Low Earth Orbit Satellite Attitude Stabilization Using Linear Quadratic Regulator

Delays are a common physic effect that is present in a huge quantity of industrial systems with feedback control. Sometimes the impact of the delay presence in a system is neglected without any difference in the performance of the controller. But in some cases, the Delay quantity reaches levels that increase the overshoot significantly or destabilizes the system. For this system the CTCR method can be used to design a “delayed scheduled” controller able to reject the delays effect. To be able to apply this method it is necessary for both the system and the controller to be Linear or linearized. In this article the study case is an articulated inverted pendulum or also called “Pendubot”. This configuration of pendulum was selected because, in spite of being a simple pendulum, it has four equilibrium points, where two equilibrium points were selected to be controlled, the most unstable which has the maximum potential energy for each link and the most stable with the lowest potential energy. The purpose of work with those equilibrium points is compare the difference between the delay rejection in each point with similar setting times and overshoots from controllers. In order to get an accurate model, the state of the current is added along with the viscous friction terms for each joint in the pendulum. To tune the linear and non-linear model an experimental validation was carry on the physical prototype from the Universidad Industrial de Santander (VIE-5373 UIS). The control laws applied were a classical PID and LQR control. Due the controller sample frequency is extremely high in comparison to the states response, all the controllers and linear models were implemented in continuous space. In the first tuning process it was observed that the PID control gets a significantly lowest performance than the LQR control in the unstable equilibrium point, for that reason the comparison between points only was carried on with the LQR equation of feedback system, this can be done in different ways, but for the PID control the Mason theorems was applied and for LQR control only with matrix operation the equation can be obtained. After applying the “Delay scheduling” it was observed that the tuned LQR get a highest delay rejection that PID. An observer fact was that although the controllers for each point have a similar performance the delay pockets have completely different values due the final poles locations for each point. Also was observed that the system only gets one stability pocket, this could because only one delay in the actuator was induced.

Efficient power consumption, intelligent power monitoring and interactive control of power consumption in smart homes are the key factors of sustainable development, reduction of power demand peaks and activities related to avoidance of blackout effects.The highlight of the proposed system is its ability to control maximum consuming power of the home appliances (HAs) and keep the total power consumption below a certain limit and allowing the home user more flexibility to operate their HAs based on HA priority.The proposed smart power management system consists of smart electric sensors (SESs) and power provisioning controller (PPC).The PPC and SES are concurrently used to control and maintain stability and complete power waveform behavior examination.However, we need to reassign an amount of consuming power from one HA to another when the ON/OFF status of HA changes.This paper offers a system to control the maximum power consumption considering heterogeneous HAs with different response speed.In order to guarantee the maximum consuming power limit, we compute the limited suggested power level for HAs.Simulation results show the effectiveness of our system in managing maximum power consumption.

In this paper, a formulation of a sandwich plate integrating an elastic central layer (isotropic or composite) between two piezoelectric sub-layers (actuators and/or sensors), which can be taken as a smart (intelligent) structure and allowing active control vibrations is presented. A 9-node finite element quadratic plate element with 5 degrees of freedom per node is used which takes into account the effect of transverse shear with an additional degree of freedom for each node of the piezoelectric sub-layer. At First, the static control of the deflection by taking the two piezoelectric sub-layers as actuators with two configurations of the total and partial recovery of the surface is undertaken. Thus, the influence of patches position, for the second configuration, on the attenuation of vibrations is analyzed. In a Second step, the active vibration control using two types of LQR and PID controllers with different control parameters is tested and compared for the two recovery configurations (total and partial) of the piezoelectric elements. It is demonstrated throughout the present results that the performances of the partial recovery are almost as good as those of the total recovery despite a ratio of the surfaces piezoelectric patches which is 1/3. It is also noticed that the PID controller is more efficient than the LQR controller. But, if using the PSO (Particle Swarm Optimization) algorithm, the LQR's parameters are optimized and give almost the same performances as those of the PID controller.DOI: http://dx.doi.org/10.5755/j01.mech.24.5.20645

This paper presents the comparative study of Model Predictive Controller (MPC) with PID Controller implemented for flow control loop in LABVIEW. Classical PID controller is mostly used in process instrumentation yet tuning of PID controller is the crucial part to be dealt with. Moreover, changes in the parameters of the loop components affects the tuning of the controller, hence over a period of time retuning of PID controller is required. On the other hand MPC controller works on the process model which predicts and optimizes the process performance. Here, Flow control loop performance was studied for MPC and PID controller. MPC worked on 1st order state space system model and PID was tuned using Internal Model Control (IMC) method. The result of implementation shows that, MPC controller performs much better than PID controller. Set point of with less settling time and zero peak overshoot was observed in MPC whereas PID has comparatively more settling time and peak overshoot.

Due to an increase in home appliances (HAs) the overall power consumption in home tends to grow and leads an increasing risk of losing stability. In this paper, we propose a system model for smart homes to control maximum power consumption by HAs based on HA priority. The proposed system consists of smart electric sensors (SESs), power provisioning controller (PPC) and HAs. The role of PPC is to gather ON/OFF status from each HA and instantaneous consuming power level from SES, and to send control signal back to each HA. After gathering information, along with HA priority, computes a final target power level for each HA is not a hard task. However, when ON/OFF status of HAs change, we may need to reassign an amount of consuming power from one HA to another, and the transient behavior due to such reassignment of power is not simple. This paper proposes a system to control the maximum total power consumption in detailed transient behavior considering heterogeneous HAs with different time constants. In order to guarantee the maximum power limit, we will compute the remaining power, and reassign it to HAs as their temporal target power levels. Simulation results show the effectiveness of our system in managing maximum power consumption.

This paper is devoted to the analysis of electricity consumption by a real enterprise in Western Siberia and the development of recommendations for optimizing its electricity consumption in the context of the tariff policy for the region. The paper discusses the possibility of using energy storage device to reduce the maximum power consumption by organizing charge and discharge cycles of the drive in certain periods of the day. During minimum power consumption, the daily load curve is levelled due to the process of charging the drives. The energy is released into the circuit at the maximum power consumption of the enterprise, reducing its peak load. Aligning the daily schedule of the projected power consumption allows selecting a price category with a lower tariff rate when applying for technological connection. It is concluded that the use of energy storage device for saving for these purposes is unprofitable, since the payback period of the drive significantly exceeds its service life. It is noted that a possible area of application of energy storage device includes enterprises where process violations lead to significant economic damage, the minimization of which justifies the use of expensive energy storage devices.

Heat exchangers are expedients used to transfer of heat energy from one medium to other while preventing the two from mixing. Heat exchangers are hired in a selection of domestic, commercial, and industrial applications, such as air conditioning, power production, refrigeration, process industry, and manufacturing industry. A larger variation in the temperature affects property of non-Newtonian fluids, thus affects the uniform heat transfer process. This paper is primarily to deal the response analysis of different controllers that is regulating the outlet temperature of fluid inside the PHE is proposed. The cold fluid flow is highly influenced on the hot water temperature, the research work mainly focuses on controlling cold fluid flow. In order to attain the precise model of the system, a mathematical model by first principle methods and process history based methods were used. A PI, PID and Model Predictive Controller (MPC) are known for its better control action of the system. The controller’s performance analysed such as PI, PID and MPC controller to adjust the temperature of hot fluid outlet to a required setpoint. Performance criteria analysis value for various controllers are PI, PID and MPC. It is understood that MPC controller results lower value of performance measures compared to other controllers, this implies that it could track the setpoint by rejecting the external disturbances with less settling time and moderate oscillation. The transient performance and the error criteria of the controllers are investigated and the best controller to regulate the temperature is found out. It is found out that the MPC controller outperforms PI and PID controller from the results of simulation.

Starting from deep submicron technologies (< 0.13μm), and even stronger in nanometer technologies, static power consumption, due to leaky “off” transistors, is becoming a non-negligible contributor to the total power dissipation. Under this condition, the total power optimization problem changes considerably. The high parallelization approach commonly used today to increase performances, will soon result in power ineffcient designs. Indeed, the static power consumption of the large number of rarely used transistors will highly penalize the total power consumption. The purpose of this thesis is to investigate the influence of static power on the design methodologies for low power. In particular, the effects of architectural as well as technology modifications are explored. The use of technology as an optimization parameter has become possible in recent technologies. In fact, they offer different threshold voltages, each one showing a different trade-off between speed and leakage current. In this work, two different frameworks are considered. In the first one, both the supply voltage and the transistor threshold voltage are freely tunable parameters. This is the most general case and corresponds to the situation where the designer has the largest freedom. In the latter framework, we assume that the designer cannot change the supply voltage nor the transistor threshold voltage and they are hence considered constants. This case corresponds to the most common one, where the designer has a supply voltage and a technology type (and hence a threshold voltage) fixed by the application and by the devices the circuit has to interface. In both cases, lot of efforts have been put to the development of a handy way to rapidly estimate the total power consumption and consequently easily compare different architectural/technology variants at the early stages of development. Examples, based on multipliers, are used extensively in the whole thesis and, at the end, the presented theory is applied to a real circuit implemented in a 90nm technology by ST Microelectronics. Measurements show a very large variability of the static power over 16 dies manufactured on the same wafer. For instance, the highest static power consumption at nominal condition (Vdd=1V, f=62.5MHz) over the lowest one corresponds to more than a factor of 2.5. Measured data also report multipliers able to work at 210mV for a frequency of 1MHz!

In this paper, a self-tuning hierarchical controller in which a Fuzzy logic controller supervises the control actions of a conventional PID has been proposed, implemented and presented. The controller has been applied to a control study of Fluid Catalytic Cracking (FCC) unit riser temperature, and regenerator temperature respectively. Performance comparison of the proposed Fuzzy-PID controller and the conventional PID was made in simulation studies of regulatory and servo performances of the two controller types. Six performance measures: Percent overshoot (OS), settling time (ST), integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE) and integral time square error (ITSE) were employed as the tools for performance comparison between the conventional PID and the Fuzzy-PID controller. For the tracking of riser temperature with a set point at 524oC, the performance indicators under PID control gave the following results overshoot (14.5%); settling time (40 seconds) Integral absolute error (8.246), integral square error (3.3); integral time absolute error(1762);integral time square error (43.77) while for the same indicators under Fuzzy-PID control the following values: overshoot (3.3%); settling time (40 seconds) ;Integral absolute error (8.811); integral square error (14.5); integral time absolute error(280),;integral time square error (31.11) .The results allude to the superiority of the fuzzy-PID scheme over the PID scheme in tracking the optimal set point of riser temperature. More so, for tracking the regenerator set point temperature of 746oC, comparative study of step response under the two schemes gave the following results in six performance indicators: overshoot (PID(12.6%)/Fuzzy-PID(6%)); settling time (PID(80 seconds)/Fuzzy-PID(20seconds));Integral absolute error(PID(14.29)/Fuzzy-PID(8.63)); integral square error(PID(6.713).Fuzzy-PID(4.506)); integral time absolute error(PID(2858)/Fuzzy-PID(305.9)), integral time square error (PID(77.55)/Fuzzy-PID(33.05)).Moreover, the fuzzy-PID controller also showed superior performance over the conventional PID controller in terms disturbance rejection (regulatory response) of both riser and regenerator temperature. The results from this study suggest that the application of fuzzy-PID scheme to temperature control offers good promise of improved fluid catalytic cracking unit (FCCU) operations.

In this paper, we discuss physical-layer network coding (PLNC) in the two-way decode-forward (DF) relay to obtain total minimum power consumption (MPC) for the entire transmission process. The MPC and power allocation scheme for each node are obtained under a predetermined constraint of outage probability threshold in a Rayleigh fading channel environment. Numerical experimental results confirm that the proposed MPC scheme achieves much lower power consumption ratio than the existing schemes without PLNC on the condition of the same system outage guarantee.

Creation of hot-spots is unavoidable, in multihop wireless sensor networks using the least power (or shortest path) routing method. This happens due to the irregularity of underlying network structures. Since hot-spots lose their energy faster than other nodes, they might create network partitions. In this paper, first, we study constructing of energy balanced topologies in a multihop sensor network using only structural information of a network with any-to-any traffic pattern. We consider both forwarding load and transmission power in energy consumption of sensors. Then, we present a strategic network formation game model. We use pairwise stability concept instead of traditional Nash stability and discuss about its advantages over Nash model in our game. After analyzing the game properties, two global and local algorithms for constructing balanced networks are introduced. Our evaluations on sparse and dense uniform networks show that our local algorithm when nodes use their limited neighborhood information, effectively reduces energy consumption imbalance and maximum power consumption while keeping the total power consumption in an acceptable level.

Homomorphic encryption for smart grids has been investigated in many studies. It is possible to estimate the total power consumption in an area without knowing the consumption data of individual households. In the case of demand response (DR), it is important to calculate the total electric power consumption in an area because DR reports are published accordingly to reduce peak power consumption when the demand is high. However, the published data may reveal private information about residents, such as the timings of specific activities (leaving from and returning home), and device details. To overcome this problem, we propose a method specialized to enable energy providers to securely share electric power consumption data. The proposed method uses a self-organizing map (SOM), which is an unsupervised learning method. In order to share power consumption data while preserving privacy, the SOM is shared without the raw data. In this framework, a target accuracy of nearly 3% is achieved, while actual data are not published by any company.

A design procedure that determines the combination of linear settling time (i.e. gain bandwidth) and slew rate that minimizes an amplifier total power consumption, while complying with a given total settling time specification, is presented. The method is presented for a Miller OTA, but can be generalized to other architectures. The proposed approach also provides the optimum combination of the g/sub m//I/sub D/ ratios of the input and output transistors and the transistor design corresponding to this optimum of power consumption. It is shown that the application of fixed "rules of thumb" criteria for the assignment of the allowable linear settling and slewing periods leads to highly increased consumption. The method is based on a simple, design oriented model of the settling behavior that is also described in this paper. This model is checked against experimental results and the design procedure results are verified with SPICE simulations.

In this paper, a four-quadrant current-mode multiplier based on a new squarer cell is proposed. The multiplier has a simple core, wide input current range with low power consumption, and it can easily be converted to a voltage-mode by using a balanced output transconductor (BOTA) [1]. The proposed four-quadrant current-mode and voltage-mode multipliers were confirmed by using PSPICE simulation and found to have good linearity with wide input dynamic range. For the proposed current-mode multiplier, the static power consumption is 0.671 mW, the maximum power consumption is 0.72 mW, the input current range is ±60 µA, the bandwidth is 31 MHz, the input referred noise current is 46 pA/√Hz, and the maximum linearity error is 3.9%. For the proposed voltage-mode multiplier, the static power consumption is 1.6 mW, the maximum power consumption is 1.85 mW, the input voltage range is ±1V from ±1.5V supply, the bandwidth is 25.34 MHz, the input referred noise voltage is 0.85 µV/√Hz, and the maximum linearity error is 4.1%.

Aiming at the time-varying and nonlinear problems of fixed-wing unmanned aerial vehicle (UAV) system, a UAV flight control algorithm was proposed based on PID control algorithm and the adaptive genetic algorithm (GA). On the basis of the traditional algorithm, the settling time was considered as the influencing factors of the objective function. The optimal index was determined by using the overshoot, rise time and settling time of the system response as variables, and adjusting the corresponding weight according to the actual situation to change the system response result. Moreover, the crossover probability and mutation probability in GA could be adaptively changed, so that the optimal parameters in the PID control process could be quickly and accurately found. Based on the rigid body dynamics model and kinematic model of the fixed-wing UAV, the simulation models of five control loops were designed in MATLAB/Simulink, namely the pitch angle, roll angle, yaw angle, speed and height control loops. Compared with the traditional PID controller, the system responses of the five control loops were significantly improved with faster response speed, and less than 5% overshoot. The proposed algorithm had strong adaptability and anti-interference ability.