Browsing by Author "Oliveira, P. B. de Moura"
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- An evolutionary approach to robot structure and trajectoryPublication . Pires, E. J. Solteiro; Tenreiro Machado, J. A.; Oliveira, P. B. de MouraThis paper proposes a genetic algorithm to generate a robot structure and the required manipulating trajectories. The objective is to minimize the space/time ripple in the workspace, while optimizing the mechanical structure.
- An evolutionary optimization for robotic manipulatorsPublication . Pires, E. J. Solteiro; Tenreiro Machado, J. A.; Oliveira, P. B. de MouraThis work proposes a real time algorithm to generate a trajectory for a 2-link planar robotic manipulator. The objective is to minimize the space/time ripple and the energy requirements or the time duration in the robot trajectories. The proposed method uses an off-line genetic algorithm to calculate every possible trajectory between all cells of the workspace grid. The resultant trajectories are saved in several trees. Then any trajectory resquested is constructed, in real time, from these trees. The article presents the results for several experiments.
- Automated Synthesis Procedure of RF Discrete Tuning Differential Capacitance CircuitsPublication . Mendes, Luís; Pires, E. J. Solteiro; Vaz, João C.; Rosário, Maria J.; Oliveira, P. B. de Moura; Machado, J. A. Tenreiro; Ferreira, N. M. FonsecaThe paper presents a RFDSCA automated synthesis procedure. This algorithm determines several RFDSCA circuits from the top-level system specifications all with the same maximum performance. The genetic synthesis tool optimizes a fitness function proportional to the RFDSCA quality factor and uses the epsiv-concept and maximin sorting scheme to achieve a set of solutions well distributed along a non-dominated front. To confirm the results of the algorithm, three RFDSCAs were simulated in SpectreRF and one of them was implemented and tested. The design used a 0.25 mum BiCMOS process. All the results (synthesized, simulated and measured) are very close, which indicate that the genetic synthesis method is a very useful tool to design optimum performance RFDSCAs.
- Design of Radio-Frequency Integrated CMOS Discrete Tuning Varactors Using the Particle Swarm Optimization AlgorithmPublication . Pires, E.J. Solteiro; Mendes, Luís; Oliveira, P. B. de Moura; Tenreiro Machado, J. A.; Vaz, João C.; Rosário, Maria J.This paper presents an automated design procedure of radiofrequency integrated CMOS discrete tuning varactors (RFDTVs). This new method use the maximin and the particle swarm optimization (PSO) algorithms to promote well distributed non-dominated fronts in the parameters space when a single-objective function is optimized. The fitness function used in the search tool is proportional to the RFDTV quality factor. The outcome of the automated design method comprises a set of RFDTV circuits, all having the same maximum performance. Each solution, which corresponds to one RFDTV circuit, is defined by the number of cells and by the circuit components values. This approach allows the designer to choose among several possible circuits the one that is easier to implement in a given CMOS process. To validate the effectiveness of the synthesis procedure proposed in this paper (PSO-method) comparisons with a design method based on genetic algorithms (GA-method) are presented. A 0.18 μm CMOS radio-frequency binary-weighted differential switched capacitor array (RFDSCA) was designed and implemented (the RFDSCA is one of the possible topologies of the RFDTVs). The results show that both design methods are in very good agreement. However, the PSO technique outperforms the GA-method in the design procedure run time taken to accomplish the same performance results.
- Fractional dynamics in genetic algorithmsPublication . Pires, E. J. Solteiro; Tenreiro Machado, J. A.; Oliveira, P. B. de MouraThis paper investigate the fractional-order dynamics during the evolution of a Genetic Algorithm (GA). In order to study the phenomena involved in the GA population evolution, themutation is exposed to excitation perturbations during some generations and the corresponding fitness variations are evaluated. Three similar functions are tested to measure its influence in GA dynamics. The input and output signals are studied revealing a fractional-order dynamic evolution.
- Fractional Dynamics in Particle Swarm OptimizationPublication . Pires, E. J. Solteiro; Tenreiro Machado, J. A.; Oliveira, P. B. de Moura; Reis, CecíliaThis paper studies the fractional dynamics during the evolution of a Particle Swarm Optimization (PSO). Some swarm particles of the initial population are randomly changed for stimulating the system response. After the result is compared with a reference situation. The perturbation effect in the PSO evolution is observed in the perspective of the time behavior of the fitness of the best individual position visited by the replaced particles. The dynamics is investigated through the median of a sample of experiments, while adopting the Fourier analysis for describing the phenomena. The influence of the PSO parameters upon the global dynamics is also analyzed by performing several experiments for distinct values.
- Fractional order dynamical phenomena in a GAPublication . Pires, E. J. Solteiro; Tenreiro Machado, J. A.; Oliveira, P. B. de MouraThis work addreses the fractional-order dynamics during the evolution of a GA, which generates a robot manipulator trajectory. In order to investigate the phenomena involved in the GA population evolution, the crossover is exposed to excitation perturbations and the corresponding fitness variations are evaluated. The input/output signals are studied revealing a fractional-order dynamic evolution, characteristic of a long-term system memory.
- Fractional order dynamics in a GA plannerPublication . Pires, E. J. Solteiro; Tenreiro Machado, J. A.; Oliveira, P. B. de MouraThis work addresses the signal propagation and the fractional-order dynamics during, the evolution of a genetic algorithm (GA), for generating a robot manipulator trajectory. The GA objective is to minimize the trajectory space/time ripple without exceeding the torque requirements. In order to investigate the phenomena involved in the GA population evolution, the mutation is exposed to excitation perturbations and the corresponding fitness variations are evaluated. The chaos-like noise and the input/output signals are studied revealing a fractional-order dynamics, characteristic of a long-term system memory.
- Fractional order dynamics in a Genetic AlgorithmPublication . Pires, E. J. Solteiro; Tenreiro Machado, J. A.; Oliveira, P. B. de MouraThis work addresses the fractional-order dynamics during the evolution of a Genetic Algorithm population (GA) for generating a robot manipulator trajectory. The GA objective is to minimize the trajectory space/time ripple without exceeding the torque requirements. In order to investigate the phenomena involved in the GA population evolution, the mutation is exposed to excitation perturbations and the corresponding fitness variations are evaluated. The input/output signals are studied revealing a fractional-order dynamic evolution, characteristic of a long-term system memory.
- Fractional Particle Swarm OptimizationPublication . Pires, E. J. Solteiro; Tenreiro Machado, J. A.; Oliveira, P. B. de MouraThe paper addresses new perspective of the PSO including a fractional block. The local gain is replaced by one of fractional order considering several previous positions of the PSO particles. The algorithm is evaluated for several well known test functions and the relationship between the fractional order and the convergence of the algorithm is observed. The fractional order influences directly the algorithm convergence rate demonstrating a large potencial for developments.
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