Dažnai realių stochastinių sistemų negalime aprašyti Markovo procesais, nes operacijų trukmės nėra pasiskirstę pagal eksponentinį dėsnį. Šiame darbe nagrinėjome sistemų aproksimavimo galimybes, taikant eksponentinių skirstinių mišinius ir sąsūkas. Skirstinių aproksimavimui taikėme Erlango mišinius ir Kokso skirstinį. Skirstinių aproksimavimą pritaikėme aptarnavimo sistemų M/G/1 ir G/M/1 tyrimui. Atlikti teoriniai skaičiavimai parodė, kad gaunamas aukštas aproksimavimo tikslumas. Aptarnavimo sistemų modeliavimui naudojome skaitmeninio Markovo procesų modeliavimo sistemą naudojant įvykių kalbą. Darbe sukurti metodai leidžia tiksliai apskaičiuoti sistemų charakteristikas, naudojant aproksimavimą eksponentiniais mišiniais ir sąsūkomis. Sukurta programinė įranga leidžia automatizuoti sistemų M/G/1 ir G/M/1 modeliavimą, naudojant aproksimavimą eksponentiniais mišiniais. Sistemos G/G/1 ( neištiriamos analiziniais metodais ) aproksimavimo rezultatai leidžia tikėtis, kad šiame darbe nagrinėjamas metodas gali būti naudojamas ir sudėtingų sistemų modeliavime. / Application of numerical methods with approximation allows to extend a class of systems represented by Markovian processes under investigation compared with analytical methods. In this paper we used approximation of positive distribution functions, using phase-type distributions: mixtures of Erlang distributions and Coxian distribution – both 2 and 3 moments-matching algorithms was used. Analysis of M/G/1 and G/M/1 queueing systems showed, that moment-based queueing approximation gives high accuracy. In purpose to compute characteristics of M/G/1 and G/M/1 systems described in an event-based language, algorithms and software was created. Comparison to simulation results shows, that event-based language enables to get more precise results. Analysis of G/G/1 systems showed, that moment-based approximation can be used to analyse difficult queueing systems.

Orientadores: João Bosco Ribeiro do Val, Eduardo Fontoura Costa / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenahria Eletrica e de Computação / Made available in DSpace on 2018-08-13T22:22:47Z (GMT). No. of bitstreams: 1 Vargas_AlessandrodoNascimento_D.pdf: 1972819 bytes, checksum: 4746f70b31b4471193e27d462a933bc0 (MD5) Previous issue date: 2009 / Resumo: Esta monografia apresenta resultados de estabilidade e controle de sistemas estocásticos representados por operadores lineares com respeito ao estado e não-lineares em relação ao controle, quando avaliados no critério de custo médio a longo prazo (CMLP). A estrutura de controle n¿ao depende da historia do processo e pode ser usada, como caso particular, para representar diversos problemas de controle existentes na literatura. Em relação a estabilidade, mostra-se que o sistema estocástico e assintoticamente estável na media se o custo CMLP 'e finito e se as hipóteses de controlabilidade e observabilidade são validas. Para garantir a estabilidade uniforme do segundo momento do sistema, algumas condições adicionais são verificadas. Em relação ao controle, apresentam-se condições que asseguram a existência de política ótima estacionaria no problema CMLP para a classe de sistemas estudados. Uma aproximação é desenvolvida para se obter o mínimo CMLP, e esta aproximação é ilustrada numericamente no problema de regulação de sistemas lineares sujeitos a saltos markovianos, supondo que o controlador não possui acesso ao estado de Markov. Exemplos numéricos são empregados para ilustrar a teoria desenvolvida. / Abstract: This monograph presents results on stability and control of stochastic systems represented by linear operators with respect to the state which are non-linear with respect to the control. The control seeks to optimize a long run average cost (LRAC). The control structure does not depend on the past history of the process and it can be used, in particular, to represent a broad range of control problems that appears in the literature. Regarding the stability, it is shown that the stochastic system is asymptotically stable in the mean if the LRAC is finite and if controllability and observability assumptions are satisfied. To guarantee the uniform second moment stability, some additional conditions must be verified. With respect to the control, the main goal is to assure the existence of an optimal stationary policy for the LRAC problem within the class of systems considered, and some independent conditions are derived. An approximation for the minimum LRAC is obtained, and it is illustrated numerically for the regulator problem of Markov jump linear systems, under the assumption that the controller does not have access to the Markov state. Numerical examples illustrate the derived theory. / Doutorado / Automação / Doutor em Engenharia Elétrica

Orientador: Furio Damiani / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-21T21:06:15Z (GMT). No. of bitstreams: 1 Feijao_PedroCipriano_M.pdf: 2409509 bytes, checksum: ef809fef536991065abf131c6a599340 (MD5) Previous issue date: 2004 / Resumo: Um levantamento detalhado dos trabalhos em composição computacional será apresentado. Um algoritmo de composição e performance em tempo real de solos de jazz foi criado, inspirado no estilo bebop. Técnicas utilizadas por músicos de bebop durante os seus improvisos foram implementadas usando-se várias regras. Um novo modelo estocástico, baseado no raciocínio de um músico durante o seu solo, escolhe a saída do algoritmo. O usuário pode avaliar a saída do algoritmo em tempo-real, e isto será utilizado em um processo de aprendizado supervisionado para modificar os parâmetros do modelo estocástico. Algumas amostras de saídas do algoritmo serão mostradas, junto com as conclusões / Abstract: An extensive review of the most prominent works in the field of computer music is presented. A real-time algorithm for composition and performance of jazz solos in the style of bebop was created. Techniques that bebop musicians use on their solos were implemented using several rules. A new stochastic model, inspired by the thinking of a musician during his solo chooses the algorithm output. The user evaluates the algorithm output in real-time, and this input is used in a supervised learning process to change the stochastic model parameters. Samplings of the algorithm output are shown, along with concluding remarks / Mestrado / Eletrônica, Microeletrônica e Optoeletrônica / Mestre em Engenharia Elétrica

Orientadores: Paulo Regis Caron Ruffino, Pedro Jose Catuogno / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-04T04:01:14Z (GMT). No. of bitstreams: 1 Vieira_MarceloGoncalvesOliveira_M.pdf: 798971 bytes, checksum: f8f23c9cc6bf1a5acb8f987a59bb2b28 (MD5) Previous issue date: 2005 / Resumo: Este trabalho aborda a homotopia monotônica, uma variante apropriada de homotopia, de trajetórias de sistemas de controle. Primeiro é introduzido um conceito de regularidade para funções de controle e depois é considerada a definição de homotopia monotônica de trajetórias regulares de um sistema de controle 'sigma' evoluindo sobre uma variedade M. Em seguida são mostrados que o conjunto 'gama' ('sigma', x) de classes de homotopia monotônica das trajetórias regulares do sistema 'sigma' a partir de um estado fixo tem um estrutura de variedade diferenciável. Outro resultado importante é a caracterização para trajetórias monotonicamente homotópicas (contidas no conjunto dos pontos acessíveis a partir de x) via os levantamentos das mesmas à variedade 'gama' ('sigma', x). Finalmente, são feitas considerações sobre homotopia monotônica e trajetórias de um sistema estocástico / Abstract: This work accosts the monotonic homotopy, an appropriate variant of homotopy of trajectories of control systems. It is introduced a concept of regularity for control functions and it is considered the de¯nition of monotonic homotopy of regular trajectories of a given control system 'sigma' on a manifold M. Then it is shown that the set 'gama' ('sigma', x) of monotonic homotopy classes of regular trajectories of 'sigma' starting at a given fixed point x has a differentiable manifold structure with the same dimension of M. Another important result is the caracterization of monotonic homotopy of trajectories (on acessible points set starting at x) via the lifts of same trajectories on the manifold 'gama' ('sigma', x). Finally, we make same considerations about monotonic homotopy and trajectories of an stochastic system / Mestrado / Matematica / Mestre em Matemática

Este trabalho consiste no estudo de métodos de otimização aplicados em um problema de controle para sistemas lineares com saltos markovianos (SLSM). SLSM formam uma importante classe de sistemas que têm sido muito úteis em aplicações envolvendo sistemas sujeitos a falhas e outras alterações abruptas de comportamento. Este estudo enfoca diferentes métodos para resolução deste problema. Comparamos o método variacional com o de Newton, sob o ponto de vista do número de problemas resolvidos e pelo nível de sub-otimalidade obtido (relação entre os custos obtidos por estes métodos). Também propomos um novo método, o qual pode ser inicializado com soluções de equações de Riccati acopladas, e o comparamos com o método variacional. Além disso, para a comparação dos métodos, propomos um algoritmo que gerou dez mil exemplos / This work addresses optimizations methods applied to a control problem for linear systems with markovian jumps, which form an important class of systems that have been very useful in applications involving systems subject to failures and other abrupt changes. This study focuses on different methods for solving this problem. We compare the variational approach with the Newton method, in terms of the number of solved problems and the level of sub-optimality (ratio between the costs obtained by these approaches). We also propose a new method, which can be initialized with solutions of coupled Riccati equations, and we compare it with the variational approach. We have proposed an algorithm for creating ten thousand examples for the comparisons

Dans cette thèse, nous développons des méthodes de contrôle pour stabiliser des systèmes quantiques en temps continu sous mesures quantiques non-destructives. En boucle ouverte, ces systèmes convergent vers un état propre de l'opérateur de mesure, mais l'état résultant est aléatoire. Le rôle du contrôle est de préparer un état prescrit avec une probabilité de un. Le nouvel élément pour atteindre cet objectif est l'utilisation d'un mouvement Brownien pour piloter les actions de contrôle. En utilisant la théorie stochastique de Lyapunov, nous montrons stabilité exponentielle globale du système en boucle fermés. Nous explorons aussi la syntèse du contrôle pour stabiliser un code correcteur d'erreurs quantiques en temps continu. Un autre sujet d'intérêt est l'implementation de contrôles efficacement calculables dans un contexte expérimental. Dans cette direction, nous proposons l'utilisation de contrôles et filtres qui calculent seulement les characteristiques classiques du système, correspondant a la base propre de l'opérateur de mesure. La formulation de dites filtres est importante pour adresser les problèmes de scalabilité du filtre posées par l'avancement des technologies quantiques. / In this thesis, we develop control methods to stabilize quantum systems in continuous-time subject to quantum nondemolition measurements. In open-loop such quantum systems converge towards a random eigenstate of the measurement operator. The role of feedback is to prepare a prescribed eigenstate with unit probability. The novel element to achieve this is the introduction of an exogenous Brownian motion to drive the control actions. By using standard stochastic Lyapunov techniques, we show global exponential stability of the closed-loop dynamics. We explore as well the design of the control layer for a quantum error correction scheme in continuous-time. Another theme of interest is towards the implementation of efficiently computable control laws in experimental settings. In this direction, we propose the use control laws and of reduced-order filters which only track classical characteristics of the system, corresponding to the populations on the measurement eigenbasis. The formulation of these reduced filters is important to address the scalability issues of the filter posed by the advancement of quantum technologies.

The field of mathematical modelling for pedestrian dynamics has attracted significant scientific attention, with various models proposed from perspectives such as kinetic theory, statistical mechanics, game theory and partial differential equations. Often such investigations are seen as being a part of a new branch of study in the domain of applied physics, called sociophysics. Our study proposes three models that are tailored to specific scenarios of crowd dynamics. Our research focuses on two primary issues. The first issue is centred around pedestrians navigating through a partially dark corridor that impedes visibility, requiring the calculation of the time taken for evacuation using a Markov chain model. The second issue is posed to analyse how pedestrians move through a T-shaped junction. Such a scenario is motivated by the 2022 crowd-crush disaster took place in the Itaewon district of Seoul, Korea. We propose a lattice-gas-type model that simulates pedestrians’ movement through the grid by obeying a set of rules as well as a parabolic equation with special boundary conditions. By the means of numerical simulations, we investigate a couple of evacuation scenarios by evaluating the mean velocity of pedestrians through the dark corridor, varying both the length of the obscure region and the amount of uncertainty induced by the darkness. Additionally, we propose an agent-based-modelling and cellular automata inspired model that simulates the movement of pedestrians through a T-shaped grid, varying the initial number of pedestrians. We measure the final density and time taken to reach a steady pedestrian traffic state. Finally, we propose a parabolic equation with special boundary conditions that mimic the dynamic of the pedestrian populations in a T-junction. We solve the parabolic equation using a random walk numerical scheme and compare it with a finite difference approximation. Furthermore, we prove rigorously the convergence of the random walk scheme to a corresponding finite difference scheme approximation of the solution.

La biología sintética se define como la ingeniería de la biología: el (re)diseño y construcción de nuevas partes, dispositivos y sistemas biológicos para realizar nuevas funciones con fines útiles, que se basan en principios elucidados de la biología y la ingeniería. Para facilitar la construcción rápida, reproducible y predecible de estos sistemas biológicos a partir de conjuntos de componentes es necesario desarrollar nuevos métodos y herramientas. La tesis plantea la optimización multiobjetivo como el marco adecuado para tratar los problemas comunes que surgen en el diseño racional y el ajuste óptimo de los circuitos genéticos sintéticos. Utilizando un enfoque clásico de ingeniería de sistemas, la tesis se centra principalmente en: i) el modelado de circuitos genéticos sintéticos basado en los primeros principios, ii) la estimación de parámetros de modelos a partir de datos experimentales y iii) el ajuste basado en modelos para lograr el desempeño deseado de los circuitos. Se han utilizado dos circuitos genéticos sintéticos de diferente naturaleza y con diferentes objetivos y problemas: un circuito de realimentación de tipo 1 incoherente (I1-FFL) que exhibe la importante propiedad biológica de adaptación, y un circuito de detección de quorum sensing y realimentación (QS/Fb) que comprende dos bucles de realimentación entrelazados -uno intracelular y uno basado en la comunicación de célula a célula- diseñado para regular el nivel medio de expresión de una proteína de interés mientras se minimiza su varianza a través de la población de células. Ambos circuitos han sido analizados in silico e implementados in vivo. En ambos casos, se han desarrollado modelos de estos circuitos basado en primeros principios. Se presta especial atención a ilustrar cómo obtener modelos de orden reducido susceptibles de estimación de parámetros, pero manteniendo el significado biológico. La estimación de los parámetros del modelo a partir de los datos experimentales se considera en diferentes escenarios, tanto utilizando modelos determinísticos como estocásticos. Para el circuito I1-FFL se consideran modelos determinísticos. Aquí, la tesis plantea la utilización de modelos locales utilizando la optimización multiobjetivo para realizar la estimación de parámetros del modelo bajo escenarios con estructura de modelo incompleta. Para el circuito QS/Fb, una estructura controlada por realimentación, el problema tratado es la falta de excitabilidad de las señales. La tesis propone una metodología de estimación en dos etapas utilizando modelos estocásticos. La metodología permite utilizar datos de curso temporal promediados de la población y mediciones de distribución en estado estacionario para una sola célula. El ajuste de circuitos basado en modelos para lograr un desempeño deseado también se aborda mediante la optimización multiobjetivo. Para el circuito QS/Fb se realiza un análisis estocástico completo. La tesis aborda cómo tener en cuenta correctamente tanto el ruido intrínseco como el extrínseco, las dos principales fuentes de ruido en los circuitos genéticos. Se analiza el equilibrio entre ambas fuentes de ruido y el papel que desempeñan en el bucle de realimentación intracelular, y en la realimentación extracelular de toda la población. La principal conclusión es que la compleja interacción entre ambos canales de realimentación obliga al uso de la optimización multiobjetivo para el adecuado ajuste del circuito. En esta tesis además del uso adecuado de herramientas de optimización multiobjetivo, la principal preocupación es cómo derivar directrices para el ajuste in silico de parámetros de circuitos que puedan aplicarse de forma realista in vivo en un laboratorio estándar. Como alternativa al análisis de sensibilidad de parámetros clásico, la tesis propone el uso de técnicas de clustering a lo largo de los frentes de Pareto, relacionando el compr / La biologia sintètica es defineix com l'enginyeria de la biologia: el (re) disseny i construcció de noves parts, dispositius i sistemes biològics per a realitzar noves funcions útils que es basen a principis elucidats de la biologia i l'enginyeria. Per facilitar la construcció ràpida, reproduïble i predictible de aquests sistemes biològics a partir de conjunts de components és necessari desenvolupar nous mètodes i eines. La tesi planteja la optimització multiobjectiu com el marc adequat per a tractar els problemes comuns que apareixen en el disseny racional i l' ajust òptim dels circuits genètics sintètics. Utilitzant un enfocament clàssic d'enginyeria de sistemes, la tesi es centra principalment en: i) el modelatge de circuits genètics sintètics basat en primers principis, ii) l' estimació de paràmetres de models a partir de dades experimentals i iii) l' ajust basat en models per aconseguir el rendiment desitjat dels circuits. S'han utilitzat dos circuits genètics sintètics de diferent naturalesa i amb diferents objectius i problemes: un circuit de prealimentació de tipus 1 incoherent (I1-FFL) que exhibeix la important propietat biològica d'adaptació, i un circuit de quorum sensing i realimentació (QS/Fb) que comprèn dos bucles de realimentació entrellaçats -un intracel·lular i un basat en la comunicació de cèl·lula a cèl·lula- dis-senyat per regular el nivell mitjà d'expressió normal d'una proteïna d'interès mentre es minimitza la seua variació al llarg de la població de cèl·lules. Els dos circuits han estat analitzats in silico i implementats in vivo. En tots dos casos, s'han desenvolupat models basats en primers principis d'aquests circuits. Després es presta especial atenció a delinear com obtenir models d'ordre reduït susceptibles de estimació de paràmetres, però mantenint el significat biològic. L' estimació dels paràmetres del model a partir de les dades experimentals es considera en diferents escenaris, tant utilitzant models determinístics com estocàstics. Per al circuit I1-FFL es consideren models determinístics. La tesi planteja la utilització de models locals utilitzant la optimització multiobjectiu per realitzar l'estimació de parametres del model sota escenaris amb estructura de model incompleta (dinàmica no modelada). Per al circuit de QS/Fb, una estructura controlada per realimentació, el problema tractat és la manca d'excitabilitat dels senyals. La tesi proposa una metodologia de estimació en dues etapes utilitzant models estocàstics. La metodologia permet utilitzar dades de curs temporal promediats de la població i mesures de distribució en estat estacionari d'una sola una cèl·lula. L' ajust de circuits basat en models per aconseguir el rendiment desitjat dels circuits també s' aborda mitjançant la optimització multiobjectiu. Per al circuit QS/Fb, es fa un anàlisi estocàstic complet. La tesi aborda com tenir en compte correctament tant el soroll intrínsec com l' extrínsec, les dues principals fonts de soroll en els circuits genètics sintètics. S' analitza l'equilibri entre dues fonts de soroll i el paper que exerceixen en el bucle de realimentació intracel·lular, les i en la realimentació extracel·lular de tota la població. La principal conclusió es que la complexa interacció entre els dos canals de realimentació fa necessari l' ús de la optimització multiobjectiu per al adequat ajust del circuit. En aquesta tesi, a més de l'ús adequat d'eines d'optimització multiobjectiu, la principal preocupació és com derivar directives per al ajust in silico de paràmetres de circuits que puguin aplicar-se de forma realista en viu en un laboratori estàndard. Així, com a alternativa a l'anàlisi de sensibilitat de paràmetres clàssic, la tesi proposa l'ús de l' tècniques de l'agrupació al llarg dels fronts de Pareto, relacionant el compromís de dessempeny amb les regions en l'espai d'paràmetres. / Synthetic biology is defined as the engineering of biology: the deliberate (re)design and construction of novel biological and biologically based parts, devices and systems to perform new functions for useful purposes, that draws on principles elucidated from biology and engineering. Methods and tools are needed to facilitate fast, reproducible and predictable construction of biological systems from sets of biological components. This thesis raises multi-objective optimization as the proper framework to deal with common problems arising in rational design and optimal tuning of synthetic gene circuits. Using a classical systems engineering approach, the thesis mainly addresses: i) synthetic gene circuit modeling based on first principles, ii) model parameters estimation from experimental data and iii) model-based tuning to achieve desired circuit performance. Two gene synthetic circuits of different nature and with different goals and inherent problems have been used throughout the thesis: an Incoherent type 1 feedforward circuit (I1-FFL) that exhibits the important biological property of adaptation, and a Quorum sensing/Feedback circuit (QS/Fb) comprising two intertwined feedback loops -an intracellular one and a cell-to-cell communication-based one-- designed to regulate the mean expression level of a protein of interest while minimizing its variance across the population of cells. Both circuits have been analyzed in silico and implemented in vivo. In both cases, circuit modeling based on first principles has been carried out. Then, special attention is paid to illustrate how to obtain reduced order models amenable for parameters estimation yet keeping biological significance. Model parameters estimation from experimental data is considered in different scenarios, both using deterministic and stochastic models. For the I1-FFL circuit, deterministic models are considered. In this case, the thesis raises ensemble modeling using multi-objective optimization to perform model parameters estimation under scenarios with incomplete model structure (unmodeled dynamics). For the QS/Fb gene circuit, a feedback controlled structure, the lack of excitability of the signals is the problem addressed. The thesis proposes a two-stage estimation methodology using stochastic models. The methodology allows using population averaged time-course data and steady state distribution measurements at the single-cell level. Model-based circuit tuning to achieve desired circuit performance is also addressed using multi-objective optimization. First, for the QS/Fb feedback control circuit, a complete stochastic analysis is performed. Here, the thesis addresses how to correctly take into account both intrinsic and extrinsic noise, the two main sources of noise in gene synthetic circuits. The trade-off between both sources of noise, and the role played by in the intracellular single-cell feedback loop and the extracellular population-wide feedback is analyzed. The main conclusion being that the complex interplay between both feedback channels compel the use of multi-objective optimization for proper tuning of the circuit to achieve desired performance. Thus, the thesis wraps up all the previous results and uses them to address circuit tuning for desired performance. Here, besides the proper use of multi-objective optimization tools, the main concern is how to derive guidelines for circuit parameters tuning in silico that can realistically be applied in vivo in a standard laboratory. Thus, as an alternative to classical parameters sensitivity analysis, the thesis proposes the use of clustering techniques along the optimal Pareto fronts relating the performance trade-offs with regions in the circuits parameters space. / This work has been partially supported by the Spanish Government (CICYT DPI2014- 55276-C5-1) and the European Union (FEDER). The author was recipient of the grant Formación de Personal Investigador by the Universitat Politècnica de València, subprogram 1 (FPI/2013-3242). She was also recipient of the competitive grants for pre-doctoral stays Erasmus Student Placement-European Programme 2015, and FPI Mobility program 2016 of the Universitat Politècnica de València. She also received the competitive grant for a pre-doctoral stay Becas de movilidad para Jóvenes Profesores e Investigadores 2016, Programa de Becas Iberoamérica of the Santander Bank. / Boada Acosta, YF. (2018). A systems engineering approach to model, tune and test synthetic gene circuits [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/112725 / TESIS

No / This paper presents a novel concept to describe the couplings among the outputs of the stochastic systems which are represented by NARMA models. Compared with the traditional coupling description, the presented concept can be considered as an extension using statistical independence theory. Based on this concept, the decoupling control in statistical sense is established with the necessary and sufficient conditions for complete decoupling. Since the complete decoupling is difficult to achieve, a control algorithm has been developed using the Cauchy-Schwarz mutual information criterion. Without modifying the existing control loop, this algorithm supplies a compensative controller to minimise the statistical couplings of the system outputs and the local stability has been analysed. In addition, a further discussion illustrates the combination of the presented control algorithm and data-based mutual information estimation. Finally, a numerical example is given to show the feasibility and efficiency of the proposed algorithm.

Yes / This paper investigates the stabilisation problem and consider transient optimisation for a class of the multi-input-multi-output (MIMO) semi-linear stochastic systems. A control algorithm is presented via an m-block backstepping controller design where the closed-loop system has been stabilized in a probabilistic sense and the transient performance is optimisable by optimised by searching the design parameters under the given criterion. In particular, the transient randomness and the probabilistic decoupling will be investigated as case studies. Note that the presented control algorithm can be potentially extended as a framework based on the various performance criteria. To evaluate the effectiveness of this proposed control framework, a numerical example is given with simulation results. In summary, the key contributions of this paper are stated as follows: 1) one block backstepping-based output feedback control design is developed to stabilize the dynamic MIMO semi-linear stochastic systems using a linear estimator; 2) the randomness and probabilistic couplings of the system outputs have been minimized based on the optimisation of the design parameters of the controller; 3) a control framework with transient performance enhancement of multi-variable semi-linear stochastic systems has been discussed. / Higher Education Innovation Fund (No. HEIF 2018-2020), De Montfort University, Leicester, UK.