Rabiah Badar

Hybrid Neuro-fuzzy Legendre-based Adaptive Control Algorithm for Static Synchronous Series Compensator

Abstract This article presents a novel adaptive non-linear control scheme for a static synchronous series compensator to improve power system stability. The proposed control system synergistically integrates the Legendre polynomial functional neural network, a member of the orthogonal polynomials family, with adaptive neuro-fuzzy Takagi–Sugeno control. The control scheme exploits the online, model-free direct control structure, which reduces the computational complexity, latency, and memory requirements, to make the proposed control strategy highly suitable for real-time implementation. The performance of the proposed control system is validated against different contingencies and operating conditions using non-linear time-domain simulations and different performance indices. The performance of the proposed control system is compared with the adaptive neuro-fuzzy Takagi–Sugeno. The results reveal that the proposed control scheme effectively damps the local and inter-area mode of oscillations.

Adaptive Fuzzy Wavelet NN Control Strategy for Full Car Suspension System

In the last few years, different linear and non-linear control techniques have been applied by many researchers on the vehicle suspension system. The basic purpose of suspension system is to improve the ride comfort and better road handling capability. Therefore, a comfortable and fully controlled ride can not be guaranteed without a good suspension system. The suspension system can be categorized as; Passive, Semi-active and Active.

Online adaptive NeuroFuzzy wavelet based SSSC control for damping power system oscillations

Major blackouts reported in the literature due to low frequency inter-area oscillations highlight the importance of efficient damping control devices. This paper presents an Online NeuroFuzzy Wavelet Control (ONFW-C) based auxiliary damping control (ADC) to damp inter-area oscillations in a multi-machine power system using Static Synchronous Series Compensator (SSSC). The control system parameters are tuned online based on the adaptive NeuroFuzzy rules extracted from rotor speed error and its derivative. The optimization of the proposed control paradigm is done using gradient descent based back-propagation algorithm. The control scheme utilizes the model free direct control structure which reduces the computational complexity, latency and memory requirements for real time implementation. The robustness of the proposed control system is checked against various faults and operating conditions on the basis of nonlinear time domain simulations. Finally, the results of proposed ONFW-C are compared with Online NeuroFuzzy TSK Control (ONFT-C).

Coordinated Adaptive Control of Multiple Flexible AC Transmission Systems using Multiple-input—Multiple-output Neuro-fuzzy Damping Control Paradigms

Abstract This article presents a novel online adaptive non-linear multiple-input–multiple-output neuro-fuzzy control scheme for flexible AC transmission systems. The proposed control system synergistically integrates the time-frequency localization property of wavelets with locally controllable membership functions in the structure of neuro-fuzzy Takagi–Sugeno–Kang control. The proposed control scheme is checked for both multiple-input–single-output and multiple-input–multiple-output topologies. The performance of the proposed control system is validated against different contingencies and operating conditions using non-linear time-domain simulations and different performance indices. The results reveal that the proposed control scheme effectively damps the local and inter-area modes of oscillations.

Online adaptive Legendre wavelet embedded neurofuzzy damping control algorithm

Power system stability can significantly be enhanced by installing a Static Synchronous Series Compensator (SSSC) using appropriate damping control scheme. In this work, a new Online Adaptive Legendre Wavelet (OALeW) based NeuroFuzzy control of SSSC is proposed. The proposed control strategy tunes the rule base using the current estimate of plant model, based on the online sensitivity measure, provided by the identification block. The parameters of the controller are updated online using gradient descent based backpropagation algorithm. The robustness of the proposed control strategy is validated using nonlinear time domain simulations and different performance indices for Single Machine Infinite Bus (SMIB) and multimachine test systems. A comparative analysis with singleton Takagi-Sugeno-Kang (TSK) reveals that the proposed OALeW control performs better in both the transient and steady-state regions for different operating conditions and faults with improvement in control effort smoothness.

Adaptive NeuroFuzzy Legendre based damping control paradigm for SSSC

The controllable series injected voltage can be used to damp low frequency power and rotor angle oscillations. Conventional linear and NeuroFuzzy control schemes perform well only for a specific operating condition, or in the vicinity of the tuned operating point of highly nonlinear power system, due to their fixed parameters architecture. To improve the performance of the damping control, nonlinear behavior of power system must be incorporated via some nonlinear control scheme. This work presents an online adaptive nonlinear control paradigm by incorporating Legendre polynomial NNs in the consequent part of the conventional TSK structure. The proposed control scheme is successfully applied to damp local and inter-area modes of oscillations for different contingencies and operating conditions. The robustness of the proposed control scheme is validated using comparative analysis based on nonlinear time domain simulations and different performance indices.

FPGA Based Implementation Scenarios of TEA Block Cipher

Transmission of sensitive data over some channel is a highly security constrained scenario and thus demands the application of some encryption algorithm. It is better to implement the algorithm in hardware as compared to software due to better computational speed and memory usage. Tiny Encryption Algorithm known as TEA block cipher is a light-weight and efficient cryptographic algorithm, well suited for wireless communication systems. This paper presents the successful implementation of TEA on FPGA for different design approaches to analyze the performance and resource utilization against each design approach.

Damping low frequency oscillations using online Adaptive NeuroFuzzy Type-2 based STATCOM

The reactive power compensation using shunt FACTS controllers also regulates the voltage of bus at which the shunt controller is installed. Static Synchronous Compensator (STATCOM), one of the shunt FACTS controllers, is a well-known controller used for this purpose, however, this article investigates its behavior for damping power system oscillations by application of a novel direct adaptive NeuroFuzzy Type2 (ANFT2) based nonlinear control scheme, for damping low frequency inter-area oscillations, using STATCOM. The proposed control scheme exploits the excellent estimation property of Type2 membership functions for modeling uncertainties in the system. The parameters of the proposed control scheme are updated online without using any offline training data which in turn minimizes the memory requirements, computational complexity and latency maintaining the performance of the system. The performance of the proposed control system is tested for various faults and operating conditions on multi-machine test system using nonlinear time domain simulations. Finally, the comparative analysis of ANT2 with Adaptive NeuroFuzzy Type-1 (ANFT1) control and without control is presented to validate the efficiency of proposed control system. The simulation results reveal that the proposed control scheme significantly improves the damping performance in transient and steady-state regions.

Hybrid NeuroFuzzy B-spline Wavelet based SSSC control for damping power system oscillations

Controllable series voltage injection can significantly enhance the damping capability of a power system. Static Synchronous Series Compensator (SSSC) is a well-known FACTS controller used for this purpose. This paper presents a novel adaptive control scheme to damp inter-area oscillations in a multi-machine power system using SSSC. The proposed control paradigm utilizes the local control property of B-spline membership function by hybridizing it with wavelet NNs in the structure of NeuroFuzzy system to design the external control for SSSC. The system parameters are tuned online based on the adaptive NeuroFuzzy rules extracted from rotor speed error and its derivative. The detailed mathematical description of online tuning the control parameters is given. The control scheme utilizes the model free direct control structure which reduces the computational complexity, latency and memory requirements making the control system a good candidate for real time implementation. The robustness of the proposed control system is checked against various faults and operating conditions on the basis of nonlinear time domain simulations. Finally, the results of proposed Hybrid B-spline Wavelet Control (HBsWC) are compared with Adaptive NeuroFuzzy TSK Control (ANeFu-TS).

Power system stabilty enhancement using Adaptive NeuroFuzzy Control for UPFC

Interconnected power system is a dynamic system and consistently exposed to disturbances. In the absence of inherited damping torque, these disturbances result in Low Frequency Oscillations, which can endanger the system security and stable operation. In order to increase the network stability, the exploitation of flexible AC transmission systems devices has become more and more significant. The Unified Power Flow Controller (UPFC) can effectively damp power system oscillations with addition of supplementary controller. This research work proposes Takagi Sugeno Kang (TSK) fuzzy system based Adaptive NeuroFuzzy Controller (ANFC) for UPFC using conjugate gradient algorithm which makes the system computationally efficient with less memory requirement and fast convergence speed. The effectiveness of control scheme is studied using simulations of two machines test system with different test scenarios. Simulation results and performance comparison with PID controller confirms the effectiveness of proposed supplementary control scheme to enhance transient stability.