Giuseppe Leonardo Cascella

This paper deals with the self-commissioning of electric drives. To improve the performance of the available industrial drives, an on-line auto-tuning based on a hybrid genetic algorithm is proposed. This strategy integrates the simplex method, local searcher, in a genetic framework, global searcher, in order to speed up the convergence. Moreover it is very reliable because experimentally tests each possible solution and consequently the final result is not affected by the accuracy of the motor… Show more

This paper deals with the self-commissioning of electric drives. To improve the performance of the available industrial drives, an on-line auto-tuning based on a hybrid genetic algorithm is proposed. This strategy integrates the simplex method, local searcher, in a genetic framework, global searcher, in order to speed up the convergence. Moreover it is very reliable because experimentally tests each possible solution and consequently the final result is not affected by the accuracy of the motor model. Finally, the proposed on-line hybrid optimization can be embedded as a fully-automated tool without any extra-hardware on industrial drives. Extensive experimental results prove the effectiveness of the proposed approach not only in comparison with conventional commissioning, but also when compared with further accurate hand-calibration. Show less

Structural response of linear multi degree of freedom (MDoF) system subject to random Gaussian dynamic actions is defined by mean of vector and covariance matrix in state space. In case of non-stationary inputs, second-order spectral moments evaluation needs the solution of the so-called Lyapunov matrix differential equation. In this work a numerical scheme for its resolution is proposed, with reference to input processes modeled as linear filtered white noise with time-varying parameters… Show more

Structural response of linear multi degree of freedom (MDoF) system subject to random Gaussian dynamic actions is defined by mean of vector and covariance matrix in state space. In case of non-stationary inputs, second-order spectral moments evaluation needs the solution of the so-called Lyapunov matrix differential equation. In this work a numerical scheme for its resolution is proposed, with reference to input processes modeled as linear filtered white noise with time-varying parameters, which is a common situation in amplitude and frequency variable loads. Numerical computational effort is minimized by taking into account symmetry characteristic of state space covariance matrix. As application of the proposed method a multi-storey building is analyzed to obtain reliability associated to maximum inter-storey exceeded over a given acceptable limit. It is assumed to be subject to seismic input described by a amplitude and frequency nonstationary process, by using a generalized non-stationary Kanai Tajimi seismic model. Structure is assumed as a plane shear frame MDoF system. Structural reliability evaluation is referred to "first time out-crossing" and different numerical benchmarks are considered. Show less

This paper proposes a period representation for modeling the multidrug HIV therapies and an adaptive multimeme algorithm (AMmA) for designing the optimal therapy. The period representation offers benefits in terms of flexibility and reduction in dimensionality compared to the binary representation. The AMmA is a memetic algorithm which employs a list of three local searchers adaptively activated by an evolutionary framework. These local searchers, having different features according to the… Show more

This paper proposes a period representation for modeling the multidrug HIV therapies and an adaptive multimeme algorithm (AMmA) for designing the optimal therapy. The period representation offers benefits in terms of flexibility and reduction in dimensionality compared to the binary representation. The AMmA is a memetic algorithm which employs a list of three local searchers adaptively activated by an evolutionary framework. These local searchers, having different features according to the exploration logic and the pivot rule, have the role of exploring the decision space from different and complementary perspectives and, thus, assisting the standard evolutionary operators in the optimization process. Furthermore, the AMmA makes use of an adaptation which dynamically sets the algorithmic parameters in order to prevent stagnation and premature convergence. The numerical results demonstrate that the application of the proposed algorithm leads to very efficient medication schedules which quickly stimulate a strong immune response to HIV. The earlier termination of the medication schedule leads to lesser unpleasant side effects for the patient due to strong antiretroviral therapy. A numerical comparison shows that the AMmA is more efficient than three popular metaheuristics. Finally, a statistical test based on the calculation of the tolerance interval confirms the superiority of the AMmA compared to the other methods for the problem under study Show less

An innovative variable-structure-systems-based approach for online training of neural network (NN) controllers as applied to the speed control of electric drives is presented. The proposed learning algorithm establishes an inner sliding motion in terms of the controller parameters, leading the command error towards zero. The outer sliding motion concerns the controlled electric drive, the state tracking error vector of which is simultaneously forced towards the origin of the phase space. The… Show more

An innovative variable-structure-systems-based approach for online training of neural network (NN) controllers as applied to the speed control of electric drives is presented. The proposed learning algorithm establishes an inner sliding motion in terms of the controller parameters, leading the command error towards zero. The outer sliding motion concerns the controlled electric drive, the state tracking error vector of which is simultaneously forced towards the origin of the phase space. The equivalence between the two sliding motions is demonstrated. In order to evaluate the performance of the proposed control scheme and its practical feasibility in industrial settings, experimental tests have been carried out with electric motor drives. Crucial problems such as adaptability, computational costs, and robustness are discussed. Experimental results illustrate that the proposed NN-based speed controller possesses a remarkable learning capability to control electric drives, virtually without requiring a priori knowledge of the plant dynamics and laborious startup procedures Show less

A fast adaptive memetic algorithm (FAMA) is proposed which is used to design the optimal control system for a permanent-magnet synchronous motor. The FAMA is a memetic algorithm with a dynamic parameter setting and two local searchers adaptively launched, either one by one or simultaneously, according to the necessities of the evolution. The FAMA has been tested for both offline and online optimization. The former is based on a simulation of the whole system-control system and plant-using a… Show more

A fast adaptive memetic algorithm (FAMA) is proposed which is used to design the optimal control system for a permanent-magnet synchronous motor. The FAMA is a memetic algorithm with a dynamic parameter setting and two local searchers adaptively launched, either one by one or simultaneously, according to the necessities of the evolution. The FAMA has been tested for both offline and online optimization. The former is based on a simulation of the whole system-control system and plant-using a model obtained through identification tests. The online optimization is model free because each fitness evaluation consists of an experimental test on the real motor drive. The proposed algorithm has been compared with other optimization approaches, and a matching analysis has been carried out offline and online. Excellent results are obtained in terms of optimality, convergence, and algorithmic efficiency. Moreover, the FAMA has given very robust results in the presence of noise in the experimental system Show less

This paper proposes to use variable-saturation regulators for Induction Motor (IM) drives operating in field-weakening region, and presents a comparative dynamic-performance analysis between the traditional Indirect Rotor Field Oriented (IRFO) control scheme and a new Stator Flux Oriented – Sliding Mode (SFO-SM) control scheme. The traditional IRFO control scheme has the d-axis current component, torque, rotor flux, and speed loops with four PI-type controllers. The SFO-SM control system is a… Show more

This paper proposes to use variable-saturation regulators for Induction Motor (IM) drives operating in field-weakening region, and presents a comparative dynamic-performance analysis between the traditional Indirect Rotor Field Oriented (IRFO) control scheme and a new Stator Flux Oriented – Sliding Mode (SFO-SM) control scheme. The traditional IRFO control scheme has the d-axis current component, torque, rotor flux, and speed loops with four PI-type controllers. The SFO-SM control system is a Direct Torque Control – Space Vector Modulation (DTC-SVM) scheme with closed loops of torque and stator flux without current PI-type controllers. Both control schemes use regulators with variable-saturation in such a way that maximum dc-bus voltage utilization is reached and overcurrent problems are prevented. The experiments are carried out using dSPACE digital controllers and comparative results show that the SFO-SM controlled IM drive and IRFO one are characterized by similar dynamic responses in spite of structural simplicity of the SFO-SM control scheme Show less

This paper proposes and compares two approaches to defeat the noise due the measurement errors in control system design of electric drives. The former is based on a penalized fitness and two cooperative-competitive survivor selection schemes, the latter is based on a survivor selection scheme which makes use of the tolerance interval related to the noise distribution. These approaches use adaptive rules in parameter setting to execute both the explicit and the implicit averaging in order to… Show more

This paper proposes and compares two approaches to defeat the noise due the measurement errors in control system design of electric drives. The former is based on a penalized fitness and two cooperative-competitive survivor selection schemes, the latter is based on a survivor selection scheme which makes use of the tolerance interval related to the noise distribution. These approaches use adaptive rules in parameter setting to execute both the explicit and the implicit averaging in order to obtain the noise defeating in the optimization process with a relatively low number of fitness evaluations. The results show that the two approaches differently bias the population diversity and that the first can outperform the second but requires a more accurate parameter setting. Show less

This paper presents a robust strategy to increase the reliability of Permanent Magnet Synchronous
Motor drives against encoder or resolver failures. If the position sensor fails, the “failure and recovery
manager” switches the drive in sensorless mode, i.e., the control system uses the speed and position feedback given by a Sliding-Mode observer in place of the sensor. As the accuracy of the sensorless control depends on the tuning of the observer parameters according to the motor… Show more

This paper presents a robust strategy to increase the reliability of Permanent Magnet Synchronous
Motor drives against encoder or resolver failures. If the position sensor fails, the “failure and recovery
manager” switches the drive in sensorless mode, i.e., the control system uses the speed and position feedback given by a Sliding-Mode observer in place of the sensor. As the accuracy of the sensorless control depends on the tuning of the observer parameters according to the motor conditions, the Sliding-Mode observer is periodically tuned during the sensor-based control of the drive. A fast and robust tuning of the observer can be obtained by Hybrid Evolutionary Algorithms. This prevents untimely sensored-to-sensorless switching due to speed transients and allows better performances of the sensorless control when the position sensor fails actually. The results carried out prove that the position sensor failures do not affect the drive operation, and proposed HEA outperforms the standard search algorithms. Show less

This paper proposes a Hierarchical Evolutionary-Deterministic Algorithm (HEDA) for designing square grounding grids. This algorithm performs the design by means of a hierarchical coupling of a real coded evolutionary algorithm and the Hooke-Jeeves algorithm. The design of the grounding grid is here formalized as a min-max problem. The maximization part is the search of the most dangerous point for a given topological structure, the minimization part is the optimization of the topological… Show more

This paper proposes a Hierarchical Evolutionary-Deterministic Algorithm (HEDA) for designing square grounding grids. This algorithm performs the design by means of a hierarchical coupling of a real coded evolutionary algorithm and the Hooke-Jeeves algorithm. The design of the grounding grid is here formalized as a min-max problem. The maximization part is the search of the most dangerous point for a given topological structure, the minimization part is the optimization of the topological parameter (compression ratio) of the grounding grid. The solution of the system of partial differential equations related to the spatial distribution of the current field is carried out by the Galerkin method. The program gives good results in terms of accuracy and computational complexity. Show less

This paper presents a novel stator flux oriented induction motor control scheme. It utilises a sliding-mode controller in the stator flux control loop. The existence condition of sliding mode control is derived, and chattering suppression at steady-state is also considered. A proportional controller is used in the torque control loop to simplify the control scheme without compromising performance. Design formulas are given for the controller parameters. They are not based on the mathematical… Show more

This paper presents a novel stator flux oriented induction motor control scheme. It utilises a sliding-mode controller in the stator flux control loop. The existence condition of sliding mode control is derived, and chattering suppression at steady-state is also considered. A proportional controller is used in the torque control loop to simplify the control scheme without compromising performance. Design formulas are given for the controller parameters. They are not based on the mathematical motor model but only need rated parameters. Experimental results are shown to prove the effectiveness of the control strategy in transient and steady state operations. Show less