Compensator for constant relative stability in process control systems

Process control systems are designed for a closed-loop peak magnitude of 2dB, which corresponds to a damping coefficient () of 0.5 approximately. With this specified constraint, the designer should choose and/or design the loop components to maintain a constant relative stability. However, the manipulative variable in almost all chemical processes will be the flow rate of a process stream. Since the gains and the time constants of the process will be functions of the manipulative variable, a constant relative stability cannot be maintained. Up to now, this problem has been overcome either by selecting proper control valve flow characteristics or by gain scheduling of controller parameters. Nevertheless, if a wrong control valve selection is made then one has to account for huge loss in controllability or eventually it may lead to an unstable control system. To overcome these problems, a compensator device that can bring back the relative stability of the control system was proposed. This compensator is similar to a dynamic nonlinear controller that has both online and offline information on several factors related to the control system. The design and analysis of the proposed compensator is discussed in this article. Finally, the performance of the compensator is validated by applying it to a two-tank blending process. It has been observed that by using a compensator in the process control system, the relative stability could be brought back to a great extent despite the effects of changes in manipulative flow rate.

Deformation processing map for control of microstructure in Al---4Mg alloy

The compression test flow stress data of Al-4Mg alloy at different temperatures and strain rates are analysed using a dynamic materials model which considers the workpiece material as a dissipator of power causing microstructural changes. A processing map representing the efficiency of power dissipation as a function of temperature and strain rate has been established and optimum processing conditions for the alloy are determined. The features of the map correlate well with the microstructure and mechanical properties.

Concepts of Static Var System Control For Enhancing Power Transfer in Long Transmission Lines

This paper is concerned with the influence of different levels of complexity in modelling various constituent subsystems on the dynamic stability of power systems compensated by static var systems (SVS) operating on pure voltage control. The system components investigated include thyristor controlled reactor (TCR) transients, SVS delays, network transients, the synchronous generator and automatic voltage regulator (AVR). An overall model is proposed which adequately describes the system performance for small signal perturbations. The SVS performance is validated through detailed nonlinear simulation on a physical simulator.

Microstructural control in hot working of IN-718 superalloy using processing map

The hot-working characteristics of IN-718 are studied in the temperature range 900 °C to 1200 °C and strain rate range 0.001 to 100 s−1 using hot compression tests. Processing maps for hot working are developed on the basis of the strain-rate sensitivity variations with temperature and strain rate and interpreted using a dynamic materials model. The map exhibits two domains of dynamic recrystallization (DRX): one occurring at 950 °C and 0.001 s−1 with an efficiency of power dissipation of 37 pct and the other at 1200 °C and 0.1 s−1 with an efficiency of 40 pct. Dynamic recrystallization in the former domain is nucleated by the δ(Ni3Nb) precipitates and results in fine-grained microstructure. In the high-temperature DRX domain, carbides dissolve in the matrix and make interstitial carbon atoms available for increasing the rate of dislocation generation for DRX nucleation. It is recommended that IN-718 may be hot-forged initially at 1200 °C and 0.1 s−1 and finish-forged at 950 °C and 0.001 s−1 so that fine-grained structure may be achieved. The available forging practice validates these results from processing maps. At temperatures lower than 1000 °C and strain rates higher than 1 s−1 the material exhibits adiabatic shear bands. Also, at temperatures higher than 1150°C and strain rates more than 1s−1, IN-718 exhibits intercrystalline cracking. Both these regimes may be avoided in hotworking IN-718.

Microstructural control in hot working of IN-718 superalloy using processing map

The hot-working characteristics of IN-718 are studied in the temperature range 900 degrees C to 1200 degrees C and strain rate range 0.001 to 100 s(-1) using hot compression tests. Processing maps for hot working are developed on the basis of the strain-rate sensitivity variations with temperature and strain rate and interpreted using a dynamic materials model. The map exhibits two domains of dynamic recrystallization (DRX): one occurring at 950 degrees C and 0.001 s(-1) with an efficiency of power dissipation of 37 pct and the other at 1200 degrees C and 0.1 s(-1) with an efficiency of 40 pct. Dynamic recrystallization in the former domain is nucleated by the delta(Ni3Nb) precipitates and results in fine-grained microstructure. In the high-temperature DRX domain, carbides dissolve in the matrix and make interstitial carbon atoms available for increasing the rate of dislocation generation for DRX nucleation. It is recommended that IN-718 may be hot-forged initially at 1200 degrees C and 0.1 s(-1) and finish-forged at 950 degrees C and 0.001 s(-1) so that fine-grained structure may be achieved. The available forging practice validates these results from processing maps. At temperatures lower than 1000 degrees C and strain rates higher than 1 s(-1), the material exhibits adiabatic shear bands. Also, at temperatures higher than 1150 degrees C and strain rates more than 1 s(-1), IN-718 exhibits intercrystalline cracking. Both these regimes may be avoided in hot-working IN-718.

Robust/Optimal Temperature Profile Control of a High-Speed Aerospace Vehicle Using Neural Networks

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the �Single Network Adaptive Critic (SNAC)� is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Effective drug dosage design for treatment of infectious diseases using dynamic inversion

A generic nonlinear mathematical model describing the human immunological dynamics is used to design an effective automatic drug administration scheme. Even though the model describes the effects of various drugs on the dynamic system, this work is confined to the drugs that kill the invading pathogen and heal the affected organ. From a system theoretic point of view, the drug inputs can be interpreted as control inputs, which can be designed based on control theoretic concepts. The controller is designed based on the principle of dynamic inversion and is found to be effective in curing the �nominal model patient� by killing the invading microbes and healing the damaged organ. A major advantage of this technique is that it leads to a closed-form state feedback form of control. It is also proved from a rigorous mathematical analysis that the internal dynamics of the system remains stable when the proposed controller is applied. A robustness study is also carried out for testing the effectiveness of the drug administration scheme for parameter uncertainties. It is observed from simulation studies that the technique has adequate robustness for many �realistic model patients� having off-nominal parameter values as well.

Active vibration suppression of beams with discrete actuators using optimal dynamic inversion

Most of the structural elements like beams, cables etc. are flexible and should be modeled as distributed parameter systems (DPS) to represent the reality better. For large structures, the usual approach of 'modal representation' is not an accurate representation. Moreover, for excessive vibrations (possibly due to strong wind, earthquake etc.), external power source (controller) is needed to suppress it, as the natural damping of these structures is usually small. In this paper, we propose to use a recently developed optimal dynamic inversion technique to design a set of discrete controllers for this purpose. We assume that the control force to the structure is applied through finite number of actuators, which are located at predefined locations in the spatial domain. The method used in this paper determines control forces directly from the partial differential equation (PDE) model of the system. The formulation has better practical significance, both because it leads to a closed form solution of the controller (hence avoids computational issues) as well as because a set of discrete actuators along the spatial domain can be implemented with relative ease (as compared to a continuous actuator)

An optimal dynamic inversion approach for controlling a class of one-dimensional nonlinear distributed parameter systems

Combining the principles of dynamic inversion and optimization theory, a new approach is presented for stable control of a class of one-dimensional nonlinear distributed parameter systems, assuming the availability a continuous actuator in the spatial domain. Unlike the existing approximate-then-design and design-then-approximate techniques, here there is no need of any approximation either of the system dynamics or of the resulting controller. Rather, the control synthesis approach is fairly straight-forward and simple. The controller formulation has more elegance because we can prove the convergence of the controller to its steady state value. To demonstrate the potential of the proposed technique, a real-life temperature control problem for a heat transfer application is solved. It has been demonstrated that a desired temperature profile can be achieved starting from any arbitrary initial temperature profile.

Dynamic analysis of voltage instability in AC-DC systems

This paper presents the analysis and study of voltage collapse at any converter bus in A C-DC systems considering the dynamics of DC system. The problem of voltage instability is acute when HVDC links are connected to weak AC systems, the strength determined by short circuit ratio (SCR) at the converter bus. The converter control strategies are important in determining voltage instability. Small signal analysis is used to identify critical modes and evaluate the effect of AC system strength and control parameters. A sample two-terminal DC system is studied and the results compared with those obtained from static analysis. Also, the results obtained from small signal analysis are validated with nonlinear simulation.

The stretching of single poly-ubiquitin molecules: Static versus dynamic disorder in the non-exponential kinetics of chain unfolding

Static disorder has recently been implicated in the non-exponential kinetics of the unfolding of single molecules of poly-ubiquitin under a constant force Kuo, Garcia-Manyes, Li, Barel, Lu, Berne, Urbakh, Klafter, and Fernandez, Proc. Natl. Acad. Sci. U. S. A. 107, 11336 (2010)]. In the present paper, it is suggested that dynamic disorder may provide a plausible, alternative description of the experimental observations. This suggestion is made on the basis of a model in which the barrier to chain unfolding is assumed to be modulated by a control parameter r that evolves in a parabolic potential under the action of fractional Gaussian noise according to a generalized Langevin equation. The treatment of dynamic disorder within this model is pursued using Zwanzig's indirect approach to noise averaging Acc. Chem. Res. 23, 148 (1990)]. In conjunction with a self-consistent closure scheme developed by Wilemski and Fixman J. Chem. Phys. 58, 4009 (1973); ibid. 60, 866 (1974)], this approach eventually leads to an expression for the chain unfolding probability that can be made to fit the corresponding experimental data very closely. (C) 2011 American Institute of Physics.

A QFT-based robust SVC controller for improving the dynamic stability of power systems

A new design technique for an SVC-based power system damping controller has been proposed. The controller attempts to place all plant poles within a specified region on the s-plane to guarantee the desired closed loop performance. The use of Horowitz's quantitative feedback theory (QFT) permits the design of a 'fixed gain controller' that maintains its performance in spite of large variations in the plant parameters during its normal course of operation. The required controller parameters are arrived at by solving an optimization problem that incorporates the control specifications. The performance of this robust controller has been evaluated on a single machine infinite bus system equipped with a mid point SVC, and the results are shown to be consistent with the expected performance of the stabilizer. (C) 1998 Elsevier Science S.A. All rights reserved.

Optimal control of a stochastic hybrid system with discounted cost

We address the optimal control problem of a very general stochastic hybrid system with both autonomous and impulsive jumps. The planning horizon is infinite and we use the discounted-cost criterion for performance evaluation. Under certain assumptions, we show the existence of an optimal control. We then derive the quasivariational inequalities satisfied by the value function and establish well-posedness. Finally, we prove the usual verification theorem of dynamic programming.

In-situ power monitoring scheme and its application in dynamic voltage and threshold scaling for digital CMOS integrated circuits

An in-situ power monitoring technique for Dynamic Voltage and Threshold scaling (DVTS) systems is proposed which measures total power consumed by load circuit using sleep transistor acting as power sensor. Design details of power monitor are examined using simulation framework in UMC 90nm CMOS process. Experimental results of test chip fabricated in AMS 0.35µm CMOS process are presented. The test chip has variable activity between 0.05 and 0.5 and has PMOS VTH control through nWell contact. Maximum resolution obtained from power monitor is 0.25mV. Overhead of power monitor in terms of its power consumption is 0.244 mW (2.2% of total power of load circuit). Lastly, power monitor is used to demonstrate closed loop DVTS system. DVTS algorithm shows 46.3% power savings using in-situ power monitor.