approach which is feed-forward backpropagation and cascade-forward backpropagation are considered to develop quadriceps muscle model. The developed model then, validated with clinical data. The model of muscle presented is able to accurately predict muscle torque outputs, along with the variability of the identified parameter. In this study, the feed-forward NN muscle model is found to be the most accurate muscle model representing paraplegic quadriceps muscle model. The established model is then used to predict the behaviour of the underlying system and will be used in the future for the design and evaluation of various control strategies.
The double-link flexible robot manipulator (DLFR) is a highly non-linear system. The development of existing linear models involves a lot of assumptions and approximations in order to reduce the complex calculation. D...
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This work deals with the main control problems found in solar power systems and the solutions proposed in literature. The paper first describes the main solar power technologies, its development status and then descri...
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