Performance comparison of THF-NLFXLMS and VFXLMS algorithms for Hammerstein NANC

Recently, THF-NLFXLMS algorithm was developed to compensate the nonlinearity encountered in nonlinear active noise control systems. Despite similar performance, this algorithm is more advantageous than the Nonlinear Filtered-X Least Mean Square (NLFXLMS) due to the use of tangential hyperbolic function (THF) instead of scaled error function (SEF) which allows the degree of nonlinearity to be modeled. In addition, the computational complexity is relatively small compared to other direct nonlinear adaptive algorithm like the Volterra filter. In this paper, the performance of THF-NLFXLMS algorithm for Hammerstein secondary path structure is quantified and compared with NLFXLMS and the Volterra Filtered-x Least Mean Squares (VFXLMS) algorithm of similar computational complexity. The results show that the THF-NLFXLMS algorithm has similar performance as NLFXLMS algorithm and outperforms 2nd order VFXLMS algorithm

Loudspeaker nonlinearity compensation with inverse tangent hyperbolic function-based predistorter for active noise control

In active noise control (ANC), the performance of the filtered-x least mean squares (FXLMS) algorithm is degraded by the saturation of the loudspeaker in the secondary path. Predistortion is a linearization technique commonly used in signal processing applications to compensate for saturation nonlinearity. The design of the predistorter (PD) requires the use of direct measurement from the output of the nonlinear element. However, in ANC applications, direct measurement from the loudspeaker output is not available. Therefore, a conventional PD design approach cannot be directly applied. In this paper, a new PD-based compensation technique based on the inverse model of the loudspeaker nonlinearity is proposed. The PD is represented by an approximated memory-less inverse tangent hyperbolic function (ITHF). The approximated ITHF is scaled by a pre-identified parameter, which represents the loudspeaker nonlinearity strength. This parameter can be obtained by modelling the secondary path using a proposed block-oriented Hammerstein structure in which the nonlinear part is represented by a memory-less tangent hyperbolic function (THF). Simulation results show that using the proposed PD along with the FXLMS algorithm increase the noise reduction performance significantly

Comparison of performance and computational complexity of nonlinear active noise control algorithms

Research on nonlinear active noise control (NANC) revolves around the investigation of the sources of nonlinearity as well as the performance and computational load of the nonlinear algorithms. The nonlinear sources could originate from the noise process, primary and secondary propagation paths, and actuators consisting of loudspeaker, microphone or amplifier. Several NANCs including Volterra filtered-x least mean square (VFXLMS), bilinear filtered-x least mean square (BFXLMS), and filtered-s least mean square (FSLMS) have been utilized to overcome these nonlinearities effects. However, the relative performance and computational complexities of these algorithm in comparison to FXLMS algorithm have not been carefully studied. In this paper, systematic comparisons of the FXLMS against the nonlinear algorithms are evaluated in overcoming various nonlinearity sources. The evaluation of the algorithms performance is standardized in terms of the normalized mean square error while the computational complexity is calculated based on the number of multiplications and additions in a single iteration. Computer simulations show that the performance of the FXLMS is more than 80% of the most effective nonlinear algorithm for each type of nonlinearity sources at the fraction of computational load. The simulation results also suggest that it is more advantageous to use FXLMS for practical implementation of NANC

Energy Management System in Battery Electric Vehicle Based on Fuzzy Logic Control to Optimize the Energy Consumption in HVAC System

This particular research has been conducted at University Putra Malaysia (UPM) to investigate the applicability of fuzzy logic technique in enhancing the energy management of battery-powered electric vehicle (BEV). Because of the increasing demand of BEVs, there is a need to increase the battery power while fulfilling the conflicting of battery power needs and power consuming needs for motor and auxiliaries (such as HVAC). The balance between keeping the comfort of HVAC use and increasing the battery range is complicated and the support of Artificial Intelligence can be useful. The study integrated an energy management system, which is using the designed Fuzzy Logic strategy, to enhance the drain of battery power capacity. The simple black box design of the EMS system has two inputs, State of Charge (SoC) and Speed, and three outputs, Heated Seats, Front HVAC, and Rear HVAC. The membership functions of output fuzzy of the Front HVAC, which shows that every output has three equal categories, 1/3, 2/3, 3/3, associated with low, mid, and high. The same approach of membership functions is applied for Rear HVAC, and Heated Seat. The three outputs of the HVAC system assumed to have a constant load of 1000 Watt each and have three equal categories, low, medium, and high. The fuzzy logic design uses a strategy of nine rules. The simulation is applied on MATLAB Simulink environment and the tests are using two driving cycles, the New European Driving Cycle (NEDC) and Japan 10-15.  The results show that using the managed HVAC strategy can increase the battery driving range by 9.8-20.4% compared with the full-unmanaged HVAC strategy

Chaotic fractal search algorithm for global optimization with application to control design

This paper presents chaos-embedded optimization algorithms named as Chaotic Fractal Search (CFS). These algorithms are improved variance to original Stochastic Fractal Search (SFS) algorithm. The influence of two chaos maps which are Chebyshev map and Gauss/Mouse map on the convergence speed and fitness accuracy of the SFS are investigated in this study. Two well-known benchmark test functions with different dimension levels and landscapes were employed in order to evaluate the performance of proposed CFS algorithms in comparison to their predecessor algorithm. Furthermore, the proposed approach is implemented in the optimal tuning of conventional PID and PD-type fuzzy logic controllers for a twin rotor system (TRS) in hovering mode. The simulation study indicates that CFS algorithm with Gauss/Mouse chaotic map in both Diffusion and First Updating process outperforms other CFS algorithms and original SFS algorithm. In addition, PD-type fuzzy logic controller shows superiority over PID controller in twin rotor system control design

Empirical modeling and control for spray drying of orange juice powder

Spray drying is a removal of moisture from liquid feed by breaking into droplets in a hot medium to convert into powder form. In order to ensure the product quality is at the desired specification, a good control system and good understanding on the dynamic behavior should be considered. The aims of this study are to develop empirical model of spray drying process and improve the process by implementation of PI controller. A nozzle atomizer spray dryer, Lab-Plant SD 05 Laboratory Scale Spray Dryer was used. The liquid feed was Sunquick Concentrated Orange Juice and DE 10-15 maltodextrin as the drying agent. The effects of inlet air temperature and maltodextrin concentration on final moisture content and outlet air temperature were investigated. From investigation, the effect of inlet air temperature on moisture content and outlet air temperature was greater than maltodextrin concentration. Thus, inlet air temperature was selected as manipulated variable. For modeling, the model obtained can be represented as first order process with time delay (FOPTD). In order to improve the process, the model obtained was used in simulation studies to determine the suitable tuning method by PI controller. The PI controllers were tuned by direct synthesis, min IAE method and Cohen-coon. From the observation, direct synthesis method is the most suitable tuning method for PI controller in spray drying process

Design procedure of robust QFT-based controller for continuous-flow grain dryer plant

Quantitative Feedback Theory (QFT) is a well known robust controller that deals with plant uncertainty. QFT has been applied to many industrial applications, however it never been applied to any types of grain dryer plant. Grain dryer plant prone to parameter uncertainty and needs a robust controller in order to maintain a good quality of product output. The objective of this paper is to explain step-by-step design procedure of QFT design for a continuous-flow grain dryer plant. The designed QFT-based controller is also tested and compared with PID controller via simulation. The test results showed that the QFT-based controller works better than PID controller in terms of shorter settling time and smaller percentage of overshoot for the grain dryer plant under study and at the same time insensitive to parameter changes i.e. input and output disturbances

Plantar pressure repeatability data analysis for healthy adult based on EMED system

This paper presents the repeatability data analyses and discusses the selection of the appropriate type of plantar pressure measurements for the EMED system with regards to Pressure Level Values (PLV) over the touch insole area of healthy adults. In this research, a participant with age 28 years old has been chosen as a sample to measure under foot pressure, it is conducted the test 20 times and took part in four types of plantar pressure clinical assessments, Dynamic (normal walking), Dynamic with load (normal walking, carrying 1.5 Kg), Static (Standing test), and Static with load (Standing, carrying 1.5 Kg). The analysis is implemented using a new approach of recognizing the measurements into 7 different levels of pressure that assigned with 7 colors by considering the image processing algorithm. Variance Coefficient (VC) check is adopted for the statistical analysis and the selection decision. The results highlighted that the overall pressure levels in dynamic with load category have a better variance as compared with three other categories of plantar pressure on this type of repeatability test. In conclusion, EMED system can be considered as an effective instrument to record plantar foot pressure measurements in such type of analysis