Search results for: multi-loop control systems

Authors: Fotis N. Koumboulis, Michael G. Skarpetis, Maria P. Tzamtzi

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The problem of robust disturbance rejection (RDR) using a proportional state feedback controller is studied for the case of Left Invertible MIMO generalized state space linear systems with nonlinear uncertain structure. Sufficient conditions for the problem to have a solution are established. The set of all proportional feedback controllers solving the problem subject to these conditions is analytically determined.

Keywords: System theory, uncertain systems, robust control, singular systems.

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Authors: A. K. Kamath, N. M. Singh, R. Pasumarthy

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This paper investigates the control of a bouncing ball using Model Predictive Control. Bouncing ball is a benchmark problem for various rhythmic tasks such as juggling, walking, hopping and running. Humans develop intentions which may be perceived as our reference trajectory and tries to track it. The human brain optimizes the control effort needed to track its reference; this forms the central theme for control of bouncing ball in our investigations.

Keywords: Bouncing Ball, impact dynamics, intermittent control, model predictive control.

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Authors: Parag Nihawan, Ravinder Singh Bhatia, Dinesh Kumar Jain

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Industrial drives are source of serious power quality problems. In this, two typical industrial drives have been dealt with, namely, FOC induction motor drives and DTC induction motor drive. The Z-source inverter is an emerging topology of power electronic converters which is capable of buck boost characteristics. The performances of different control methods based Z-source inverters feeding these industrial drives have been investigated, in this work. The test systems have been modeled and simulated in MATLAB/SIMULINK. The results obtained after carrying out these simulations have been used to draw the conclusions.

Keywords: Z-Source Inverter, total harmonic distortion, direct torque control, field orientation control.

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Authors: Agus Sahri, Cahya Putra Dinata, Faishal Andhi Rokhman

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Intersection is a critical area on a highway which is a place of conflict points and congestion due to the meeting of two or more roads. Conflicts that occur at the intersection include diverging, merging, weaving, and crossing. To deal with these conflicts, a crossing control system is needed, at a plot of intersection there are two control systems namely signal intersections and non-signalized intersections. The control system at a plot of intersection can affect the intersection performance. In Indonesia there are still many intersections with poor intersection performance. In analyzing the parameters to measure the performance of a plot of intersection in Indonesia, it is guided by the 1997 Indonesian Road Capacity Manual. For this reason, this study aims to develop laboratory diagnostics at plot intersections to analyze parameters that can affect the performance of an intersection. The research method used is research and development. The laboratory diagnosis includes anamnesis, differential diagnosis, inspection, diagnosis, prognosis, specimens, analysis and sample data analysts. It is expected that this research can encourage the development and application of laboratory diagnostics at a plot of intersection in Indonesia so that intersections can function optimally.

Keywords: Intersection, laboratory diagnostic, control systems, Indonesia.

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Authors: Nemat Abazari, Ilgin Sager

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In this paper smooth trajectories are computed in the Lie group SO(2, 1) as a motion planning problem by assigning a Frenet frame to the rigid body system to optimize the cost function of the elastic energy which is spent to track a timelike curve in Minkowski space. A method is proposed to solve a motion planning problem that minimizes the integral of the Lorentz inner product of Darboux vector of a timelike curve. This method uses the coordinate free Maximum Principle of Optimal control and results in the theory of integrable Hamiltonian systems. The presence of several conversed quantities inherent in these Hamiltonian systems aids in the explicit computation of the rigid body motions.

Keywords: Optimal control, Hamiltonian vector field, Darboux vector, maximum principle, lie group, rigid body motion, Lorentz metric.

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Authors: M. Reza Bagerzadeh Karimi, M. Mahdi Bagerzadeh Karimi

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In the present paper, active control system is used in different heights of the building and the most effective part was studied where the active control system is applied. The mathematical model of the building is established in MATLAB and in order to active control the system FLC method was used. Three different locations of the building are chosen to apply active control system, namely at the lowest story, the middle height of the building, and at the highest point of the building with TMD system. The equation of motion was written for high rise building and it was solved by statespace method. Also passive control was used with Tuned Mass Damper (TMD) at the top floor of the building to show the robustness of FLC method when compared with passive control system.

Keywords: Fuzzy Logic Controller (FLC), Tuned Mass Damper(TMD), Active control, passive control

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Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco, I. Garcia-Moral

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Robust stability and performance are the two most basic features of feedback control systems. The harmonic balance analysis technique enables to analyze the stability of limit cycles arising from a neural network control based system operating over nonlinear plants. In this work a robust stability analysis based on the harmonic balance is presented and applied to a neural based control of a non-linear binary distillation column with unstructured uncertainty. We develop ways to describe uncertainty in the form of neglected nonlinear dynamics and high harmonics for the plant and controller respectively. Finally, conclusions about the performance of the neural control system are discussed using the Nyquist stability margin together with the structured singular values of the uncertainty as a robustness measure.

Keywords: Robust stability, neural network control, unstructured uncertainty, singular values, distillation column.

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Authors: Amira Abbes Kheriji, Faouzi Bouani, Mekki Ksouri, Mohamed Ben Ahmed

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Model Predictive Control (MPC) is increasingly being proposed for real time applications and embedded systems. However comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprises as well as a transformer of organizations and markets. Recently, advances in microelectronics and software allow such technique to be implemented in embedded systems. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In fact in this paper, we propose an efficient framework for implementation of Generalized Predictive Control (GPC) in the performed STM32 microcontroller. The STM32 keil starter kit based on a JTAG interface and the STM32 board was used to implement the proposed GPC firmware. Besides the GPC, the PID anti windup algorithm was also implemented using Keil development tools designed for ARM processor-based microcontroller devices and working with C/Cµ langage. A performances comparison study was done between both firmwares. This performances study show good execution speed and low computational burden. These results encourage to develop simple predictive algorithms to be programmed in industrial standard hardware. The main features of the proposed framework are illustrated through two examples and compared with the anti windup PID controller.

Keywords: Embedded systems, Model Predictive Control, microcontroller, Keil tool.

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Authors: C. Senanayake, S. Veera Ragavan

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Warehousing is commonly used in factories for the storage of products until delivery of orders. As the amount of products stored increases it becomes tedious to be carried out manually. In recent years, the manual storing has converted into fully or partially computer controlled systems, also known as Automated Storage and Retrieval Systems (AS/RS). This paper discusses an ASRS system, which was designed such that the best storage location for the products is determined by utilizing a fuzzy control system. The design maintains the records of the products to be/already in store and the storage/retrieval times along with the availability status of the storage locations. This paper discusses on the maintenance of the above mentioned records and the utilization of the concept of fuzzy logic in order to determine the optimum storage location for the products. The paper will further discuss on the dynamic splitting and merging of the storage locations depending on the product sizes.

Keywords: ASRS, fuzzy control systems, MySQL database, dynamic splitting and merging.

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Authors: Aziz Sezgin

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We consider the problem of stabilization of an unstable heat equation in a 2-D, 3-D and generally n-D domain by deriving a generalized backstepping boundary control design methodology. To stabilize the systems, we design boundary backstepping controllers inspired by the 1-D unstable heat equation stabilization procedure. We assume that one side of the boundary is hinged and the other side is controlled for each direction of the domain. Thus, controllers act on two boundaries for 2-D domain, three boundaries for 3-D domain and ”n” boundaries for n-D domain. The main idea of the design is to derive ”n” controllers for each of the dimensions by using ”n” kernel functions. Thus, we obtain ”n” controllers for the ”n” dimensional case. We use a transformation to change the system into an exponentially stable ”n” dimensional heat equation. The transformation used in this paper is a generalized Volterra/Fredholm type with ”n” kernel functions for n-D domain instead of the one kernel function of 1-D design.

Keywords: Backstepping, boundary control, 2-D, 3-D, n-D heat equation, distributed parameter systems.

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Authors: M. Sedighizadeh, A. Rezazadeh

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A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS). Actor-Critic learning is used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency, a single RBF neural network is used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for WECS and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

Keywords: Wind energy conversion systems, reinforcementlearning; Actor-Critic learning; adaptive PID control; RBF network.

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Authors: Joon-Young Park, Beom-Joo Kim, Jae-Kyung Lee

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As an effort to promote wind power industry in Korea, Korea South-East Power Corporation has been developing 22MW YeungHeung wind farm consisting of nine 2 to 3MW wind turbines supplied by three manufacturers. To maximize its availability and reliability and to solve the difficulty of operating three kinds of SCADA systems, Korea Electric Power Corporation has been developing a condition monitoring system integrated with control functions. This paper presents the developed condition monitoring system and its application to YeungHeung wind test bed, and the design of its control functions.

Keywords: condition monitoring, control function, reliability, wind turbine

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Authors: Bibhya Sharma, Jito Vanualailai, Jai Raj

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In this paper, we propose a solution to the motion planning and control problem for a swarm of three-dimensional boids. The swarm exhibit collective emergent behaviors within the vicinity of the workspace. The capability of biological systems to autonomously maneuver, track and pursue evasive targets in a cluttered environment is vastly superior to any engineered system. It is considered an emergent behavior arising from simple rules that are followed by individuals and may not involve any central coordination. A generalized, yet scalable algorithm for attraction to the centroid and inter-individual swarm avoidance is proposed. We present a set of new continuous time-invariant velocity control laws, formulated via the Lyapunov-based control scheme for target attraction and collision avoidance. The controllers provide a collision-free trajectory. The control laws proposed in this paper also ensures practical stability of the system. The effectiveness of the control laws is demonstrated via computer simulations.

Keywords: Swarm, Practical stability, Motion planning.

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Authors: Neha Khanduja

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This paper presents a comparative analysis of continuously stirred tank reactor (CSTR) control based on adaptive control and optimal tuning of PID control based on particle swarm optimization. In the design of adaptive control, Model reference adaptive control (MRAC) scheme is used, in which the adaptation law have been developed by MIT rule & Lyapunov’s rule. In PSO control parameters of PID controller is tuned by using the concept of particle swarm optimization to get optimized operating point for minimum integral square error (ISE) condition. The results show the adjustment of PID parameters converting into the optimal operating point and the good control response can be obtained by the PSO technique.

Keywords: Model reference adaptive control (MRAC), optimal control, particle swarm optimization (PSO).

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Authors: L. Benaaouinate, M. Khafallah, A. Martinez, A. Mesbahi, T. Bouragba

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This paper concerns with the modeling, simulation, and emulation of a wind turbine emulator for standalone wind energy conversion systems. By using emulation system, we aim to reproduce the dynamic behavior of the wind turbine torque on the generator shaft: it provides the testing facilities to optimize generator control strategies in a controlled environment, without reliance on natural resources. The aerodynamic, mechanical, electrical models have been detailed as well as the control of pitch angle using Fuzzy Logic for horizontal axis wind turbines. The wind turbine emulator consists mainly of an induction motor with AC power drive with torque control. The control of the induction motor and the mathematical models of the wind turbine are designed with MATLAB/Simulink environment. The simulation results confirm the effectiveness of the induction motor control system and the functionality of the wind turbine emulator for providing all necessary parameters of the wind turbine system such as wind speed, output torque, power coefficient and tip speed ratio. The findings are of direct practical relevance.

Keywords: Wind turbine, modeling, emulator, electrical generator, renewable energy, induction motor drive, field oriented control, real time control, wind turbine emulator, pitch angle control.

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Authors: S. Kahvecioglu, A. Karamancioglu, A. Yazici

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In this paper, a nonlinear model predictive swing-up and stabilizing sliding controller is proposed for an inverted pendulum-cart system. In the swing up phase, the nonlinear model predictive control is formulated as a nonlinear programming problem with energy based objective function. By solving this problem at each sampling instant, a sequence of control inputs that optimize the nonlinear objective function subject to various constraints over a finite horizon are obtained. Then, this control drives the pendulum to a predefined neighborhood of the upper equilibrium point, at where sliding mode based model predictive control is used to stabilize the systems with the specified constraints. It is shown by the simulations that, due to the way of formulating the problem, short horizon lengths are sufficient for attaining the swing up goal.

Keywords: Inverted pendulum, model predictive control, swingup, stabilization.

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Authors: Arne Koschel, Irina Astrova, Elena Deutschkämer, Jacob Ester, Johannes Feldmann

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In this paper various techniques in relation to large-scale systems are presented. At first, explanation of large-scale systems and differences from traditional systems are given. Next, possible specifications and requirements on hardware and software are listed. Finally, examples of large-scale systems are presented.

Keywords: Distributed file systems, cashing, large scale systems, MapReduce algorithm, NoSQL databases.

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Authors: Xia Zhou, Shouming Zhong

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The problem of delay-range-dependent exponential synchronization is investigated for Lur-e master-slave systems with delay feedback control and Markovian switching. Using Lyapunov- Krasovskii functional and nonsingular M-matrix method, novel delayrange- dependent exponential synchronization in mean square criterions are established. The systems discussed in this paper is advanced system, and takes all the features of interval systems, Itˆo equations, Markovian switching, time-varying delay, as well as the environmental noise, into account. Finally, an example is given to show the validity of the main result.

Keywords: Synchronization, delay-range-dependent, Markov chain, generalized Itō's formula, brownian motion, M-matrix.

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Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco

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Neural networks offer an alternative approach both for identification and control of nonlinear processes in process engineering. The lack of software tools for the design of controllers based on neural network models is particularly pronounced in this field. SIMULINK is properly a widely used graphical code development environment which allows system-level developers to perform rapid prototyping and testing. Such graphical based programming environment involves block-based code development and offers a more intuitive approach to modeling and control task in a great variety of engineering disciplines. In this paper a SIMULINK based Neural Tool has been developed for analysis and design of multivariable neural based control systems. This tool has been applied to the control of a high purity distillation column including non linear hydrodynamic effects. The proposed control scheme offers an optimal response for both theoretical and practical challenges posed in process control task, in particular when both, the quality improvement of distillation products and the operation efficiency in economical terms are considered.

Keywords: Distillation, neural networks, software tools, identification, control.

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Authors: Helder Adão, Rui Antunes, Frederico Grilo

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This paper describes the project and development of a very low-cost and small electronic prototype, especially designed for monitoring and controlling existing home automation alarm systems (intruder, smoke, gas, flood, etc.), via TCP/IP, with a typical web browser. Its use will allow home owners to be immediately alerted and aware when an alarm event occurs, and being also able to interact with their home automation alarm system, disarming, arming and watching event alerts, with a personal wireless Wi-Fi PDA or smartphone logged on to a dedicated predefined web page, and using also a PC or Laptop.

Keywords: Alarm Systems, Home Automation, Web-Server, TCP/IP.

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Authors: T. C. Kuo

Abstract:

In this paper, a novel adaptive fuzzy sliding mode control method is proposed for the robust tracking control of robotic manipulators. The proposed controller possesses the advantages of adaptive control, fuzzy control, and sliding mode control. First, system stability and robustness are guaranteed based on the sliding mode control. Further, fuzzy rules are developed incorporating with adaptation law to alleviate the input chattering effectively. Stability of the control system is proven by using the Lyapunov method. An application to a three-degree-of-freedom robotic manipulator is carried out. Accurate trajectory tracking as well as robustness is achieved. Input chattering is greatly eliminated.

Keywords: Fuzzy control, sliding mode control, roboticmanipulator, adaptive control.

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Authors: H. Nasiraghdam, A. Jalilian

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DSTATCOM is one of the equipments for voltage sag mitigation in power systems. In this paper a new control method for balanced and unbalanced voltage sag mitigation using DSTATCOM is proposed. The control system has two loops in order to regulate compensator current and load voltage. Delayed signal cancellation has been used for sequence separation. The compensator should protect sensitive loads against different types of voltage sag. Performance of the proposed method is investigated under different types of voltage sags for linear and nonlinear loads. Simulation results show appropriate operation of the proposed control system.

Keywords: Custom power, power quality, voltage sagmitigation, current vector control.

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Authors: J. Ritonja

Abstract:

The biochemical technology has been developing extremely fast since the middle of the last century. The main reason for such development represents a requirement for large production of high-quality biologically manufactured products such as pharmaceuticals, foods, and beverages. The impact of the biochemical industry on the world economy is enormous. The great importance of this industry also results in intensive development in scientific disciplines relevant to the development of biochemical technology. In addition to developments in the fields of biology and chemistry, which enable to understand complex biochemical processes, development in the field of control theory and applications is also very important. In the paper, the control for the biochemical reactor for the milk fermentation was studied. During the fermentation process, the biophysical quantities must be precisely controlled to obtain the high-quality product. To control these quantities, the bioreactor’s stirring drive and/or heating system can be used. Available commercial biochemical reactors are equipped with open loop or conventional linear closed loop control system. Due to the outstanding parameters variations and the partial nonlinearity of the biochemical process, the results obtained with these control systems are not satisfactory. To improve the fermentation process, the self-tuning adaptive control system was proposed. The use of the self-tuning adaptive control is suggested because the parameters’ variations of the studied biochemical process are very slow in most cases. To determine the linearized mathematical model of the fermentation process, the recursive least square identification method was used. Based on the obtained mathematical model the linear quadratic regulator was tuned. The parameters’ identification and the controller’s synthesis are executed on-line and adapt the controller’s parameters to the fermentation process’ dynamics during the operation. The use of the proposed combination represents the original solution for the control of the milk fermentation process. The purpose of the paper is to contribute to the progress of the control systems for the biochemical reactors. The proposed adaptive control system was tested thoroughly. From the obtained results it is obvious that the proposed adaptive control system assures much better following of the reference signal as a conventional linear control system with fixed control parameters.

Keywords: Adaptive control, biochemical reactor, linear quadratic regulator, recursive least square identification.

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Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

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Advancements in the field of artificial intelligence (AI) made during this decade have forever changed the way we look at automating spacecraft subsystems including the electrical power system. AI have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. In this paper, a mathematical modeling and MATLAB–SIMULINK model for the different components of the spacecraft power system is presented. Also, a control system, which includes either the Neural Network Controller (NNC) or the Fuzzy Logic Controller (FLC) is developed for achieving the coordination between the components of spacecraft power system as well as control the energy flows. The performance of the spacecraft power system is evaluated by comparing two control systems using the NNC and the FLC.

Keywords: Spacecraft, Neural network, Fuzzy logic control, Photovoltaic array.

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Authors: Alexander P. Eremeev, Ivan E. Kurilenko, Pavel R. Varshavskiy

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In this paper the problem of the application of temporal reasoning and case-based reasoning in intelligent decision support systems is considered. The method of case-based reasoning with temporal dependences for the solution of problems of real-time diagnostics and forecasting in intelligent decision support systems is described. This paper demonstrates how the temporal case-based reasoning system can be used in intelligent decision support systems of the car access control. This work was supported by RFBR.

Keywords: Analogous reasoning, case-based reasoning, intelligent decision support systems, temporal reasoning.

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Authors: T.C. Manjunath, B. Bandyopadhyay

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This paper features the modeling and design of a Fast Output Sampling (FOS) Feedback control technique for the Active Vibration Control (AVC) of a smart flexible aluminium cantilever beam for a Single Input Single Output (SISO) case. Controllers are designed for the beam by bonding patches of piezoelectric layer as sensor / actuator to the master structure at different locations along the length of the beam by retaining the first 2 dominant vibratory modes. The entire structure is modeled in state space form using the concept of piezoelectric theory, Euler-Bernoulli beam theory, Finite Element Method (FEM) and the state space techniques by dividing the structure into 3, 4, 5 finite elements, thus giving rise to three types of systems, viz., system 1 (beam divided into 3 finite elements), system 2 (4 finite elements), system 3 (5 finite elements). The effect of placing the sensor / actuator at various locations along the length of the beam for all the 3 types of systems considered is observed and the conclusions are drawn for the best performance and for the smallest magnitude of the control input required to control the vibrations of the beam. Simulations are performed in MATLAB. The open loop responses, closed loop responses and the tip displacements with and without the controller are obtained and the performance of the proposed smart system is evaluated for vibration control.

Keywords: Smart structure, Finite element method, State spacemodel, Euler-Bernoulli theory, SISO model, Fast output sampling, Vibration control, LMI

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Authors: Abdelaziz Sahbani, Kamel Ben Saad, Mohamed Benrejeb

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This paper deals with the comparison between two proposed control strategies for a DC-DC boost converter. The first control is a classical Sliding Mode Control (SMC) and the second one is a distance based Fuzzy Sliding Mode Control (FSMC). The SMC is an analytical control approach based on the boost mathematical model. However, the FSMC is a non-conventional control approach which does not need the controlled system mathematical model. It needs only the measures of the output voltage to perform the control signal. The obtained simulation results show that the two proposed control methods are robust for the case of load resistance and the input voltage variations. However, the proposed FSMC gives a better step voltage response than the one obtained by the SMC.

Keywords: Boost DC-DC converter, Sliding Mode Control (SMC), Fuzzy Sliding Mode Control (FSMC), Robustness.

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Authors: M. A. Okezue, K. L. Clase, S. R. Byrn, P. Shivanand

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Medicines regulatory authorities expect pharmaceutical companies and contract research organizations to seek ways to certify that their laboratory control measurements are reliable. Establishing and maintaining laboratory quality standards are essential in ensuring the accuracy of test results. ‘ISO/IEC 17025:2017’ and ‘WHO Good Practices for Pharmaceutical Quality Control Laboratories (GPPQCL)’ are two quality standards commonly employed in developing laboratory quality systems. A review was conducted on the two standards to elaborate on areas on convergence and divergence. The goal was to understand how differences in each standard's requirements may influence laboratories' choices as to which document is easier to adopt for quality systems. A qualitative review method compared similar items in the two standards while mapping out areas where there were specific differences in the requirements of the two documents. The review also provided a detailed description of the clauses and parts covering management and technical requirements in these laboratory standards. The review showed that both documents share requirements for over ten critical areas covering objectives, infrastructure, management systems, and laboratory processes. There were, however, differences in standard expectations where GPPQCL emphasizes system procedures for planning and future budgets that will ensure continuity. Conversely, ISO 17025 was more focused on the risk management approach to establish laboratory quality systems. Elements in the two documents form common standard requirements to assure the validity of laboratory test results that promote mutual recognition. The ISO standard currently has more global patronage than GPPQCL.

Keywords: ISO/IEC 17025:2017, laboratory standards, quality control, WHO GPPQCL

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Authors: Robert Gold

Abstract:

Control flow graphs are a well-known representation of the sequential control flow structure of programs with a multitude of applications. Not only single functions but also sets of functions or complete programs can be modeled by control flow graphs. In this case the size of the graphs can grow considerably and thus makes it difficult for software engineers to analyze the control flow. Graph reductions are helpful in this situation. In this paper we define reductions to subsets of nodes. Since executions of programs are represented by paths through the control flow graphs, paths should be preserved. Furthermore, the composition of reductions makes a stepwise analysis approach possible.

Keywords: Control flow graph, graph reduction.

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Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

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In Zambia, recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines, to upgrade power systems into smart grids, target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, they are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, and therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we present a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: Anomaly detection, SmartGrid, edge, maintainability, reliability, stochastic process.

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