Application of Multivariable Predictive Control in a Hydropower Plant

Generalized predictive controller (GPC) has robust performance when faced to control non-minimum phase and open-loop unstable processes. GPC has been originally developed with linear predictor models which leads to a formulation that can be solved analytically. If a nonlinear model is used then nonlinear optimization and nonlinear modeling techniques are necessary. This paper presents a new method of multivariable GPC design for nonlinear systems. The proposed GPC design incorporates the neural network model based on radial basis function neural network and optimization methodology of cost function by Lamarckian hybrid method using evolutionary programming and Nelder-Mead’s simplex algorithm. Steps of the control law implementation and intelligent procedure are discussed. Simulation results on a nonlinear MIMO (multi-input multi-output) system are presented to show the effectiveness of the neuro-evolutionary GPC method. The new GPC design is applicable for improve the approximation of nonlinear systems with unknown interactor matrix using neural network model and an efficient control law optimization task by simplex-evolutionary hybrid methodology.

The multivariable generalized predictive control (GPC) law is derived in a stochastic setting which closely follows the usual polynomial solution of the LQG problem. The assumptions which must be made to ensure a GPC type of control law emerges are clear from the analysis which provides insights into the relationship between LQG and GPC control. The form of the single degree-of-freedom control law obtained closely parallels the GPC solution but ensures closed loop stability. The solution of the multi-step cost-function problem is shown to include an LQG controller which must be implemented for the actual feedback system and a set of controllers which are needed to calculate the predicted future controls and outputs. This is of importance when constraints are to be applied based on the future predicted signals. The alternative method outlined, referred to as the vector-matrix solution, does not require this sequence of controllers to be found and it is very similar to the GPC form of solution. However, the LQG stability properties for the feedback loop are still retained.

A unified state-space approach to linear quadratic Gaussian (LQG) and generalised predictive controller (GPC) control problems based on state-space representations of ARMAX models and explicit delay performance indices is presented. Links between the state-space and polynomial approaches to prediction and control problems are highlighted. Both the one-stage and infinite horizon solutions can be found within the unified framework.

Generalized predictive control (GPC) is nowadays, widely ,spread in control theory as well as in the industrial world. Generalized predictive control (GPC) belong to this family has been demonstrated as a powerful controlling process plants, In this work a polynomial approach of generalized predictive control is proposed whose aim to find optimal values for the tuning control and application of predictive control with polynomial form RST and application of induction motor and developed prediction optimal equation with cost function and resolved of the Diophantine equations this application is reserved in our work for the induction motor with example of a dynamic system and non linear multivariable with load torque.

Nepal is a small mountainous Country lying between India and China. The geographical coordinates are 2800N 8400E. Nepal’s falls in the temperate zone north of the tropic of cancer. The Country can be dividing into three main geographical regions; Himalayan region, mid-hill region and Terai region. The highest point in the Country is Mt. Everest (8, 848m) while the lowest point is the terai plains of Kechana Kalanin, Jhapa (60 m). The hydropower sector of Nepal was recognized as one of the most feasible and potential sector for green economy. In Nepal, approximately 10% of the population has access to electricity from the national grid till date. Nepal has huge capacity to generate Hydro Electricity. The Benefit of hydropower are, it is non-polluting in the since it does not release any heat and gases. It has low operating and maintenance cost. The most important benefit is that hydropower plant’s produce electricity without consuming power. This paper is written to find out the future scope of Hydropower in Nepal and to provide information for foreign Investors and domestic investors to invest in Nepal’s hydropower. Primary data were collected through news magazine/daily newspapers, journals and books. This paper presents the hydro-power potential, current utilization and future plan of hydro-power development in the Nepal. The government policy in hydropower its issue and barriers for the development in Nepal are discussed.

This contribution wants to sum up some of the considerations developed during the research carried out for BIM of Adige - Trento Province Consortium of Municipalities - and ended on April 2016 with the conference “La citta dell’Alt(r)o Adige. Esiti di un percorso di ricerca per il BIM Adige”. Research outcomes show a result – not a definite one - of a survey done with an across-the-board point of view of the disciplines that deal with the relationship between watercourses and human settlements. This viewpoint goes through the disciplines’ borders making the architecture and landscape project again a central focus among the most pivotal issues. This reflection begins with a phenomenon that has emerged with some urgency in recent years: the exponential growth of the demands for the creation of new lines and hydroelectric plants, especially small or very small. This new phase coincides with one of the most co) mplex moments of watercourse management due to the overlapping of distinct goals set by two different European Directives that are in conflict with each other: the need to increase the use of renewable energies (Directive 2009/28 / EC) and the need to meet the requirements for classification, protection and improvement of water bodies (Directive 2000/ 60 / EC). This theme becomes an opportunity to make wider reflection on the conflicts generated by the different uses of watercourses and the need to rethink them according to an ecosystem approach. For a wider discussion of the following subjects, please see the volume titled La citta dell’altro Adige, of the same author, published by ListLab 2016.

Stocks are securities that can be bought or sold by individuals or institutions as a sign of participating or possessing a company in the amount of its proportions. From the lens of market capitalization values, stocks are divided into 3 groups: large capitalization (Big-Cap), medium capitalization (Mid-Cap) and small capitalization (Small-Cap). Longitudinal data is observation which is conducted as n subjects that are independent to each subject observed repeatedly in different periods dependently. Smoothing technique used to estimate the nonparametric regression model in longitudinal data is local polynomial estimator. Local polynomial estimator can be obtained by WLS (Weighted Least Square) methods. Local polynomial estimator is very dependent on optimal bandwidth. Determination of the optimal bandwidth can be obtained by using GCV (Generalized Cross Validation) method. Among the Gaussian kernel, Triangle kernel, Epanechnikov kernel and Biweight kernel, it is obtained the best model using Gaussian kernel. Based on the application of the model simultaneously, it is obtained coefficient of determination of 97,80174% and MSE values of 0,03053464. Using Gaussian kernel, MAPE out sample of data is obtained as 11,74493%. Keywords: Longitudinal Data, Local Polynomial, Stocks

The design and simulation of ultrashort pulse shaping systems require pulse propagation methods that take the combined effects of dispersion, diffraction, and system aberrations into account. In the conventional pulse propagation methods based on the spectrum of plane wave, usually large number of sampling points are needed for the correct Fourier transform operations due to the fast oscillating phase of the complex pulse field. In this work, I have developed an alternative pulse propagation method, based on the Gaussian pulsed beam decomposition, as an extension of the monochromatic Gaussian beam propagation method. Methods for the decomposition of an input pulse, with arbitrary spatial and temporal (spectral) profiles, into a set of elementary Gaussian pulsed beams are proposed. Algorithms for computing the spatio-temporal and spatio-spectral profiles of the propagated pulse as the phase correct superposition of individual Gaussian pulsed beams are developed. The proposed decomposition method allows the elementary Gaussian pulsed beams to have different parameters depending on the local spatial and spectral phase of the given input pulse which reduces the number of Gaussian pulsed beams required to decompose an input pulsed beam with a given accuracy. Furthermore, a new kind of beam called the truncated Gaussian beam, is introduced and combined with the conventional Gaussian beam decomposition method to enable decomposition of fields after hard apertures. The analytical propagation equation of the truncated Gaussian beam through a paraxial optical system is derived. Additionally, the application of the Gaussian beam decomposition method is extended to handle the propagation of vectorial fields. Several example calculations are presented to validate the proposed methods and show their application in propagating fields through optical systems which are rather complicated to model using the conventional methods.

A practical method of robust generalized predictive controller (GPC) application is developed using a combination of Ziegler-Nichols type functions relating the GPC controller parameters to a first order with time delay process parameters and a model matching controller. The GPC controller and the model matching controller are used in a master/slave configuration, with the GPC as the master controller and the model matching controller as the slave controller. The model matching controller parameters are selected to obtain the desired overall performance. The effectiveness of the proposed control method is tested by simulation using a mathematical model of the boiler super heater temperature process.

The increasing demand for high-density and high-speed digital optical recording systems has made the development of advanced coding and signal processing techniques for fast and reliable data recovery increasingly important. In recent years, the parity-check (PC)-code-based reception technique has been widely studied for magnetic recording systems, and it is projected to be highly promising for high-density optical recording. The PC code is an inner error correction code (ECC), which can detect dominant short error events of the system, using only a few parity bits. This reduces the loss in error correction capability of the outer ECC due to random short errors and results in a simple and efficient solution to improve the overall performance. This thesis is dedicated to the design and analysis of PCcode- based recording systems to achieve higher recording capacity with low implementation complexity, for high-density blue laser disc systems. In particular, most of the key components of the PC-code-based optical recording system have been designed and optimized for different recording densities, and different proportions of white noise and media noise. During the development of advanced coding and detection techniques, it becomes necessary to investigate the system’s performance with different coding schemes and recording densities. In Chapter 2 of the thesis, we propose a generalized Braat-Hopkins model for optical recording channels, which provides a fair basis for the performance comparison of detection schemes over different coding schemes and recording densities, for channels with additive, white Gaussian noise (AWGN) and media noise. Various basic issues associated with the PC-code-based systems are investigated in Chapter 3. These include bounds for bit error rates and error event probabilities, the dominant error events at channel detector output, different PC codes, simple and efficient post-processors, the impact of error events that are split across data block boundaries and the corresponding remedy, as well as the effects of code rates and recording densities. Simulation results show that a 4-bit PC code achieves the best performance. The corresponding bit error rates (BERs) are very close to the performance bounds, at both nominal and high densities. Constrained codes, which serve as a key component in the read-write channel of data storage systems, are desired to have a high code rate with low-complexity encoder/decoder. In Chapter 4, we investigate the design of certain capacity-approaching constrained codes for optical recording systems. In particular, we derive analytically the relationship between the number of encoder states and the maximum size of these codes. We identify the minimum number of encoder states that maximizes the code rate, for any desired codeword length. The design of constrained PC codes is key to the development of PCcode- based systems, and the systematic design of efficient constrained PC codes remains a challenging problem. In Chapter 5, we propose a general and systematic code design technique for constructing capacity-approaching constrained PC codes, which can detect any type of error events of the system, with the minimum code rate loss. Compared to the rate 2/3 code without parity, the newly designed constrained 4-bit PC code achieves a performance gain of 2 dB at nominal density, and 1.5 dB at high density, at BER = 10-5. As the dominant noise for high-density optical recording systems, media noise severely degrades the performance of channel detectors and postprocessors that are designed for AWGN. In Chapter 6, we propose two novel modifications to the bit detector to combat media noise. We further develop a data-dependent post-processing scheme for error correction. Compared to the system designed without considering media noise and without PC codes, the overall performance gain of the developed scheme can be more than 11 dB at high media noise levels. In data storage systems, the ECC failure rate (EFR) serves as the ultimate measure of the data recovery performance. In Chapter 7, we develop semi-analytical approaches for estimating the EFR, and analyze EFRs for the developed PC-code-based systems, for the cases without and with interleaving. Our analysis shows that with the optimum interleaving degrees, compared to the rate 9/13 code without parity, the 2-bit PC code achieves a gain of around 0.5 dB, and the 4-bit PC code gains 0.6 dB, at high record ing density and EFR = 10-16. The thesis concludes in Chapter 8 with some suggestions for further work.

Hydroelectric energy is a major source of renewable electricity in the world. The industry is continuously searching for ways to improve the efficiency and reliability with which it produces energy. Here suggested a PID approach to turbine governor by utilizing human experience. The simulation model of Hydro Power Plant was constructed based on mathematical equations that summarize the behavior of the power plant. The simulation model of power plant is useful in stability studies. Simulation models are suitable for use in large scale system stability studies. The PID controller is designed and tested for three phases to ground fault by simulations which are reported in this paper. Results obtained by simulation show the rapidity and robustness of the PID controller. This controller is able to maintain the generated electrical power characteristics in spite of the changing user load. The invention and design of stabilized system means the ability of the system working with different load and fault. Controlling voltage system represent control an active power in electrical power grid by increasing and decreasing the generator voltage. In this paper completed models test that stability and flexibility of the Synchronized generator with over exciter, and under exciter by Governor and Excitation systems.  Â

The refinery units frequently need advanced process control (APC) strategies and near smooth real-time feed stream composition of crude oil for increasing economic profit in petroleum refining industry. So crude oil blending is a crucial process for managing crude transitions in logistics. In this paper we model the blending process as multi-input multi-output (MIMO) CARIMA model according to the characteristics that there is no coupling among variables, we control the blending process based on generalized predictive control (GPC) strategy. Meanwhile a nuclear magnetic resonance (NMR) spectroscopy analyzer is used to precisely measure the important crude oil composition of different steam of the blender. Then the real time data is used to adapt the parameters of CARIMA model. Finally, the accurateness and suitability of the proposed method is demonstrated with the case study of a crude oil blender.

The climate and land-use changes impact on water availability for hydropower plants in Indonesia

The acceptability and also the acceleration of renewable energy technologies is tightly linked with a better understanding of dynamic behavior of drive train components and their interactions. This ultimate understanding of system characteristics can only be achieved with comprehensive experimental investigations on different phenomena of large electrical generators. This leads consequently to a better verification of numerical and analytical models of large generators. The large generator-converter lab which is discussed in this paper is a unique opportunity for deep experimental investigations on large hydro and wind generators. It is designed to deal with the current as well as future research topics in the field of wind and hydro generators and their interactions with power electronic devices and electrical grid.

Time-Delay-Estimation (TDE) has been a topic of interest in many applications in the past few decades. The emphasis of this work is on the application of model-based estimation (MBE) for TDE of ultrasonic signals used in ultrasonic thickness gaging. Ultrasonic thickness gaging is based on precise measurement of the time difference between successive echoes which reflect back from the back wall of the test piece. The received echoes are modelled by Gaussian pulses and the desired system response is estimated using Gauss-Newton and Space Alternating Generalized Expectation Maximization (SAGE) algorithms. In addition to the model-based estimation approach, five other TDE techniques including peak-to-peak measurement, cross-correlation, cross-correlation with interpolation, phase-slope, and cross-correlation with Wiener filtering are also considered and compared with the SAGE. The main advantage of the SAGE algorithm, in addition to its higher accuracy, is its ability to deconvolve the overlapping echoes.