Francis A. Okou

Strategies to Accelerate Harmonic Minimization in Multilevel Inverters Using a Parallel Genetic Algorithm on Graphical Processing Unit

Multilevel inverters form a popular class of high-power inverters due to their high-voltage operation, high efficiency, low switching losses, and low electromagnetic interference. Metaheuristics, such as the genetic algorithm (GA), have been used with success to compute optimal switching angles for multilevel inverters with many dc sources while minimizing several harmonics. However, these methods are computationally demanding and cannot easily be used for real-time control. In this letter, a parallel implementation of the GA on graphical processing unit (GPU) is proposed in order to accelerate the computation of the optimal switching angles for multilevel inverters with varying dc sources. Four approaches to parallelize and speed up the computation of the total harmonic distortion are presented and compared. By exploiting the massively parallel architecture of GPUs, the computation of optimal angles is accelerated by a factor of 469× compared to a sequential execution on CPU. The proposed solution optimizes multilevel inverters with 100 variable dc sources while minimizing the first 100 harmonics in 164 ms.

Adaptive backstepping control of a wheeled mobile robot

This paper proposes an adaptive nonlinear controller to stabilize an autonomous wheeled mobile robot. The controller equations are obtained following a backstepping approach. The robot model is divided into two parts: a state space model with intermediate control inputs and algebraic nonlinear equations relating the true and the intermediate control inputs. The robot parameters are assumed unknown. First, a suitable change of variable is applied to the traditional robot dynamics to reveal the strict feedback structure of this state space model. ext, a three-step adaptive backstepping control design method is applied to obtain the intermediate control input expressions. Finally the true control inputs are found by solving iteratively the nonlinear equations that relates intermediate and true control inputs. The adaptation algorithms are based on the projection method and guarantee that estimated parameters converge and remain inside predefined domains. The proposed design strategy is tested in simulation. The results show good tracking performances despite large parameter variations.

A novel modelling approach for decentralized voltage and speed control of multi-machine power systems

This paper proposes a novel modelling approach of multi-machine power systems for the design of decentralized multi-variable voltage and speed regulators. In this approach, each generator views the rest of the network as effective instantaneous impedance. The new model contains time-varying parameters representing the interactions among the system generators. The time-varying parameters depend only on the operating conditions of the power system and are independent of the structure of the latter. The advantages of this model are its simplicity, the fact that each generators terminal voltage and rotor speed are expressed only in terms of local measurable variables and its capability to model inter-machines interactions. A decentralized multi-input multi-output (MIMO) non-linear voltage and speed regulator based on the new model is then used to dampen oscillations in a four-machine power system and to illustrate the advantages of the proposed modelling approach. Simulation results show that voltage, rotor and inter-area oscillations are well damped.

Parallel Power Flow on Graphics Processing Units for Concurrent Evaluation of Many Networks

The power flow (PF) analysis provides the steady state of the power system and is key to the simulation of transmission networks. It is a tool commonly used by system operators to visualize the effect of generator settings on the network prior to making a change. In situations involving large networks, hundreds or even thousands of PF analysis may have to be run on the network before finding the optimal power dispatch. This process requires significant computation time and does not allow for rapid control of the network. To address this problem, this paper presents two parallel PF solvers that exploit the massively parallel architecture of graphics processing units (GPU) in a hybrid GPU-central processing unit (CPU) computing environment using compute unified device architecture and OpenMP in order to significantly speedup the concurrent analysis of many instances of a network. Both implementations use sparse matrices, double precision operations, and enforce the reactive power limit of generators. The parallel Gauss-Seidel (G-S) and Newton-Raphson (N-R) PF algorithms are tested on networks ranging from 4 to 2383 buses. The accuracy is validated using MATPOWER and the maximum speedup achieved, compared with a sequential execution on CPU, is

Wide-area measurements based coordination of SVCs and synchronous generators

45.2 \boldsymbol {\times }

Time-delay compensation of a wide-area measurements-based hierarchical voltage and speed regulator

for G-S and

A novel adaptive hybrid force-position control of a robotic manipulator

17.8 \boldsymbol {\times }

A multivariable adaptive nonlinear controller for a five-level diode clamped active power filter

for N-R.

A new adaptive state feedback controller for the ball and beam system

This paper presents a new control design method based on wide-area measurements to coordinate generator excitations and static var compensator (SVC) auxiliary controls. A new state space model comprising a multimachine power system and a SVC is first derived. This model clearly shows the interactions between SVC and generator variables. Next, generator excitations and the SVC auxiliary input are synthesized to decouple the subsystems. These control signals utilize remote measurements and compensate the interactions between the SVC and generators. The proposed control strategy provides an additional damping of inter-area oscillations. Therefore, it also enhances the global stability of the power system. The effectiveness of the new control strategy is tested using the Anderson and Farmer four-generator nine-bus power system. Simulation results demonstrate that generator speeds, SVC and generator terminal voltages oscillations are well damped when the coordinating controller is used.

A robust nonlinear controller for a StatCom based on a 3-phase neutral point clamped converter

This paper presents a delay-insensitive version of a wide-area measurements-based two-level hierarchical controller. This hierarchical structure consists of a central controller, at the secondary level, dedicated to inter-generator interactions compensation, and conventional controllers (automatic voltage regulator, power system stabilizer, and speed governor), at the primary level, to dampen local oscillations. First, a Smith prediction approach is used to preserve performance in the presence of large remote-measurement time delays and communication time delays between central and local controllers. Second, an optimization algorithm is used to considerably reduce the complexity of the controller and thereby increase its reliability. Finally, sets of realistic tests are performed to assess the robustness of the proposed structure in the presence of uncertainties over time delays and power system parameters. Simulation results reveal that time-delay compensation is effectively required to enhance the hierarchical-structure performance in realistic situations. Furthermore, the performance of local controllers is considerably improved by the secondary-level controller action. The stability margin of the system is improved in the presence of severe contingencies.