In this paper, an adaptive wavelet neural network tracking controller is studied for solving control and stability problem of a class of uncertain Nonlinear systems. The considered systems in this paper are of the discrete-time form in pure-feedback structure and include the Backlash and external disturbance. The Backlash Nonlinearity input appears non-symmetric in the systems. These systems are more general than those in the previous work. There are major difficulties for stabilizing such systems and in order to overcome the difficulties, by using prediction function of future states, the systems are transformed into an n-step-ahead predictor. The wavelet neural networks are used to approximate the unknown functions and unknown Backlash in the transformed systems and the adaption laws are to update neural weights and to compensate for the unknown parameter of Backlash. Based on the Lyapunov theory, it is shown that the proposed controller guarantees that all the signals in the closed-loop system are bounded and the tracking error converges to a small neighborhood of zero. The simulation of a Single-link robot arm system is provided to verify the effectiveness of the control approach in the paper. Finally, in order to validate, the results of the proposed method are compared with the results of PID and sliding mode controller.

In many wheeled robot applications, in addition to accurate position control, dimensional and weight limitations are also important. The limitation of weight and dimensions means that it is not possible to use arbitrarily large actuators. On the other hand, accurate and fast tracking usually requires high control gains and, as a result, large control inputs. If the control input exceeds the saturation limit of the operator, in addition to increasing the tracking error, it may lead to robot instability in some cases. Therefore, it will be precious to provide a control method that can simultaneously provide high control accuracy and guarantee the robot's stability, taking into account the saturation limit of the actuators (speed and torque) in a predetermined manner. This issue has been addressed in the present study. The proposed control includes two parts: a kinematic controller and a dynamic controller. The kinematic control design is based on the Lyapunov approach, which can adjust the speed saturation limit of the actuators. For dynamic control, the robot velocity components are considered as control reference values ​​and the robot wheel torque is considered as control inputs. In the dynamic control design, the torque saturation limit of the actuators is included in a predetermined way. To evaluate the performance of the proposed Nonlinear control, various analyses were performed on the wheeled robot. The results showed that the proposed control algorithm while guaranteeing stability and following the path with high accuracy, has also fully met the requirements of the actuators’ saturation limits

A Fault-Tolerant Control (FTC) methodology has been presented for Nonlinear processes being imposed by control input constraints. The proposed methodology uses a combination of Feedback Linearization and Model Predictive Control (FLMPC) schemes. The resulting constraints in the transformed process will be dependent on the actual evolving states, making their incorporation in the design context a non-trivial task. A feasible direction method has been integrated in the design procedure based on active set technique to resolve the challenging constraint–based FLMPC problem. The formulated FLMPC design method is utilized to develop a FTC scheme by providing a set of backup control configurations for a CSTR benchmark process. The successful performance of the proposed FTC methodology has been demonstrated via a category of common fault scenarios by exercising an arbitrary replacement of control configurations through a supervisor to maintain the CSTR operation at an unstable desired steady-state point.

BACKGROUND AND OBJECTIVES: Air quality in some developing countries is dominated by particulate matter, especially those with size 10 micrometers and smaller or PM10. They can be inhaled and sometimes can get deep into lungs,some may even get into bloodstream and cause serious health problems. Therefore, future PM10 concentration forecasting is important for early prevention and in urban development planning, which is crucial for developing cities. This paper presents the development of PM10 forecasting model using Nonlinear autoregressive with exogenous input model. METHODS: To improve performance of Nonlinear autoregressive with exogenous input model, principal component analysis is used prior to the model for variable selection. The first stage of principal component analysis involves Scree plot, which determines the number of principal components based on explained variance. This is then followed by selecting variables using a rotated component matrix, based on their strength of contribution towards variation of PM10 concentration. To test the model, PM10 data in Kota Kinabalu from 2003 –,2010 was used. Neural network models are developed using this data by varying number of input variables with the inclusion of temporal variables. The developed forecasting models are evaluated using data PM10 in the city from 2011 to 2012. Four performance indicators, namely root mean square error, mean absolute error, index of agreement and fractional bias are reported. FINDINGS: Results from principal component analysis show that five variables including wind direction index, relative humidity, ambient temperature, concentration of nitrogen dioxide and concentration of ozone strongly contribute to the variation of PM10 concentration. By using these variables together with temporal variables as input in the Nonlinear autoregressive with exogenous input models, the resultant model shows good forecasting performance, with root mean square error of 7. 086±, 0. 873 μ, g/m3. The selection of significant variables helps in reducing input variables inside the forecast model without degrading its forecast performance. CONCLUSION: This model shows very promising performance in forecasting PM10 concentration in Kota Kinabalu as it requires fewer input variables and does not require variable transformation.

In this paper, it is designed and simulated a 4 input AND all-optical gate based on Kerr-type Nonlinear ring resonator using 2D-photonic crystal with silicon rods embedded into air as square lattice. It is utilized silicon Nano-crystal (Si-NC) with Nonlinear Kerr coefficient in the ring resonator structure. The ring resonator parameters such as rod radius, refractive index, ring radius and lattice constant are selected in the proposed optical device to operate in c telecommunication window (1550 nm). Finite Difference Time Domain (FDTD) method And Plane Wave Expansion (PWE) method are used for simulations. The Kerr Nonlinear effect causes to obtain resonance frequency shift in output characteristics. The input threshold for altering the gate logical state is around 150 mW/ µ m and its time response is 0. 85 ps. The simulation results show that the ratio contrast between the logical state 0 and 1 for the proposed AND logical gate is more than 28 dB.

In the present paper, the effects of deconvolved earthquake input on the linear and Nonlinear seismic response of an existing arch dam in a 3D space are investigated. Nonlinearities originate from the opening/slipping of the vertical contraction joints within the dam body. The reservoir– structure interaction is taken into account by the finite element method with the appropriate boundary conditions. The reservoir was assumed to be compressible. The Shahid Abbaspour arch dam was selected for the case study. Finally, the viscous condition at the far-end boundary of the foundation is used to model the radiation effect. A quasi elastic damping model is utilized. The stiffness and mass proportional damping, equivalent to 10% of the critical damping based on the 2Hz and 6Hz frequencies of the dam foundation system, is applied to the structure. Three components of the 1994 Northridge earthquake as maximum credible earthquake are selected as the free field ground motions. The analysis is carried out in two steps. First a deconvolution analysis is performed to adjust the amplitude and frequency contents of an earthquake ground motion applied at the base of the foundation to achieve the desired output ground acceleration at the dam-foundation interface at the different points. Then the calibrated base acceleration history is applied to the foundation base of the dam-reservoir-foundation-system to perform the seismic analysis. Based on the results, spectra of the response at the dam-foundation interface at different points match very closely with the spectra of the horizontal free field ground motions. However, the existing deconvolution procedure does not produce appropriate results for high frequency ground motion records. To overcome such limitation, a modified procedure has been used for vertical earthquake which has led to better convergence. In existing procedure, a correction factor for each frequency is computed using the ratio of the Fourier amplitudes of the reproduced ground acceleration at the dam-foundation interface and free-field ground acceleration signals in a given iteration. The acceleration signal applied at the base of the foundation model is modified using the correction factor for each frequency. In modified procedure, Instead of adjusting the Fourier amplitudes, the response spectra at different frequency are adjusted. It is worth mentioning that the main novelty of the present investigation, is that it takes into account the effects of deconvolved earthquake input in addition to both the joints Nonlinearity. According to the analyses, modeling vertical contraction joints leads to a decrease in the maximum value of stensile stress levels through the dam body by 6%. The extreme values of joints opening/sliding experienced by the contact elements located on the upstream face along the crest are 6. 3mm and 18. 1mm, respectively. The maximum values for joints sliding occurred in vicinity of the abutments. Also, maximum values of joint opening/sliding along the height of the dam body experienced by the contact elements located between the central cantilever and the adjacent ones on the upstream face occurred in crest of the dam body. However, to achieve more realistic results, other factors such as the spatial variation in ground motion, should be considered.