find a controller K, which based on the information v, generates a control signal u, which compensates the influence of w on z and minimizes the closed loop norm w to z. The paper is organized as follow, section 2 represents the nuclear reactor model (actual and nominal plants).Section3 introduce the H ∞ optimal control while the simulation results
The internal components of the reactor vessel are supported from the bottom head and/or vessel wall. The reactor core is made up of fuel assemblies (15), control rods (16), and neutron monitoring instruments (24). The structure surrounding the active core consists of a core shroud (14), core plate (17), and top guide (12). The components making up the remainder of the reactor vessel internals are the jet pump assemblies (13), steam separators (6), steam dryers (3), feedwater spargers (8), and core spray spargers (11). The jet pump assemblies are located in the region between the core shroud and the vessel wall, submerged in water. The jet pump assemblies are arranged in two semicircular groups of ten, with each group being supplied by a separate recirculation pump.
3.3.2. Thermal Hydraulic Design
The main objective and the unique challenge of the Flexible Conversion Ratio reactor thermal hydraulic design is the requirement that the reactorsystems be able to accept cores with different fuel loadings. Two limiting cases of core configurations with zero and unity conversion ratios are considered. Due to significant variation of the fuel composition, the unity and zero conversion ratio cores have different numbers of control rods, power peaking maps, coolant velocities, decay heat curves, and reactivity coefficients. All of the differences must be accounted for in the thermal hydraulic design in order to assure that the inlet and outlet temperatures are the same for both cores. The same inlet and outlet temperature condition is necessary because both core designs are intended for the same Power Conversion System. TRU fuel and lead coolant impose temperature limits on the fuel cladding. Therefore, both cores must be designed within the limits while maximizing the core outlet temperature for better plant efficiency. Another major challenge of the thermal hydraulic design is the achievement of a large power rating in a small footprint plant. A pool-type reactor plant with 2400 MWt power output and Intermediate Heat Exchangers (IHX) inside the pool has the advantages of small footprint, elimination of intermediate loop, and benefit of economy of scale. Pool design also eliminates certain types of accidents, such as Loss of Coolant Accident from primary coolant pipe break. However, such a large power rating raises challenges related to the tight space within the vessel, where a core, primary coolant pumps, and four IHXs must be placed inside the vessel. While placement of the IHX inside the vessel eliminates additional loops, there is a possibility of ingress of the secondary coolant, supercritical carbon dioxide, at high pressure, in the core. Ingress of the gas results in coolant voiding which can lead to reactivity increase and the development of hot spots on the cladding. Therefore, the core must be protected against such incidents. IHX design is important for the overall plant performance. Iterative design and analysis of the IHX is necessary since its performance directly impacts the efficiency of the secondary side as well as the primary coolant pumping requirements.
The new definition for the SoS is the starting point for the development of methodology that may lead to systematic design. Examining the rules of composition of the subsystems and their coordination as agents in a larger system defines a challenging new area for research and requires links across many disciplines. Examining in detail the special features of the different classes of SoS is crucial in the effort to provide a quantitative formulation of the notion of “systems play” which may take different forms in the different classes. This is also crucial in quantifying the notion of emergence in the SoS context. The potential for applications is well beyond the traditional engineering field, when powerful modeling tools are defined that may allow the study of design and decision problems of the respective classes of SoS. It is worth mentioning at this point that the majority of SoS are products of “physical”, or “technological “ evolution, rather than products of systematic design and understanding evolutionary processes leading to the formation of SoS is crucial.
ZF Marine’s Joystick Maneuvering System, operates off of the SmartCommand control system, and offers simple and intuitive vessel control at your fingertips. JMS manages the vessel’s main engines, ZF transmis- sions and bow thruster all through the joystick, giving the operator precise speed, smooth maneuvering and easy docking. JMS offers vessel operators the ability to move the vessel sideways, rotate 360 degrees on the vessel’s axis, and hold vessel position accounting for current and wind.
Controllable saturation reactors are widely used in reactive power compensation. The control system of controllable saturation reactor determines adaption speed, accuracy, and stability. First, an innovative type of controllable saturation reactor is introduced. After that the control system is designed, and a self-tuning algorithm in PID controller is proposed in the paper. The algorithm tunes PID parameters automatically with different error signals caused by varied loads in power system. Then the feasibility of the above algorithm is verified by Simulink module of Matlab soft- ware. The results of simulation indicate that the control system can efficiently reduce adaption time and overshoot.
In traditional feedback controllers, control action is adjusted in response to a change in the output set-point of a system. Model predictive control (MPC) is a technique that focuses on constructing controllers that can adjust the control action before a change in the output set-point actually occurs. This predictive ability, when combined with traditional feedback operation, enables a controller to make adjustments that are smoother and closer to the optimal control action values. Fig. 1 shows the block diagram of model predictive control. A model of the process is used to predict the future evolution of the process to optimize the control signal. At each control interval, MPC algorithm attempts to optimize the future plant behavior by computing a sequence of future manipulated variable adjustments. The first input in the optimal sequence is then sent into the plant and the entire calculation is repeated at subsequent control intervals.
In solving optimization problems, as the number of reactor sections increases, it is expected that the discrete profile estimates the continuous profile more closely at the expense of significant raise of computation time. Table 2 and Fig. 2 show effect of number of sections in optimizing of the reactor temperature. As can be seen from Table 2, as number of sections exceeds five, no considerable changes are observed in polymer final characteristics. Therefore, to avoid increase of computation load, five zones have been chosen for further analysis. Effects of weight factor w on the optimization results for PD ref = PD feed and PD ref = 2.4 are shown
4 a practical control approach. Nevertheless, it still requires knowledge of the unmeasured states by the I/O feedback 7 . To resolve this issue, some observer based nonlinear control approaches have been presented 14-20 . Some advanced industrial applications, e.g. alkylation of benzene with ethylene process, expect high performance such as, strong robustness and fast response. Even the above mentioned observer based control approaches can in practice only achieve (asymptotical) stability, when high gain control is applied. Such high gain control may lead to control input saturation, particularly in the instance of the large initial track error 21-22 . If there exist external disturbances, it is very challenging to design observers and output feedback controllers for CSTRs.
master, which would usually difficult, one possible method of reducing the dead time of the jacket outlet to the jacket inlet. This usually is not recommended, because when this is done, the slave will do much less work because the nonlinear dynamics of the cascade slave loop is to move the measurement from the jacket have been transferred into the master loop. There are several advantages of cascade control, effectively accounts for external disturbances, reduces dead time in variable response, and compatible with other ControlSystems, such as Feed-Back and Feed-Forward Control. Commonly used for chemical reactors is a PI cascade control structure, which provides a robust operation but often lacks in control performance. The cascaded control structure (CCs), which is illustrated by the block diagram in Figure 4.5, is configured such that the master controller in the outer loop is the primary controller that regulates the primary controlled variable (reactor temperature 𝑇) by setting the set-point of the inner loop. The slave controller in the inner loop is the secondary controller adjusts the
A BSTRACT : In this paper, we study the control of a fixed catalyst multi-staged reactor. This reactor is an industrial one, used for sulphur dioxide oxidation. The aim of this work is to determine the best control strategy between one whom consist to control the production capacity of the reactor and another, more usual, whom consist to control the maximal catalyst temperature in order to avoid the occurrence of hot spot inside the catalyst. Command algorithm used is the generalised predictive control (GPC) with on line process identification. The results obtained by numerical simulation show that the control of the production capacity is possible and also preferable, since the reactor is strongly influenced by inlet reagent concentrations and, on the other hand, it presents a notable thermal stability conferred by the thermal inertia due to the important catalyst mass.
Research and development (R&D) of the Generation-IV nuclear reactors have been carried out worldwide under the coordination of the Generation-IV International Forum (GIF). Supercritical Pressure Light Water Reactor (SCWR) is selected as one of the new reactor concepts considering its significant improvements in the thermal efficiency (44%) and economics. It uses light water as the coolant, but the capital cost can be reduced by 20-30% lower than those of the current light water reactors (LWRs) , . In Japan, the new type of light water reactor has been studied at The UT (University of Tokyo) and Waseda University since 1989 , . It consists of thermal and fast reactors developments. The version of the fast reactor is expected to be more economical due to its higher density of power with the possibility of fuel breeding.
Decommissioning of fuel channels represents one of the last operations which are performed in the process of decommissioning the nuclear power plant and it is considered the most important in dismantling the nuclear reactor structure. Due to safety reasons, special devices with command and control from the outside (in remote control mode) should be used. The designed device shall provide a full protection of
By Pontryagin’s maximum principle, the necessary optimality system for time optimal control problems contains a multivalued operation which impedes the use of fast numerical methods. Traditional approaches for solving time optimal problems are mainly grouped into direct and indirect methods. Indirect methods are based on multiple shooting techniques  to solve the two point boundary value problem. Equipped with a good initial guess for all unknowns, particularly the number and location of the switchings, the shooting method is reported to converge fast and to generate very accurate solutions, for example, see . Direct methods, on the other hand, consider time optimal problems as genuine nonlinear programming problems. They are used in several variants, which frequently involve reparametrization of the controls as the unknowns, see  . Much of the literature for time optimal control problem up to the late sixties is covered in . Many recent results can be found in   . Time optimal control for infinite dimensional systems is considered in , for instance.
Lalit G. Patil was born on June 20, 1990. Hereceived the B.E degree inElectronics and Communication Engineering from Gujarat University and M.E Degree in Electrical Engineering from The M.S.University of Baroda, India. He is currently Working as a Teaching Assistant at The M.S.University of Baroda, India. His Current interest is Control applications, Pattern Recognitions and Robotic applications.
The IVAC Titrator was developed to regulate mean arterial pressure in hypertensive intensive care unit (ICU) patients by infusing sodium nitroprusside. The device received FDA approval in 1987 and was marketed for a short time, but was discontinued after a few years. The reasons for its failure in the marketplace include the following: (1) no consistent communication standards existed at the time, so the device had its own blood pressure sensor that was not particularly easy to set up; (2) the computer interface technology was not advanced; (3) the units were overpriced (IVAC chose to recoup R&D costs within a short time period); and (4) although studies showed less variability in blood pressure than with manual control, the effect of the reduced variability on patient outcomes was unclear . Some studies suggested that patients were able to reduce hospital stays by a day. With new communication standards and advances in microprocessor-based pump technology, a closed-loop blood pressure system could probably succeed in the marketplace today.
In the manufacturing processes of high value-added products in the pharmaceutical, fine chemical polymer and food industry, insufficient control might produce off-grade products. This can cause significant financial losses, or in the pharmaceutical industry, it can result in an unusable batch. In these industries, batch reactors are commonly used, the control of which is essentially a problem of temperature control. In the industry, an increasing number of heat- ing-cooling systems utilising three different temperature levels can be found, which are advantageous from an economic point of view. However, it makes the control more complicated. This paper presents a split-range designing technique using the model of the controlled system with the aim to design a split-range algorithm more specific to the actual sys- tem. The algorithm described provides high control performance when using it with classical PID-based cascade tem- perature control of jacketed batch reactors; however, it can be used with or as part of other types of controllers, for ex- ample, model-based temperature controllers. The algorithm can be used in the case of systems where only two as well as where three temperature levels are used for temperature control. Besides the switching between the modes of opera- tion and calculating the value of the manipulated variable, one of the most important functions of the split-range algo- rithm is to keep the sign of the gain of the controlled system unchanged. However, with a more system-specific split-range solution, not only can the sign of the gain be kept unchanged, but the gain can also be constant or less de- pendent on the state of the system. Using this solution, the design of the PID controller becomes simpler and can be implemented in existing systems without serious changes.