Adel A. A. El-Gammal

A modified design of PID controller for DC motor drives using Particle Swarm Optimization PSO

This paper presents the application of a new Particle swarm optimization technique for adjusting the gains of a PID speed controller adaptively to give the minimum integral absolute error between the speed demand and the output response, minimum settling time, and minimum overshoot for a separately excited dc drive. The new technique converts all objective functions to a single objective function by deriving a single aggregate objective function using specified or selected weighting factors. Since the optimal PID controller parameters are dependent on the selected weighting factors, the weighting factors was also treated as dynamic optimizing parameters within the Particle Swarm Optimization as a dual optimization and global selection of PID controller optimal parameters as well as best set of weighting factors. Computer simulations and experimental results show that the performance of the optimal PID controller is better than that of the traditional PID controller.

Adaptive Tuning of a PID Speed Controller for DC Motor Drives Using Multi-objective Particle Swarm Optimization

In this paper, a control scheme based on Multi-Objective Particle Swarm optimization MOPSO is proposed, which is able to tune the PID controller parameters simultaneously in order to find the set of trade-off optimal solutions that is called Pareto-set optimization solution of the conflicting objective functions for dc motor drive system. Multi Objective Particle Swarm Optimization MOPSO is implemented to tackle a number of conflicting goals that define the optimality problem. This paper deals with five conflicting objective functions. These conflicting functions are:1. Minimize the maximum overshoot,2. Minimize the rise time,3. Minimize speed tracking error, 4. Minimize the steady state error, and 5. Minimize the settling time,

A novel discrete multi-objective Particle Swarm Optimization (MOPSO) of optimal shunt power filter

In this paper, a novel discrete optimization approach is developed to optimally solve the optimization problem of power system shunt filter design based on Discrete Multi Objective Particle Swarm Optimization MOPSO technique to ensure harmonic current reduction and noise mitigation on electrical utility grid. In this novel optimization approach, Multi Objective Particle Swarm Optimization MOPSO is implemented to tackle a number of conflicting goals that define the optimality problem. This paper deals with three conflicting objective functions. These conflicting functions are: 1. Minimum harmonic current penetration into the electric grid system, 2. Maximum harmonic current absorption by the harmonic power filter, 3. Minimum harmonic voltage distortion at the point of common coupling, Throughout the optimization process, all power filter parameters are being treated as either continuous or discrete variables. The shunt power filter design and optimization is performed over a specified set of discrete dominant offending harmonics.

An integral squared error -ISE optimal parameters tuning of modified PID controller for industrial PMDC motor based on Particle Swarm Optimization-PSO

The paper presents the optimal tuning of the modified PID controller gains for high performance permanent magnet PMDC industrial motor drives based on Particle Swarm optimization PSO. The modified PID controller implements another control parameter of the integral of the total error square. This will smooth the starting torque; enhance acceleration and dynamic tracking of the reference speed. The proposed dynamic tri-loop controller utilizes the motor speed error (eω), the armature current deviation (eI) from its maximum or “specified” allowable current level, dynamic current ripple error (eR), and the total error square as inputs to the PSO search algorithm. The proposed Tuned modified PID controller is based on the minimization of the total system error. The control voltage signal is used to regulate the firing delay angle α of the 3-phase controlled rectifier bridge.

Power efficient PID controller of wind driven induction generation single-phase induction motors for electric energy saving applications

The paper presents a novel self adjusting wind energy utilization scheme using a modified single phase operation of the three phase induction generator supplemented by a voltage stabilization switched filter compensation scheme. The series-parallel switched capacitor filter scheme is controlled by a dynamic Particle Swarm Optimization PSO error driven self adjusting controller to ensure voltage stabilization, minimum impact of the electric load excursions and wind variations on terminal voltage. The paper presents a family of novel switched smart filter compensated devices using Green Plug Filter Compensator GPFC devices for small single phase induction motors. The GPFC devices are equipped with a dynamic online error driven optimally tuned controller that ensures improved power factor, reduced feeder losses, stabilized voltage, minimal current ripples and efficient energy utilization/conservation with minimal impact on the host electric grid security and reliability.

A novel Particle Swarm optimization PSO tuning scheme for PMDC motor drives controllers

The paper presents the novel application of Particle Swarm optimization PSO for the optimal tuning of PID controller for high performance permanent magnet PMDC industrial motor drives. This will smooth the starting torque; enhance acceleration and dynamic tracking of the reference speed. The permanent magnet PMDC motor drive is fed from a 3-phase AC supply via a six pulse thyristor controlled rectifier. The dynamic error driven controller regulates the firing delay angle (α) using the Particle Swarm optimization PSO tuning PID block. The proposed dynamic tri-loop controller utilizes the motor speed error (ew), the armature current deviation (eI) from its maximum or “specified” allowable current level and dynamic current ripple error (eR) as inputs to the PSO gain search algorithm. The control voltage signal is used to regulate the firing delay angle α of the 3-phase controlled rectifier bridge. The proposed Tuned PID controller is based on the minimization of the absolute of total Error.

A discrete particle swarm optimization technique (DPSO) for power filter design

In this paper, a novel optimization approach is developed to optimally solve the problem of power system shunt filter design based on discrete particle swarm optimization (DPSO) technique to ensure harmonic reduction and noise mitigation on the electrical utility grid. The proposed power filter design is based on the minimization of a multi objective function. The main power filter objective function includes minimum harmonic current penetration into the electric grid system, maximum harmonic current absorption by the harmonic power filter, minimum harmonic voltage distortion at the point of common coupling, and minimum current harmonic injected in the system and also in same time ensure a dynamically maximum current in the shunt power filter. Throughout the optimization process, all parameters of the power filter are being treated as continuous and discrete variables. The power filter design and optimization is performed over a specified set of discrete dominant offending harmonics. Since the optimal power filter parameters are dependent on the selected weighting factors, the weighting factors was also treated as dynamic optimizing parameters within the Particle Swarm Optimization as a dual optimization and global selection of shunt power filters optimal parameters as well as best set of weighting factors.

A variable structure sliding mode Particle Swarm Optimization-PSO optimal regulating controller for industrial PMDC motor drives

the paper presents the novel application of Particle Swarm optimization PSO for the optimal tuning of an incremental sliding mode variable structure controller for high performance permanent magnet PMDC industrial motor drives. The proposed dynamic tri-loop controller utilizes the motor speed error (eω), the armature current deviation (eI) from its maximum or “specified” allowable current level and dynamic current ripple error (eR) as inputs to the PSO search algorithm tuned variable structure incremental sliding mode controller. The proposed Tuned incremental sliding mode variable structure controller is based on the minimization of the absolute of total Error. The control voltage signal is used to regulate the firing delay angle α of the 3-phase controlled rectifier bridge.

Design of self-excited induction generators for wind applications

Wind energy schemes have the potential to substantially reduce the consumption of fossil fuels used in the production of electric energy. The self-excited induction generator has found renewed interest as a low maintenance wind generator for standalone and grid integrated applications. This paper will present a full analytical model of the dynamic response and steady state operation of the induction generator. Design equations describing self-excitation, loss of excitation and voltage regulation are presented. These closed form analytical solutions can be part of an integrated design process and intelligent control design for a self-excited induction generator allowing maximum wind energy capture.

A novel efficient PSO-self regulating PID controller for hybrid PV-FC-diesel-battery micro grid scheme for village/resort electricity utilization

The paper presents the dynamic modeling and coordinated control strategy for an integrated micro grid scheme using Photo Voltaic PV, Fuel Cell FC, and backup Diesel generation with additional battery backup system. The integrated scheme is fully stabilized using a novel FACTS based green filter compensators that ensures stabilized DC bus voltage, minimal inrush current conditions, and load excursions. The diesel generator set is only utilized when the demand energy exceeds the PV, FC and battery sources capacity within specified operational levels to ensure highest efficient operation of the integrated renewable energy sources with the diesel engine. The paper presents a novel application of Multi Objective Particle Swarm Optimization MOPSO for PID controller parameters tuning to control the 6-pulse controlled rectifier converter, dynamic filter/capacitor compensation DFC and the Green Power Filter GPF AC and DC schemes using real time dynamic self regulating error tracking.