Abstractions of Hamiltonian control systems

Given a control system and a desired property, an abstracted system is a reduced system that preserves the property of interest while ignoring modeling detail. In previous work, abstractions of linear and nonlinear control systems were considered while preserving reachability properties. In this paper, we consider the abstraction problem for Hamiltonian control systems, where, in addition to the property of interest we also preserve the Hamiltonian structure of the control system. We show how the Hamiltonian structure of control systems can be exploited to simplify the abstraction process. We then focus on local accessibility preserving abstractions, and provide conditions under which local accessibility properties of the abstracted Hamiltonian system are equivalent to the local accessibility properties of the original Hamiltonian control system

Designing Air Intake System for Engine Performance and Efficiency Optimisation

This study is aimed to study the feasibility of using fish scale as the adsorbent to remove heavy metal from its aqueous solution. The adsorption nature of three types of metals namely Copper (Cu), Nickel (Ni) and Lead (Pb) on fish scale are studied independently, in a binary metal environment, where another competitive metal is also present during the adsorption process and finally in a continuous adsorption process

ALGORITHM FOR SELF-TUNING THE PID CONTROLLER

An algorithm for self-tuning the PID controller to the second order systems is proposed in this paper. The proposed self-tuning procedure was developed according to the maximum stability degree criterion, the criterion that permits to achieve the high stability degree, good performance and robustness of the system. According to the proposed algorithm, the controller can be tuned according to the parameters that characterize the process and they can be determinate from the experimental response of the open loop system. To demonstrate the efficiency of proposed procedure of self-tuning the PID controller, the computer simulation was performed and the obtained results were compared with Haeri’s method, maximum stability degree method with iterations and parametrical optimization method. According to the developed algorithm, it was performed the control of the thermal regime in the oven

Sensorless Control of a Stepper Motor Based on Higher Order Sliding Modes

International audienceA robust control for a stepper motor with no position nor velocity sensors and only needing current and voltage measurements is designed. Second order sliding mode based observers are realized to estimate both rotor angular position and velocity. Moreover, a robust control law, which is also based on second order sliding modes and which uses the estimates of the observer, is designed. The stability of the observer based control loop is discussed. The results obtained in simulations indicate the usefulness and the robustness of the method

Backstepping and Sequential Predictors for Control Systems

We provide new methods in mathematical control theory for two significant classes of control systems with time delays, based on backstepping and sequential prediction. Our bounded backstepping results ensure global asymptotic stability for partially linear systems with an arbitrarily large number of integrators. We also build sequential predictors for time-varying linear systems with time-varying delays in the control, sampling in the control, and time-varying measurement delays. Our bounded backstepping results are novel because of their use of converging-input-converging-state conditions, which make it possible to solve feedback stabilization problems under input delays and under boundedness conditions on the feedback control. Our sequential predictors work is novel in its ability to cover time-varying measurement delays and sampling which were beyond the scope of existing sequential predictor methods for time-varying linear systems, and in the fact that the feedback controls that we obtain from our sequential predictors do not contain any distributed terms

Designing Air Intake System for Engine Performance and Efficiency Optimisation

This study is aimed to study the feasibility of using fish scale as the adsorbent to remove heavy metal from its aqueous solution. The adsorption nature of three types of metals namely Copper (Cu), Nickel (Ni) and Lead (Pb) on fish scale are studied independently, in a binary metal environment, where another competitive metal is also present during the adsorption process and finally in a continuous adsorption process

Support optimization tool for aero engine configuration systems

In an aircraft engine, basic functionality of configuration system is to form the network of supply lines for air, fuel & oil. Configuration hardware mainly consists of tubes, ducts, valves & support brackets. Many of the Aircraft engines are failed due to failure of fuel pipes and caused big hazards. Hence to avoid accidents, hard wares are designed properly against the failures. In order to use the resources properly optimum design of hard wares is necessary. The two basic design requirements for configuration systems are: (a) high cycle fatigue (vibratory stresses) and (b) low cycle fatigue (thermally induced stresses). Under these design requirements optimum design can be done through the selection of critical design parameters. Critical design parameters in a configuration system considered in the present study are: (i) Support location for the tube layout and (ii) Bracket support type at this location. The judicious selections of these two design parameters greatly influence the high cycle fatigue and low cycle fatigue life. This also helps in reducing the weight and cost of the system. Design optimisation is an iterative process and computer software can help to obtain an optimum design. In the present study, user friendly software is developed using TCL/TK environment. This is linked with a commercial software ANSYS and PEZ tool. ANSYS is used to carry out the structural analysis considering preliminary support locations. Analysis results from ANSYS are the inputs for the optimization analysis. PEZ tool modifies the support locations based on the optimization results. ANSYS will analyse the structure once again based on the modified support locations. This loop will continue till target reaches