Smart Control of Automatic Voltage Regulators using K-means Clustering

The future cyber physical systems consist of voltage regulators distributed across wide geographical areas. In this paper, a smart control approach of voltage regulators is presented for cyber physical system applications. The approach is implemented using K-means clustering algorithms that use data from voltage and current sensors, compute the correlation of changes across the regulators and generate a proportional feedback. Advanced estimation methods are used in cases where the data from the sensors was not available. The results show that the approach could be used to improve the performance of networked, power dependent systems by 94.5% in terms of overshoot and 9.52% in terms of response time as compared to other methods of controlling voltage regulators

Parallelized Distributed Embedded Control System for 2D Walking Robot for Studying Rough Terrain Locomotion

Biped robots present many advantages for exploration over mobile robots. They do not require a continuous path, which allows them to navigate over a much larger range of terrain. Currently, bipeds have been successful at walking on flat surfaces and non-periodic rough terrain such as stairs, but few have shown success on unknown periodic terrain. The Jaywalker is a 2D walker designed to study locomotion on uneven terrain. It is a fully active robot providing actuation at every joint. A distributed, parallelized, embedded control system was developed to provide the control structure for the Jaywalker. This system was chosen for its ability to execute simultaneous tasks efficiently. The two level control system provides a first level to implement a higher level control strategy, and a second lower level to drive the Jaywalker's systems. The concept was implemented using the Parallax Propeller chip for its relative fast clock frequencies and parallel computing functionality. The chips communicate over a new variation of the I2C bus, which allows multiple slaves to listen to information simultaneously reducing the number of transmissions for redundant data transfers. The system has shown success in taking steps with open loop control. The success of the step is highly dependent on the initial step length using open loop control, but this dependency can be eliminated using closed loop control. The robust structure will provide an excellent platform for uneven terrain locomotion research

An ANN-based temperature controller for a plastic injection moulding system

This paper proposes an approach to an ANN-based temperature controller design for a plastic injection moulding system. This design approach is applied to the development of a controller based on a combination of a classical ANN and integrator. The controller provides a fast temperature response and zero steady-state error for three typical heaters (bar, nozzle, and cartridge) for a plastic moulding system. The simulation results in Matlab Simulink software and in comparison to an industrial PID regulator have shown the advantages of the controller, such as significantly less overshoot and faster transient (compared to PID with autotuning) for all examined heaters. In order to verify the proposed approach, the designed ANN controller was implemented and tested using an experimental setup based on an STM32 board

Design of Power System Stabilizer

A power system stabilizer (PSS) installed in the excitation system of the synchronous generator improves the small-signal power system stability by damping out low frequency oscillations in the power system. It does that by providing supplementary perturbation signals in a feedback path to the alternator excitation system. In our project we review different conventional PSS design (CPSS) techniques along with modern adaptive neuro-fuzzy design techniques. We adapt a linearized single-machine infinite bus model for design and simulation of the CPSS and the voltage regulator (AVR). We use 3 different input signals in the feedback (PSS) path namely, speed variation(w), Electrical Power (Pe), and integral of accelerating power (Pe*w), and review the results in each case. For simulations, we use three different linear design techniques, namely, root-locus design, frequency-response design, and pole placement design; and the preferred non-linear design technique is the adaptive neuro-fuzzy based controller design. The MATLAB package with Control System Toolbox and SIMULINK is used for the design and simulations

Quadcopter: Design, modelling, control and trajectory tracking

A quadcopter is a type of unmanned aerial vehicles (UAV). The industry of this type of UAVs is growing exponentially in terms of new technology development and the increase of potential applications that may cover construction inspections, search and rescue, surveillance, aerial photography, monitoring, mapping, etc. A quadcopter is a nonlinear and under-actuated system that introduces complex aerodynamics properties and create challenges which demands the development of new, reliable and effective control techniques to enhance the stability of flight control, plan and track a desired trajectory while minimizing the effect induced by the operational environment and its own sensors. Hence, many control techniques have been developed and researched. Some of such developments work well with the provision of having an accurate mathematical model of the system while other work is associated with a mathematical model that can accommodate certain level of wind disturbances and uncertainties related to measurement noise. Moreover, various linear, nonlinear and intelligent control techniques were developed and recognized in the literature. Each one of such control techniques has some aspect that excels in under certain conditions. The focus of this thesis is to develop different control techniques that can improve flight control stability, trajectory tracking of a quadcopter and evaluate their performance to select the best suitable control technique that can realize the stated technical flight control requirements. Accordingly, three main techniques have been developed: Standard PID, Fuzzy based control technique that tune PID parameters in real time (FPID) and a Hybrid control strategy that consists of three control techniques: (a) FPID with state coordinates transformation (b) State feedback (c) Sliding mode The configuration of the hybrid control strategy consists of two control loops. The inner control loop aims to control the quadcopter\u27s attitude and altitude while the outer control loop aims to control the quadcopter\u27s position. Two configurations were used to configure the developed control techniques of the control loops. These configurations are: (a) A sliding mode control is used for the outer loop while for the inner loop two control techniques are used to realize it: a Fuzzy gain scheduled PID with state coordinates transformation and a state feedback control. (b) Fuzzy gain scheduled PID control is used for the outer loop while for the inner loop two control techniques are used to realize it using the same formation as in (a) above. Furthermore, in order to ensure a feasible desired trajectory before tracking it, a trajectory planning algorithm has been developed and tested successfully. Subsequently, a simulation testing environment with friendly graphical User Interface (GUI) has been developed to simulate the quadcopter mathematical model and then to use it as a test bed to validate the developed control techniques with and without the effect of wind disturbance and measurement noise. The quadcopter with each control technique has been tested using the simulation environment under different operational conditions. The results in terms of tracking a desired trajectory shows the robustness of the first configuration of control techniques within the hybrid control strategy under the presence of wind disturbance and measurement noise compared to all the other techniques developed. Then, the second configuration of the control techniques came second in terms of results quality. The third and fourth results in the sequence shown by the fuzzy scheduled PID and the standard PID respectively. Finally, Validating the simulation results on a real system, a quadcopter has been successfully designed, implemented and tested. The developed control techniques were tested using the implemented quadcopter and the results were demonstrated and compared with the simulation results

Electronic CVT - Controls

The following document outlines the design process, manufacturing, and testing of the control system for an electronically controlled continuously variable transmission (ECVT). This control system was integrated into the custom designed and manufactured mechanical transmission system created in parallel by another senior project group. The transmission was designed for use in the Cal Poly Baja SAE vehicle. Through researching customer needs, competition requirements, previous and alternate CVT designs, and vehicle characteristics, we were able to determine the requirements and specifications for our unique system. Input, output, speed, and durability requirements guided our hardware selection. The primary components which comprised our system include an alternator and regulator, a custom circuit board, rotary encoders and hall effect sensors, brushed DC motors, lead screws, and a custom system enclosure; further details are included in the Final Design section of this report. With the knowledge of our vehicle characteristics, actuation mode, and inputs, a system model determined that a standard proportional + integral action (PI) controller would be sufficient to obtain the speed and accuracy demanded by our customer needs. Electrical components were assembled, tested, and programmed on a prototyping breadboard, and a custom printed circuit board (PCB) was outsourced for manufacture following qualification of our prototype. The final production board was bench tested with the mechanical CVT system to ensure it met all customer and design requirements. Furthermore, the enclosure was tested to ensure the safety and durability of the electrical systems. Planning and timing mismanagement between our team, the mechanical design team, and Cal Poly SAE Baja team, in conjunction with controls specific setbacks, resulted in the final combined system remaining untested on the Baja vehicle. This project is being continued by a new senior project group which will continue to test and improve upon the current system during the 2019-2020 academic year

Flow-oriented anomaly-based detection of denial of service attacks with flow-control-assisted mitigation

Flooding-based distributed denial-of-service (DDoS) attacks present a serious and major threat to the targeted enterprises and hosts. Current protection technologies are still largely inadequate in mitigating such attacks, especially if they are large-scale. In this doctoral dissertation, the Computer Network Management and Control System (CNMCS) is proposed and investigated; it consists of the Flow-based Network Intrusion Detection System (FNIDS), the Flow-based Congestion Control (FCC) System, and the Server Bandwidth Management System (SBMS). These components form a composite defense system intended to protect against DDoS flooding attacks. The system as a whole adopts a flow-oriented and anomaly-based approach to the detection of these attacks, as well as a control-theoretic approach to adjust the flow rate of every link to sustain the high priority flow-rates at their desired level. The results showed that the misclassification rates of FNIDS are low, less than 0.1%, for the investigated DDOS attacks, while the fine-grained service differentiation and resource isolation provided within the FCC comprise a novel and powerful built-in protection mechanism that helps mitigate DDoS attacks

Fuzzy Logic for pH Neutralization Process

pH neutralization process is a process that is widely studied due to its highly nonlinear process reaction. Its nonlinearity behavior is caused by static nonlinearity between pH and concentration. This nonlinearity depends on the substances in the solution and on their concentrations. In this project, the nonlinearity of the process was investigated. Later, the mathematical model of the process was developed based on McAvoy et al [I]. In addition to the mathematical model, an empirical model was also obtained from Analytical & Chemical Pilot Plant located in the Process Control & Instrumentation Laboratory (23-00-06). Both models were then used to develop the Fuzzy Logic Controller (FLC) by using Advanced-Neuro Fuzzy Inference System (ANFIS) and also gain-scheduling method. In ANFIS implementation for empirical model, the FLC output was identical to the output from PID. Therefore it is concluded that FLC could be used to replace PID for empirical model. In ANFIS implementation for mathematical model, the FLC also could be implemented for mathematical model since the controlled variable successfully follows all the set point changes. For gainscheduling method, the FLC was tested on servo and regulator problems. The servo test was performed by using a random number generator to generate random pH set points between 3 and 11 and the simulation is performed for 100 seconds. The result for the servo test was similar with the result from the ANFIS implementation for mathematical model. For regulator test, the disturbance was the ±20% variation in acid flow. The result for the regulator shows, the controller manages to eliminate the disturbance effect in the process variable. In overall, the project successfully shows that FLC could be a good alternative to PID controller

Studies on SI engine simulation and air/fuel ratio control systems design

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.More stringent Euro 6 and LEV III emission standards will immediately begin execution on 2014 and 2015 respectively. Accurate air/fuel ratio control can effectively reduce vehicle emission. The simulation of engine dynamic system is a very powerful method for developing and analysing engine and engine controller. Currently, most engine air/fuel ratio control used look-up table combined with proportional and integral (PI) control and this is not robust to system uncertainty and time varying effects. This thesis first develops a simulation package for a port injection spark-ignition engine and this package include engine dynamics, vehicle dynamics as well as driving cycle selection module. The simulations results are very close to the data obtained from laboratory experiments. New controllers have been proposed to control air/fuel ratio in spark ignition engines to maximize the fuel economy while minimizing exhaust emissions. The PID control and fuzzy control methods have been combined into a fuzzy PID control and the effectiveness of this new controller has been demonstrated by simulation tests. A new neural network based predictive control is then designed for further performance improvements. It is based on the combination of inverse control and predictive control methods. The network is trained offline in which the control output is modified to compensate control errors. The simulation evaluations have shown that the new neural controller can greatly improve control air/fuel ratio performance. The test also revealed that the improved AFR control performance can effectively restrict engine harmful emissions into atmosphere, these reduce emissions are important to satisfy more stringent emission standards

Clustering methods for the efficient voltage regulation in smart grids

In this paper, clustering methods are presented to enhance the stability of automatic voltage regulators using the efficient adjustment of their respective gains. The results show that implementations of some of the clustering algorithms provide better reliability and stability for the feedback-based voltage regulators as compared to the other methods, namely, a model predictive controller (MPC), a gaussian mixture model (GMM), a self-organizing mapping (SOM) and hierarchical clustering (HC) methods. Specifically, the K-Means clustering approach (KM) provided superior stability but a slower rise time of the output voltage of the voltage regulators as compared to the other methods. Furthermore, coordination of the clustering methods is tested for a 10 machine, 39 bus power grid system. The results show that the clustering approach could be applied to improve the efficiency of voltage regulation methods in smart grids and related cyber-physical systems