Izvedba poopćenih predikcijskih regulatora u prostoru stanja

This paper introduces a methodology for the original design of generalised predictive controllers (GPC\u27s) based on the use of a state space CARIMA model to carry out those predictions. The CARIMA model presented is equivalent to the CARIMA model commonly used in the input/output (I/O) formulation of the GPC\u27s. A connection is settled among the stochastic part of this model and the filter polynomials Ti(z-1), making possible the design of the controller once any one of them is known. It is also remarkable that for the estimation of non-measurable states, a full rank observer is proposed, and the fact that its poles are equal to the roots of the filter polynomials Ti(z-1) can also be appreciated.U članku se opisuje izvorna metodologija projektiranja i izvedbe poopćenih predikcijskih regulatora (GPC-a) zasnovana na primjeni CARIMA modela u prostoru stanja za predikciju stanja. Opisani CARIMA model ekvivalentan je najčešće korištenom CARIMA modelu koji se koristi pri ulazno/izlaznoj formulacji GPC-a. Uspostavljena je veza između stohastičkog dijela modela i polinoma Ti (z-1), čime je omogućena sinteza regulatora kada je poznat bilo koji od njih. Za estimaciju nemjerljivih veličina stanja predložen je estimator punog reda, koji, što je posebno važno, ima polove jednake korijenima polinoma Ti (z-1)

The analysis and design of multirate sampled-data feedback systems via a polynomial approach

This thesis describes the modelling, analysis and design of multirate sampled-data feed-back via the polynomial equations approach. The key theoretical contribution constitutes the embedding of the principles underpinning and algebra related to the switch and frequency decomposition procedures within a modern control framework, thereby warranting the use of available computer-aided control systems design software. A salient feature of the proposed approach consequently entails the designation of system models that possess dual time- and frequency-domain interpretations. Expositionally, the thesis initially addresses scalar systems excited by deterministic inputs, prior to introducing stochastic signals and culminates in an analysis of multivariable configurations. In all instances, overall system representations are formulated by amalgamating models of individual sub-systems. The polynomial system descriptions are shown subsequently to be compatible with the Linear Quadratic Gaussian and Generalised Predictive Control feedback system synthesis methods provide causality issues are dealt with appropriately. From a practical perspective, the polynomial equations approach proffers an alternative methodology to the state-variable techniques customarily utilised in this context and affords the insights and intuitive appeal associated with the use of transfer function models. Numerical examples are provided throughout the thesis to illustrate theoretical developments

Izvedba poopćenih predikcijskih regulatora u prostoru stanja

This paper introduces a methodology for the original design of generalised predictive controllers (GPC\u27s) based on the use of a state space CARIMA model to carry out those predictions. The CARIMA model presented is equivalent to the CARIMA model commonly used in the input/output (I/O) formulation of the GPC\u27s. A connection is settled among the stochastic part of this model and the filter polynomials Ti(z-1), making possible the design of the controller once any one of them is known. It is also remarkable that for the estimation of non-measurable states, a full rank observer is proposed, and the fact that its poles are equal to the roots of the filter polynomials Ti(z-1) can also be appreciated.U članku se opisuje izvorna metodologija projektiranja i izvedbe poopćenih predikcijskih regulatora (GPC-a) zasnovana na primjeni CARIMA modela u prostoru stanja za predikciju stanja. Opisani CARIMA model ekvivalentan je najčešće korištenom CARIMA modelu koji se koristi pri ulazno/izlaznoj formulacji GPC-a. Uspostavljena je veza između stohastičkog dijela modela i polinoma Ti (z-1), čime je omogućena sinteza regulatora kada je poznat bilo koji od njih. Za estimaciju nemjerljivih veličina stanja predložen je estimator punog reda, koji, što je posebno važno, ima polove jednake korijenima polinoma Ti (z-1)

Analysis and resynthesis of polyphonic music

This thesis examines applications of Digital Signal Processing to the analysis, transformation, and resynthesis of musical audio. First I give an overview of the human perception of music. I then examine in detail the requirements for a system that can analyse, transcribe, process, and resynthesise monaural polyphonic music. I then describe and compare the possible hardware and software platforms. After this I describe a prototype hybrid system that attempts to carry out these tasks using a method based on additive synthesis. Next I present results from its application to a variety of musical examples, and critically assess its performance and limitations. I then address these issues in the design of a second system based on Gabor wavelets. I conclude by summarising the research and outlining suggestions for future developments

Model Predictive Control with First-Order Hold Element

Nowadays, the size and complexity of petrochemical industries have increased considerably as the demand from the consumers have increased, while the profit margins are decreasing. The control systems play an important role in maximizing the profit margins by optimally utilizes resources and energy. Model Predictive Control (MPC) handle multi-variable systems and constraints in a systematic way. The MPC has been used for about four decades and it provides a positive impact to the system which is why it’s been mostly used in the petrochemical plant. However, in this report, it will discuss more on the way to improvise the performance of MPC by implementing the first-order hold element instead of zero-order hold element method. By using the single input and single output plant for MPC, the result will differentiate the zero-order hold and first-order hold. The tools that have been used for this project is the MATLAB simulation. The expected result from the study is the first-order hold element method will show better result compared to the zero-order hold element method. However, there will be some cons if using the first-order hold and it will be discussed in the report. The function of this MPC is to get the production meet the required criteria by controlling the manipulated variables. The required criteria can be control by the system as it is the reference point. In conclusion, the first-order hold element method will give a better result than zero-order hold element although nowadays many companies still using zero-order hold. This is because zero-order hold is easier to calculate and operate compared to the other method. However, the final production whether it is in a good quality or quantity is more important and it will increase the profit of that company. So, it is highly recommended the petrochemical company to use this equivalent to first-order hold element method in their MPC system as it will maximize the production of their product

Model Predictive Control with First-Order Hold Element

Nowadays, the size and complexity of petrochemical industries have increased considerably as the demand from the consumers have increased, while the profit margins are decreasing. The control systems play an important role in maximizing the profit margins by optimally utilizes resources and energy. Model Predictive Control (MPC) handle multi-variable systems and constraints in a systematic way. The MPC has been used for about four decades and it provides a positive impact to the system which is why it’s been mostly used in the petrochemical plant. However, in this report, it will discuss more on the way to improvise the performance of MPC by implementing the first-order hold element instead of zero-order hold element method. By using the single input and single output plant for MPC, the result will differentiate the zero-order hold and first-order hold. The tools that have been used for this project is the MATLAB simulation. The expected result from the study is the first-order hold element method will show better result compared to the zero-order hold element method. However, there will be some cons if using the first-order hold and it will be discussed in the report. The function of this MPC is to get the production meet the required criteria by controlling the manipulated variables. The required criteria can be control by the system as it is the reference point. In conclusion, the first-order hold element method will give a better result than zero-order hold element although nowadays many companies still using zero-order hold. This is because zero-order hold is easier to calculate and operate compared to the other method. However, the final production whether it is in a good quality or quantity is more important and it will increase the profit of that company. So, it is highly recommended the petrochemical company to use this equivalent to first-order hold element method in their MPC system as it will maximize the production of their product