Sharif Digital Repository

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... 

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... 

The demand for safety operating systems is growing with the new developments in technology. One of the important and critical issues in system monitoring is the capability of the system to detect probable faults and hazards. In model-based fault detection one specific diagnostic signal called residual should be generated for each fault that is only sensitive to a particular fault and independent of other faults and disturbances. In this thesis we try to investigate the nonlinear geometric approach in fault detection of a class of mechanical systems. After a brief introduction to geometric tool for nonlinear inputaffine systems and conditions in which output is decoupled from input, we... 

This work addresses adaptive neural control for a class of stochastic nonlinear systems in the nonstrict-feedback form. By introducing a nonlinear mapping, the output-constrained stochastic system transformed into a new system without constraint. The systems under study is subject to state time delay, input nonlinearity, unavailable states, unknown dynamics and actuator failure. The appropriate Lyapunov-Krasovskii functionals is used to compensate the time-delay effects, the neural network is used to approximate the unknown nonlinearities, the linear state observer is constructed to estimate the unmeasured states, and a variable separation method is used to deal with the difficulty caused by... 

In this thesis, the goal is to design a predictive controller using orthogonal functions. In this way, we convert the minimization interval of the objective function into several subintervals, and in each interval, we consider the states and inputs of the system in terms of unknown coefficients of orthogonal functions, and we find the unknown coefficients according to the cost function and the dynamics of the system. According to the found coefficients, the control signal and modes are found in each interval. The length of the intervals, the number of foundations, the type of foundations and their effects on the system response and cost distribution are the questions that will be answered in...