International Science Index

101
10006341
Stochastic Model Predictive Control for Linear Discrete-Time Systems with Random Dither Quantization
Abstract:
Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.
Paper Detail
120
downloads
100
10006444
Optimal Tuning of Linear Quadratic Regulator Controller Using a Particle Swarm Optimization for Two-Rotor Aerodynamical System
Abstract:
This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed.
Paper Detail
6
downloads
99
10006052
Stability of Stochastic Model Predictive Control for Schrödinger Equation with Finite Approximation
Abstract:
Recent technological advance has prompted significant interest in developing the control theory of quantum systems. Following the increasing interest in the control of quantum dynamics, this paper examines the control problem of Schrödinger equation because quantum dynamics is basically governed by Schrödinger equation. From the practical point of view, stochastic disturbances cannot be avoided in the implementation of control method for quantum systems. Thus, we consider here the robust stabilization problem of Schrödinger equation against stochastic disturbances. In this paper, we adopt model predictive control method in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. The objective of this study is to derive the stability criterion for model predictive control of Schrödinger equation under stochastic disturbances.
Paper Detail
880
downloads
98
10005569
Solutions to Probabilistic Constrained Optimal Control Problems Using Concentration Inequalities
Abstract:
Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.
Paper Detail
423
downloads
97
10005652
Movement Optimization of Robotic Arm Movement Using Soft Computing
Authors:
Abstract:

Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Paper Detail
241
downloads
96
10005955
Optimal Bayesian Control of the Proportion of Defectives in a Manufacturing Process
Abstract:
In this paper, we present a model and an algorithm for the calculation of the optimal control limit, average cost, sample size, and the sampling interval for an optimal Bayesian chart to control the proportion of defective items produced using a semi-Markov decision process approach. Traditional p-chart has been widely used for controlling the proportion of defectives in various kinds of production processes for many years. It is well known that traditional non-Bayesian charts are not optimal, but very few optimal Bayesian control charts have been developed in the literature, mostly considering finite horizon. The objective of this paper is to develop a fast computational algorithm to obtain the optimal parameters of a Bayesian p-chart. The decision problem is formulated in the partially observable framework and the developed algorithm is illustrated by a numerical example.
Paper Detail
121
downloads
95
10005440
Study on Optimal Control Strategy of PM2.5 in Wuhan, China
Abstract:

In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given.

Paper Detail
594
downloads
94
10004568
Disaggregating and Forecasting the Total Energy Consumption of a Building: A Case Study of a High Cooling Demand Facility
Abstract:
Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  
Paper Detail
435
downloads
93
10005056
An Algorithm for Estimating the Stable Operation Conditions of the Synchronous Motor of the Ore Mill Electric Drive
Abstract:
An algorithm for estimating the stable operation conditions of the synchronous motor of the ore mill electric drive is proposed. The stable operation conditions of the synchronous motor are revealed, taking into account the estimation of the q angle change and the technological factors. The stability condition obtained allows to ensure the stable operation of the motor in the synchronous mode, taking into account the nonlinear character of the mill loading. The developed algorithm gives an opportunity to present the undesirable phenomena, arising in the electric drive system. The obtained stability condition can be successfully applied for the optimal control of the electromechanical system of the mill.
Paper Detail
205
downloads
92
10004085
Stochastic Control of Decentralized Singularly Perturbed Systems
Abstract:

Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.

Paper Detail
685
downloads
91
10004030
Optimal Voltage and Frequency Control of a Microgrid Using the Harmony Search Algorithm
Abstract:

The stability is an important topic to plan and manage the energy in the microgrids as the same as the conventional power systems. The voltage and frequency stability is one of the most important issues recently studied in microgrids. The objectives of this paper are the modelling and designing of the components and optimal controllers for the voltage and frequency control of the AC/DC hybrid microgrid under the different disturbances. Since the PI controllers have the advantages of simple structure and easy implementation, so they are designed and modeled in this paper. The harmony search (HS) algorithm is used to optimize the controllers’ parameters. According to the achieved results, the PI controllers have a good performance in voltage and frequency control of the microgrid.

Paper Detail
435
downloads
90
10002375
Conservativeness of Probabilistic Constrained Optimal Control Method for Unknown Probability Distribution
Abstract:
In recent decades, probabilistic constrained optimal control problems have attracted much attention in many research fields. Although probabilistic constraints are generally intractable in an optimization problem, several tractable methods haven been proposed to handle probabilistic constraints. In most methods, probabilistic constraints are reduced to deterministic constraints that are tractable in an optimization problem. However, there is a gap between the transformed deterministic constraints in case of known and unknown probability distribution. This paper examines the conservativeness of probabilistic constrained optimization method for unknown probability distribution. The objective of this paper is to provide a quantitative assessment of the conservatism for tractable constraints in probabilistic constrained optimization with unknown probability distribution.
Paper Detail
1061
downloads
89
10002572
Developing New Algorithm and Its Application on Optimal Control of Pumps in Water Distribution Network
Abstract:
In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.
Paper Detail
712
downloads
88
10001865
Computational Simulations on Stability of Model Predictive Control for Linear Discrete-time Stochastic Systems
Abstract:
Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the effectiveness of the obtained stability condition.
Paper Detail
962
downloads
87
10002456
GSA-Based Design of Dual Proportional Integral Load Frequency Controllers for Nonlinear Hydrothermal Power System
Abstract:
This paper considers the design of Dual Proportional- Integral (DPI) Load Frequency Control (LFC), using gravitational search algorithm (GSA). The design is carried out for nonlinear hydrothermal power system where generation rate constraint (GRC) and governor dead band are considered. Furthermore, time delays imposed by governor-turbine, thermodynamic process, and communication channels are investigated. GSA is utilized to search for optimal controller parameters by minimizing a time-domain based objective function. GSA-based DPI has been compared to Ziegler- Nichols based PI, and Genetic Algorithm (GA) based PI controllers in order to demonstrate the superior efficiency of the proposed design. Simulation results are carried for a wide range of operating conditions and system parameters variations.
Paper Detail
1033
downloads
86
10005157
Comparative Dynamic Performance of Load Frequency Control of Nonlinear Interconnected Hydro-Thermal System Using Intelligent Techniques
Abstract:
This paper demonstrates dynamic performance evaluation of load frequency control (LFC) with different intelligent techniques. All non-linearities and physical constraints have been considered in simulation studies such as governor dead band (GDB), generation rate constraint (GRC) and boiler dynamics. The conventional integral time absolute error has been considered as objective function. The design problem is formulated as an optimisation problem and particle swarm optimisation (PSO), bacterial foraging optimisation algorithm (BFOA) and differential evolution (DE) are employed to search optimal controller parameters. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic control (FLC) for the same interconnected power system. The comparison is done using various performance measures like overshoot, undershoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than FLC. Further, robustness analysis is carried out by varying the time constants of speed governor, turbine, tie-line power in the range of +40% to -40% to demonstrate the robustness of the proposed DE optimized PID controller.
Paper Detail
243
downloads
85
9998763
Optimal Control of Volterra Integro-Differential Systems Based On Legendre Wavelets and Collocation Method
Abstract:

In this paper, the numerical solution of optimal control problem (OCP) for systems governed by Volterra integro-differential (VID) equation is considered. The method is developed by means of the Legendre wavelet approximation and collocation method. The properties of Legendre wavelet together with Gaussian integration method are utilized to reduce the problem to the solution of nonlinear programming one. Some numerical examples are given to confirm the accuracy and ease of implementation of the method.

Paper Detail
1772
downloads
84
9998456
An Inverse Optimal Control Approach for the Nonlinear System Design Using ANN
Abstract:

The design of a feedback controller, so as to minimize a given performance criterion, for a general non-linear dynamical system is difficult; if not impossible. But for a large class of non-linear dynamical systems, the open loop control that minimizes a performance criterion can be obtained using calculus of variations and Pontryagin’s minimum principle. In this paper, the open loop optimal trajectories, that minimizes a given performance measure, is used to train the neural network whose inputs are state variables of non-linear dynamical systems and the open loop optimal control as the desired output. This trained neural network is used as the feedback controller. In other words, attempts are made here to solve the “inverse optimal control problem” by using the state and control trajectories that are optimal in an open loop sense.

Paper Detail
1378
downloads
83
9998586
Application of STATCOM-SMES Compensator for Power System Dynamic Performance Improvement
Abstract:

Nowadays the growth of distributed generation within the bulk power system is feasible by using the optimal control of the transmission lines power flow. Static Synchronous Compensators (STATCOM) is effective for improving voltage stability but it can only exchange reactive power with the power grid. The integration of Superconducting Magnetic Energy Storage (SMES) with a STATCOM can extend the traditional STATCOM capabilities to four-quadrant bulk power system power flow control and providing exchange both the active and reactive power related to the STATCOM with the ac network. This paper shows how the SMES system can be connected to the ac system via the DC bus of a STATCOM and also analyzes how the integration of STATCOM and SMES allows the bus voltage regulation and power oscillation damping (POD) to be achieved simultaneously. The dynamic performance of the integrated STATCOM-SMES is evaluated through simulation by using PSCAD/EMTDC software and the compensation effectiveness of this integrated compensator is shown.

Paper Detail
1559
downloads
82
9997539
Optimum Parameter of a Viscous Damper for Seismic and Wind Vibration
Abstract:

Determination of optimal parameters of a passive  control system device is the primary objective of this study.  Expanding upon the use of control devices in wind and earthquake  hazard reduction has led to development of various control systems.  The advantage of non-linearity characteristics in a passive control  device and the optimal control method using LQR algorithm are  explained in this study. Finally, this paper introduces a simple  approach to determine optimum parameters of a nonlinear viscous  damper for vibration control of structures. A MATLAB program is  used to produce the dynamic motion of the structure considering the  stiffness matrix of the SDOF frame and the non-linear damping  effect. This study concluded that the proposed system (variable  damping system) has better performance in system response control  than a linear damping system. Also, according to the energy  dissipation graph, the total energy loss is greater in non-linear  damping system than other systems.

 

Paper Detail
2220
downloads
81
9998018
Gravitational Search Algorithm (GSA) Optimized SSSC Based Facts Controller to Improve Power System Oscillation Stability
Abstract:

In this paper, an investigation into the use of modified Genetic Algorithm optimized SSSC based controller to aid damping of low frequency inter-area oscillations in power systems is presented. Controller design is formulated as a nonlinear constrained optimization problem and modified Genetic Algorithm (MGA) is employed to search for the optimal controller parameters. For evaluation of effectiveness and robustness of proposed controllers, the performance was tested on multi-machine system subjected to different disturbances, loading conditions and system parameter variations. Simulation results are presented to show the fine performance of the proposed SSSC controller in damping the critical modes without significantly deteriorating the damping characteristics of other modes in multi-machine power system.

Paper Detail
1266
downloads
80
9998385
Load Frequency Control of Nonlinear Interconnected Hydro-Thermal System Using Differential Evolution Technique
Abstract:

This paper presents a differential evolution algorithm to design a robust PI and PID controllers for Load Frequency Control (LFC) of nonlinear interconnected power systems considering the boiler dynamics, Governor Dead Band (GDB), Generation Rate Constraint (GRC). Differential evolution algorithm is employed to search for the optimal controller parameters. The proposed method easily copes of with nonlinear constraints. Further the proposed controller is simple, effective and can ensure the desirable overall system performance. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic controller for the same power systems. The comparison is done using various performance measures like overshoot, settling time and standard error criteria of frequency and tie-line power deviation following a 1% step load perturbation in hydro area. It is noticed that, the dynamic performance of proposed controller is better than fuzzy logic controller. Furthermore, it is also seen that the proposed system is robust and is not affected by change in the system parameters.

Paper Detail
2213
downloads
79
9997287
The Optimal Indirect Vector Controller Design via an Adaptive Tabu Search Algorithm
Abstract:

The paper presents how to design the indirect vector control of three-phase induction motor drive systems using the artificial intelligence technique called the adaptive tabu search. The results from the simulation and the experiment show that the drive system with the controller designed from the proposed method can provide the best output speed response compared with those of the conventional method. The controller design using the proposed technique can be used to create the software package for engineers to achieve the optimal controller design of the induction motor speed control based on the indirect vector concept.

 

Paper Detail
1097
downloads
78
17207
Adaptive Dynamic Time Warping for Variable Structure Pattern Recognition
Abstract:

Pattern discovery from time series is of fundamental importance. Particularly, when information about the structure of a pattern is not complete, an algorithm to discover specific patterns or shapes automatically from the time series data is necessary. The dynamic time warping is a technique that allows local flexibility in aligning time series. Because of this, it is widely used in many fields such as science, medicine, industry, finance and others. However, a major problem of the dynamic time warping is that it is not able to work with structural changes of a pattern. This problem arises when the structure is influenced by noise, which is a common thing in practice for almost every application. This paper addresses this problem by means of developing a novel technique called adaptive dynamic time warping.

Paper Detail
1176
downloads
77
1295
The Optimized Cascade PI Controllers of the Generator Control Unit in the Aircraft Power System
Abstract:
This paper presents the optimal controller design of the generator control unit in the aircraft power system. The adaptive tabu search technique is applied to tune the controller parameters until the best terminal output voltage of generator is achieved. The output response from the system with the controllers designed by the proposed technique is compared with those from the conventional method. The transient simulations using the commercial software package show that the controllers designed from the adaptive tabu search algorithm can provide the better output performance compared with the result from the classical method. The proposed design technique is very flexible and useful for electrical aircraft engineers.
Paper Detail
1643
downloads
76
16738
A Direct Probabilistic Optimization Method for Constrained Optimal Control Problem
Abstract:

A new stochastic algorithm called Probabilistic Global Search Johor (PGSJ) has recently been established for global optimization of nonconvex real valued problems on finite dimensional Euclidean space. In this paper we present convergence guarantee for this algorithm in probabilistic sense without imposing any more condition. Then, we jointly utilize this algorithm along with control parameterization technique for the solution of constrained optimal control problem. The numerical simulations are also included to illustrate the efficiency and effectiveness of the PGSJ algorithm in the solution of control problems.

Paper Detail
925
downloads
75
9996748
STATCOM based Damping Controller in Power Systems for Enhance the Power System Stability
Abstract:

This paper describes the power-system stability improvement by a static synchronous compensator (STATCOM) based damping controller with Differential evolution (DE) algorithm is used to find out the optimal controller parameters. The present study considered both local and remote signals with associated time delays. The performances of the proposed controllers have been compared with different disturbances for both single-machine infinite bus power system and multi-machine power system. The performance of the proposed controllers with variations in the signal transmission delays has also been investigated. To show the effectiveness and robustness of the proposed controller the Simulation results are presented under different disturbances and loading conditions.

Paper Detail
1661
downloads
74
17235
Coordinated Design of PSS and STATCOM for Power System Stability Improvement Using Bacteria Foraging Algorithm
Abstract:

This paper presents the coordinated controller design of static synchronous compensator (STATCOM) and power system stabilizers (PSSs) for power system stability improvement. Coordinated design problem of STATCOM-based controller with multiple PSSs is formulated as an optimization problem and optimal controller parameters are obtained using bacteria foraging optimization algorithm. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is improved. The nonlinear simulation results show that coordinated design of STATCOM-based controller and PSSs improve greatly the system damping oscillations and consequently stability improvement.

Paper Detail
1848
downloads
73
9996960
Compliance Modelling and Optimization of Kerf during WEDM of Al7075/SiCP Metal Matrix Composite
Abstract:

This investigation presents the formulation of kerf (width of slit) and optimal control parameter settings of wire electrochemical discharge machining which results minimum possible kerf while machining Al7075/SiCp MMCs. WEDM is proved its efficiency and effectiveness to cut the hard ceramic reinforced MMCs within the permissible budget. Among the distinct performance measures of WEDM process, kerf is an important performance characteristic which determines the dimensional accuracy of the machined component while producing high precision components. The lack of available of the machinability information such advanced MMCs result the more experimentation in the manufacturing industries. Therefore, extensive experimental investigations are essential to provide the database of effect of various control parameters on the kerf while machining such advanced MMCs in WEDM. Literature reviled the significance some of the electrical parameters which are prominent on kerf for machining distinct conventional materials. However, the significance of reinforced particulate size and volume fraction on kerf is highlighted in this work while machining MMCs along with the machining parameters of pulse-on time, pulse-off time and wire tension. Usually, the dimensional tolerances of machined components are decided at the design stage and a machinist pay attention to produce the required dimensional tolerances by setting appropriate machining control variables. However, it is highly difficult to determine the optimal machining settings for such advanced materials on the shop floor. Therefore, in the view of precision of cut, kerf (cutting width) is considered as the measure of performance for the model. It was found from the literature that, the machining conditions of higher fractions of large size SiCp resulting less kerf where as high values of pulse-on time result in a high kerf. A response surface model is used to predict the relative significance of various control variables on kerf. Consequently, a powerful artificial intelligence called genetic algorithms (GA) is used to determine the best combination of the control variable settings. In the next step the conformation test was conducted for the optimal parameter settings and found good agreement between the GA kerf and measured kerf. Hence, it is clearly reveal that the effectiveness and accuracy of the developed model and program to analyze the kerf and to determine its optimal process parameters. The results obtained in this work states that, the resulted optimized parameters are capable of machining the Al7075/SiCp MMCs more efficiently and with better dimensional accuracy.

Paper Detail
1197
downloads
72
9706
Advanced ILQ Control for Buck-Converter viaTwo-Degrees of Freedom Servo-System
Abstract:

In this paper, we propose an advanced ILQ control for the buck-converter via two-degrees of freedom servo-system. Our presented strategy is based on Inverse Linear Quadratic (ILQ) servo-system controller without solving Riccati-s equation directly. The optimal controller of the current and voltage control system is designed. The stability and robust control are analyzed. A conscious and persistent effort has been made to improve ILQ control via two-degrees of freedom guarantees the optimal gains on the basis of polynomial pole assignment, which our results of the proposed strategy shows that the advanced ILQ control can be controlled independently the step response and the disturbance response by appending a feed-forward compensator.

Paper Detail
1193
downloads