A smart approach to precision attitude maneuvers of spacecrafts

A nonlinear adaptive approach is presented to achieve rest-to-rest attitude maneuvers for spacecrafts in the presence of parameter uncertainties and unknown disturbances. A nonlinear controller, designed on the principle of dynamic inversion achieves the goals for the nominal model but suffers performance degradation in the presence of off-nominal parameter values and unwanted inputs. To address this issue, a model-following neuro-adaptive control design is carried out by taking the help of neural networks. Due to the structured approach followed here, the adaptation is restricted to the momentum level equations.The adaptive technique presented is computationally nonintensive and hence can be implemented in real-time. Because of these features, this new approach is named as structured model-following adaptive real-time technique (SMART). From simulation studies, this SMART approach is found to be very effective in achieving precision attitude maneuvers in the presence of parameter uncertainties and unknown disturbances.

Active Vibration Suppression of One-dimensional Nonlinear Structures Using Optimal Dynamic Inversion

A flexible robot arm can be modeled as an Euler-Bernoulli beam which are infinite degrees of freedom (DOF) system. Proper control is needed to track the desired motion of a robotic arm. The infinite number of DOF of beams are reduced to finite number for controller implementation, which brings in error (due to their distributed nature). Therefore, to represent reality better distributed parameter systems (DPS) should be controlled using the systems partial differential equation (PDE) directly. In this paper, we propose to use a recently developed optimal dynamic inversion technique to design a controller to suppress nonlinear vibration of a beam. The method used in this paper determines control forces directly from the PDE model of the system. The formulation has better practical significance, because it leads to a closed form solution of the controller (hence avoids computational issues).

Improved utilisation of an HF transformer in DC–AC application

Power conversion using high frequency (HF) link converters is popular because of compact size and light weight of highfrequency transformer. This study focuses on improved utilisation of HF transformer in DC–AC applications. In practical application, the operating condition of the power converter deviates significantly from the designed considerations. These deviating factors are commutation requirements (dead-time, overlap), mismatch in device drops and presence of the fundamental frequency in load current. As a result, the HF transformer handles some amount of low-frequency components (including DC) other than desired HF components. This causes the operating point in B-H curve to shift away from its normal or idealised position and hence results poor utilisation of the HF transformer and unwanted losses. This study investigates the nature of the problem with experimental determination of approximate lumped parameter modelling and saturation behaviour (B-H curve) of the HF transformer. A simple closed-loop control algorithm with online tuning of the controller parameters is proposed to improve the utilisation of the isolation transformer. The simulation and experimental results are presented.

Discrete control algorithms for a tubular ammonia reactor

The specific objective of this paper is to develop direct digital control strategies for an ammonia reactor using quadratic regulator theory and compare the performance of the resultant control system with that under conventional PID regulators. The controller design studies are based on a ninth order state-space model obtained from the exact nonlinear distributed model using linearization and lumping approximations. The evaluation of these controllers with reference to their disturbance rejection capabilities and transient response characteristics, is carried out using hybrid computer simulation.

Control technique for non-linear and unbalance compensation of an integrated magnetics-based three-phase series-shunt-compensated uninterruptible power supply

Handling unbalanced and non-linear loads in a three-phase AC power supply has always been a difficult issue. This has been addressed in the literature by either using fast controllers in the fundamental rotating reference frame or using separate controllers in reference frames specific to the harmonics. In the former case, the controller needs to be fast and in the latter case, besides the need for many controllers, negative-sequence components need to be extracted from the measured signal. This study proposes a control scheme for harmonic and unbalance compensation of a three-phase uninterruptible power supply wherein the problems mentioned above are addressed. The control takes place in the fundamental positive-sequence reference frame using only a set of feedback and feed-forward compensators. The harmonic components are extracted by a process of frame transformations and used as feed-forward compensation terms in the positive-sequence fundamental reference frame. This study uses a method wherein the measured signal itself is used for fundamental negative-sequence compensation. As the feed-forward compensator handles the high-bandwidth components, the feedback compensator can be a simple low-bandwidth one. This control algorithm is explained and validated experimentally.

Control technique for non-linear and unbalance compensation of an integrated magnetics-based three-phase series-shunt-compensated uninterruptible power supply

Handling unbalanced and non-linear loads in a three-phase AC power supply has always been a difficult issue. This has been addressed in the literature by either using fast controllers in the fundamental rotating reference frame or using separate controllers in reference frames specific to the harmonics. In the former case, the controller needs to be fast and in the latter case, besides the need for many controllers, negative-sequence components need to be extracted from the measured signal. This study proposes a control scheme for harmonic and unbalance compensation of a three-phase uninterruptible power supply wherein the problems mentioned above are addressed. The control takes place in the fundamental positive-sequence reference frame using only a set of feedback and feed-forward compensators. The harmonic components are extracted by a process of frame transformations and used as feed-forward compensation terms in the positive-sequence fundamental reference frame. This study uses a method wherein the measured signal itself is used for fundamental negative-sequence compensation. As the feed-forward compensator handles the high-bandwidth components, the feedback compensator can be a simple low-bandwidth one. This control algorithm is explained and validated experimentally.

Control technique for non-linear and unbalance compensation of an integrated magnetics-based three-phase series-shunt-compensated uninterruptible power supply

Handling unbalanced and non-linear loads in a three-phase AC power supply has always been a difficult issue. This has been addressed in the literature by either using fast controllers in the fundamental rotating reference frame or using separate controllers in reference frames specific to the harmonics. In the former case, the controller needs to be fast and in the lattercase, besides the need for many controllers, negative-sequence components need to be extracted from the measured signal.This study proposes a control scheme for harmonic and unbalance compensation of a three-phase uninterruptible power supply wherein the problems mentioned above are addressed. The control takes place in the fundamental positive-sequence reference frame using only a set of feedback and feed-forward compensators. The harmonic components are extracted by process of frame transformations and used as feed-forward compensation terms in the positive-sequence fundamental reference frame. This study uses a method wherein the measured signal itself is used for fundamental negative-sequence compensation. As the feed-forward compensator handles the high-bandwidth components, the feedback compensator can be a simple low-bandwidth one. This control algorithm is explained and validated experimentally.

Space vector based bus clamped PWM algorithms for three level inverters: implementation, performance analysis and application considerations

This paper describes the different types of space vector based bus clamped PWM algorithms for three level inverters. A novel bus clamp PWM algorithm for low modulation indices region is also presented. The principles and switching sequences of all the types of bus clamped algorithms for high switching frequency are presented. Synchronized version of the PWM sequences for high power applications where switching frequency is low is also presented. The implementation details on DSP based digital controller and experimental results are presented. The THD of the output waveforms is studied for the entire operating region and is compared with the conventional space vector PWM technique. The bus clamped techniques can be used to reduce the switching losses or to improve the output voltage quality or both.. Different issues dominate depending on the type of application and power rating of the inverters. The results presented in this paper can be used for judicious use of the PWM techniques, which result in improved system efficiency and performance.

A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

Reinforcement learning controllers for automatic generation control in power systems having re-heat units with GRC and dead-band

A new automatic generation controller (AGC) design approach, adopting reinforcement learning (RL) techniques, was recently pro- posed [1]. In this paper we demonstrate the design and performance of controllers based on this RL approach for automatic generation control of systems consisting of units having complex dynamics—the reheat type of thermal units. For such systems, we also assess the capabilities of RL approach in handling realistic system features such as network changes, parameter variations, generation rate constraint (GRC), and governor deadband.

A neural network based power system stabilizer suitable for on-line training-a practical case study for EGAT system

This paper presents the development of a neural network based power system stabilizer (PSS) designed to enhance the damping characteristics of a practical power system network representing a part of Electricity Generating Authority of Thailand (EGAT) system. The proposed PSS consists of a neuro-identifier and a neuro-controller which have been developed based on functional link network (FLN) model. A recursive on-line training algorithm has been utilized to train the two neural networks. Simulation results have been obtained under various operating conditions and severe disturbance cases which show that the proposed neuro-PSS can provide a better damping to the local as well as interarea modes of oscillations as compared to a conventional PSS

Application of UPFC for system security improvement under normal and network contingencies

Electric power systems are exposed to various contingencies. Network contingencies often contribute to over-loading of network branches, unsatisfactory voltages and also leading to problems of stability/voltage collapse. To maintain security of the systems, it is desirable to estimate the effect of contingencies and plan suitable measures to improve system security/stability. This paper presents an approach for selection of unified power flow controller (UPFC) suitable locations considering normal and network contingencies after evaluating the degree of severity of the contingencies. The ranking is evaluated using composite criteria based fuzzy logic for eliminating masking effect. The fuzzy approach, in addition to real power loadings and bus voltage violations, voltage stability indices at the load buses also used as the post-contingent quantities to evaluate the network contingency ranking. The selection of UPFC suitable locations uses the criteria on the basis of improved system security/stability. The proposed approach for selection of UPFC suitable locations has been tested under simulated conditions on a few power systems and the results for a 24-node real-life equivalent EHV power network and 39-node New England (modified) test system are presented for illustration purposes.

Synthesis and Characterization of a Fluorescent Analogue of Cyclic di-GMP

Cyclic di-GMP (c-di-GMP), a ubiquitous bacterial second messenger, has emerged as a key controller of several biological processes. Numbers of reports that deal with the mechanistic aspects of this second messenger have appeared in the literature. However, the lack of a reporter tag attached to the c-di-GMP at times limits the understanding of further details. In this study, we have chemically coupled N-methylisatoic anhydride (MANT) with c-di-GMP, giving rise to Mant-(c-di-GMP) or MANT-CDG. We have characterized the chemical and physical properties and spectral behavior of MANT-CDG. The fluorescence of MANT-CDG is sensitive to changes in the microenvironment, which helped us study its interaction with three different c-di-GMP binding proteins (a diguanylate cyclase, a phosphodiesterase, and a PilZ domain-containing protein). In addition, we have shown here that MANT-CDG can inhibit diguanylate cyclase activity; however, it is hydrolyzed by c-di-GMP specific phosphodiesterase. Taken together, our data suggest that MANT-CDG behaves like native c-di-GMP, and this study raises the possibility that MANT-CDG will be a valuable research tool for the in vitro characterization of c-di-GMP signaling factors.

Sliding-Mode Guidance and Control for All-Aspect Interceptors with Terminal Angle Constraints

In this paper, sliding-mode-control-based guidance laws to intercept stationary, constant-velocity, and maneuvering targets at a desired impact angle are proposed. The desired impact angle, which is defined in terms of a desired line-of-sight angle, is achieved in finite time by selecting the missile's lateral acceleration to enforce terminal sliding mode on a switching surface designed using nonlinear engagement dynamics. The conditions for capturability are also presented. In addition, by considering a three-degree-of-freedom linear-interceptor dynamic model and by following the procedure used to design a dynamic sliding-mode controller, the interceptor autopilot is designed as a simple static controller to track the lateral acceleration generated by the guidance law. Numerical simulation results are presented to validate the proposed guidance laws and the autopilot design for different initial engagement geometries and impact angles.

Control of a Duct Flow Network for Wind Display in a Virtual Environment

Control of flow in duct networks has a myriad of applications ranging from heating, ventilation, and air-conditioning to blood flow networks. The system considered here provides vent velocity inputs to a novel 3-D wind display device called the TreadPort Active Wind Tunnel. An error-based robust decentralized sliding-mode control method with nominal feedforward terms is developed for individual ducts while considering cross coupling between ducts and model uncertainty as external disturbances in the output. This approach is important due to limited measurements, geometric complexities, and turbulent flow conditions. Methods for resolving challenges such as turbulence, electrical noise, valve actuator design, and sensor placement are presented. The efficacy of the controller and the importance of feedforward terms are demonstrated with simulations based upon an experimentally validated lumped parameter model and experiments on the physical system. Results show significant improvement over traditional control methods and validate prior assertions regarding the importance of decentralized control in practice.