Sharif Digital Repository

Using fractional order calculus to model complex phenomena with combined behavior (i.e., dissipative, capacitive and inertia behavior) is one of the most recent research fields in the world. These accurate models lead to better understanding of the phenomena. For example, consider viscoelastic materials. In early models, dissipative behavior is separated from capacitive behavior but by using fractional order models, these two behaviors are considered simultaneously thus the complexity of the model would be reduced. To use fractional order models in real-life engineering applications, it is important to investigate the dynamics of these systems. Unfortunately, there are a few proper... 

The constrained nonlinear systems with large operating regions have attracted great attention due to their correspondence with the most practical systems. There are several tools such as gain scheduling and Nonlinear Model Predictive Control (NMPC) to control them. Gain scheduling, with ability to provide stability guarantees between the estimated stability regions overlapping each other and to cover a large space of the allowable operating range of the system, is an attractive practical approach to control the systems with large operating regions. But this strategy do not account for constraints explicitly by online optimization. On the contrary, NMPC handles constraints on the manipulated... 

Selecting an appropriate control structure is an important subject in the design of control systems. Distillation column is one of the most popular and widely used unit operations in industry which complete understanding of its operability and controllability is one of the most important issues in the process control engineering. The present work studies the method of Output Controllability Index for nonlinear systems and compares it with Relative Gain Array and Condition Number. By using this index, the extent of intrinsic controllability of a process can be identified quantitatively in the absence of any controller. Also, the controllability of the process can be stated numerically or... 

This research is trying to investigate the control algorithms of unknown control direction systems. Since Nussbaum function is the most common method which in used for these systems this research focus on this algorithm to overcome control the effect of unknown control direction. This research study the performance of different control algorithms in controlling such systems followed by analysis of two control modes of continuous and discrete using Nussbam Function. Additionally, in continuous mode, the performance of two methods of backstepping and liding mode has been compared on the given system in variety of situation. Results demonstrate that backstepping method shows better performance... 

Disturbance is one of the inseparable components of the mechanical systems which cannot be avoided. In these systems a number of inner and outer sources exist which are the cause of disturbance. Abrupt changes in torque, uncertainty in parameters, mechanical impulses and external forces on robot’s parts all can be mentioned as examples which introduce disturbance that affects the output of mechanical and robotic systems. Therefore, disturbance rejection is considered indispensable in robotic control systems. There are number of problems which are associated with disturbance rejection. In several methods, mostly optimization based methods, system fails to completely reject the disturbance and... 

One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameters were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this thesis, we employed a nonlinear system identification method for identification,... 

In this thesis, partitioning of multi inputs nonlinear dynamical systems into distinct subsystems with the goal of designing decentralized, distributed, and cooperative predictive controllers for reducing the computational load and time in practical implementations has been studied. At first, the concept of dynamical systems graph is introduced and the problem of decomposing nonlinear dynamical systems into distinct subsystems has been converted to the problem of decomposing dynamical systems graph into separate subgraphs. The proposed method for decomposition of the dynamical system graph is represented as a linear integer optimization programing where the separated subgraphs is obtained by... 

Many processes and real world systems indicate nonlinear behavior and operate either naturally in multiple regions or in a wide range of operation space. Modelling and control of these systems by nonlinear methods needs to have a deep insight. Furthermore, the nonlinear methods leads to complexity issues. To overcome these problems, multi-model methods are introduced which consist of two steps, decomposition and combination. In decomposition step, the complex system is divided into a set of simple models; in the combination step, the behavior of local models are combined. How to decompose to local models and how to combine them are two main questions in this area which not answered... 

Time delay systems may arise in practice for a variety of reasons, such as autonomous systems (without feedback control), and the delay is the result of an intrinsic property of the system. Sometimes the delay results from feedback control action, instead from the system itself; that is, due to the nature of the system, the feedback is delayed. Another type of delays of similar effects may be incurred due to delayed measurements. In both delayed control and delayed measurement, the delay is usually considered undesirable, which has the tendency to deteriorate the system performance or even destabilize the system.

In this thesis, three types of adaptive controller are proposed for... 

The purpose of this paper is to design an integrated controller and observer (ICO) for a nonlinear system using genetic programming. ICO is a function that constructs control command directly from the measured state variables of the system. It means that, this function should imitate the behavior of the observer and controller and control the system with acceptable performance in different initial conditions, at the presence of disturbances and system uncertainties. The complexity of this design method, is not related to the complexity of the plant, in fact, the complexity in plant just effects at run time, but the design procedure does not change. So, if exact model of plant exist, using... 

Time delay usually exists due to different causes in actuator dynamics of robot manipulator. If this time delay is not considered to compensate, we will encounter with instability or oscillation. In this dissertation, we propose a nonlinear predictor feedback to achieve exponentially convergence in the presence of constant and known delay in actuator dynamics of robot manipulator. It is assumed that the dynamics of robot manipulator is known. Since the robot manipulator system is forward-complete, we don’t have explosive instability in dead time and it stays bounded until the control kicks in t=D. Our approach to stability proof of proposed controller employs PDE form to present the delay in... 

Inthis thesis, we provide a reduced multiple linear approximationfornonlinear systems. This approximationis a weighted summation of reduced order models thatapproximates the states or output(s) of the nonlinear system. It can be used inreal-time control instead of high-ordernonlinear models in order toreduce thecomputational cost. The reduction of computation cost is claimed qualitatively, based on the linearity of the approximation and its less order compared to the original model. To form amultiple modelapproximation eachlinearmodelis obtained from linearization atanoperating point. Then,each model is reduced byalinearreduction method. We used truncation and balanced residualization... 

This project presents algorithms for intelligent control of the viral load in a HIV-1 infection model. The first part of thesis was dedicated to the study of the three states model adopted to describe the HIV-1 infection. A sensitivity analysis of the model parameters was described and computer simulations were provided to show the influence of the parameters explicitly. Then, an internal model control based on neural networks was implemented on the introduced infection model with including the RTIs and PIs drugs efficacies as control input. A stable adaptive neuro-control approach was presented for affine in the control nonlinear dynamical systems, whose nonlinearities were assumed to be... 

We consider a system of nonlinear partial differential equations corresponding to a generalization of a mathematical model for geographical spreading of dengue disease. the mosquito population is divided into subpopulations: winged form (mature female mosquitoes) and aquatic form (comprising eggs, larvae and pupae); the human population is divided into the subpopulations:susceptible, infected and removed (or immune). On the other hand we allow higher spatial dimensions and also parameters depending on space and time. is last generalization is done to cope with possible abiotic effects as variations in temperature, humidity, wind velocity, carrier capacities, and so on; thus, the results... 

This thesis is concerned with stability and tracking of nonlinear noisy Lipschitz systems over the packet erasure channel with feedback acknowledgment when system and measurement are due to bounded noises. The desired stability and tracking criteria is bounded stability and tracking in probability. Two approaches are adopted to address the desired stability and tracking performance, one is based on the Chebyshev inequality and the other is based on the Binomial distribution. It is illustrated that when the erasure probability is large, the approach based on the Chebyshev inequality provides a better bound for stability and tracking in probability; while, when the erasure probability is... 

In this thesis, a new non-linear control synthsis technique (θ - D) approximation) is discussed. This approach achieves suboptimal solutions to a class of non-linear optimal control problems characterized by a quadratic cost function and a plant model that is a_ne in control. An approximate solution to the Hamilton-Jacobi-Bellman (HJB) equation is sought by adding perturbations to the cost function. By manipulating the perturbation terms both asymptotic stability and suboptimality properties are obtained. The new technique overcomes the large-control-for-large-initial-states problem that occurs in some other Taylor series expansion based methods. Also this method does not require excessive... 

A modeling framework is proposed for complex chemical process networks. Concept such as passivity systems, thermodynamic function and graph theory are some important and applicable concept which seems to be useful for process network. The state is represented by energy, volume and mass inventories. The dynamic behavior of the process system is constrained so that all trajectories satisfy the first and second laws of thermodynamics. The concavity of the entropy function is used to define a storage function for passivity design. The proposed storage function is closely related to the Gibbs tangent plane condition. Stability analysis, pairing and controller design could be done by this new... 

In this paper, an approach is proposed to estimate the location of the leaks in oil pipelines. The pipeline possesses a system of Partial Differential Equations (PDE). First, a closed-form solution is applied to the pipeline equations and the leakage location is found solving the steady-state equations. To tackle the case where the pressure and flowrate do not reach constant values, the initial estimations are provided by the closed-form solution. Then, the pressures, flow rates, and leakage coefficient are estimated by solving the system of differential equations. This system is then discretized with respect to the location variable to yield the system state equations which, in turn, are... 

Design of optimal controllers for nonlinear systems and even for linear systems is one of the most important parts of the control science. In optimal controller design, our aim is to maximize or minimize some kind of cost function associated with that particular problem. Such cost functions are usually combining the overall control effort, system’s energy, or some other important specifications of the system. Explicit solution for linear quadratic controllers exists under some mild conditions such as stabilizability of the system. The solution is in the form of a full state-feedback law. But in practical problems, we may not have access to all of the system state variables. The problem can... 

The stability of dynamic systems has long been discussed in the theory of control and many people and experts have researched in this field and important results have been obtained from their research. In the real world, systems stability is the premise of controlling their behavior. In fact, systems that are unstable will not be controllable without stability. Therefore, the stability of the systems is discussed and at the same time the control expectations of the system will be raised. The systems of the surrounding world behave nonlinearly; Therefore, their exact stability is not debatable with linear approaches and requires stronger mathematics and attention to specific behaviors of...