Subrat Kumar Swain

Incorporating uncertainty and risk in transportation investment decision-making

This paper presents a framework for addressing uncertainty and risk for large-scale transportation investments involving public–private participation. Demand, fare/toll and demand responsive costs are considered in the uncertainty analysis. Uncertainty analysis provides information on economic feasibility of the project. A set of relaxation policies is proposed to form various Ownership, Tenure and Governance (OTG) strategies reflecting the nature and level of participation by the public and private entity. A Monte Carlo Simulation-based Value at Risk is used to quantify risk. Finally, a methodology is proposed to integrate uncertainty and risk. The framework is tested on the proposed multibillion dollar Detroit River International Crossing connecting the cities of Detroit in the USA with Windsor in Canada. The analysis provides insights to probable outcomes for this transportation infrastructure investment under different OTG scenarios.

PID controller design for cruise control system using genetic algorithm

In this paper, the design of a Proportional-Integral-Derivative (PID) controller for the cruise control system has been proposed. The cruise control system, which is a highly nonlinear, has been linearized around the equilibrium point. The controller has been designed for the linearized model, by taking the dominant pole concept in the closed loop characteristic equation. The PID controller parameters, i.e. proportional, integral and derivative parameters have been tuned using Genetic Algorithm (GA). In this study, the performance of the controller has been compared with that of the conventional PID, state space and Fuzzy logic based controller. The simulation output reveals the superiority of the proposed controller in terms of maximum overshoot, peak time, rise time, settling time and steady state error. The sensitivity and complementary sensitivity analysis show the robust behaviour of the system with output disturbance and high-frequency noise rejection qualities. As a scope of further research, fractional order and 2-dof PID controller will be designed for this cruise control system and the performance will be compared with this design.

Robust 2-DOF FOPID Controller Design for Maglev System Using Jaya Algorithm

In this paper, 1-Degree of Freedom (1-DOF) and 2-Degree of Freedom (2-DOF) Integer Order (IO) and Fractional Order (FO) Proportional–Integral–Derivative (PID) Controller has been designed for the Magnetic Levitation (Maglev) system. Maglev is one of the most versatile research-oriented laboratory instruments in the field of control systems engineering. The controller for the Maglev system is designed in such a way that a ferromagnetic ball can precisely levitate in a controlled electromagnetic field with particular design specifications. The controller parameters can be appropriately identified by optimizing the objective function with various popular artificial intelligence based evolutionary optimization algorithms. The 2-DOF controller structure takes care of both reference signal tracking and disturbance rejection through the feedback path. The 1 and 2-DOF controller structures with both Integer as well as Fractional Order approaches for different nonlinear systems were already discussed in various papers. However, the application of the Fractional Order control technique on a highly nonlinear Maglev system using the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Hybrid Particle Swarm Optimization (Hybrid PSO), and recently developed Jaya Algorithm is of our interest. Observation of the final analysis based on different simulation results states that as the controller structure moves from 1-DOF to 2-DOF, the performance of the system and the control signal gets improved. The robustness analysis has also been incorporated in this study which shows that the 1 and 2-DOF IOPID and FOPID controllers designed using different optimization algorithms for the Maglev plant are robust in nature.

Design of Two-Loop PID Controller for Inverted Cart-Pendulum System Using Modified Genetic Algorithm

This study focuses on the design of controllers for inverted cart-pendulum system. This cart-pendulum system, a nonlinear one, has been linearized around the equilibrium point to obtain linearized model transfer function. In this paper, the design of two-loop proportional integral derivative (PID) controller that gives more flexibility to control the inverted cart-pendulum system has been considered and the controller parameters have been optimized through modified genetic algorithm (GA). Furthermore, other methods such as LQR and LQG have been applied to verify closed loop response of the system for unit step signal. A performance comparison between the above mentioned techniques is investigated and the analysis shows superiority of two-loop PID controller in terms of both overshoot and settling time as compared to other mentioned methods. A comprehensive analysis of robustness to model uncertainties will be incorporated in the future work.

Real-Time Performance Analysis of FOI-PD Controller for Twin Rotor MIMO System

ABSTRACT Designing a controller for the Twin Rotor MIMO System (TRMS) is a challenging task due to the presence of high non-linearity and cross-coupling between different elements. In this paper, a Fractional Order Integral–Proportional Derivative (FOI-PD) controller has been realized and implemented in both simulation and real-time for the control of pitch and yaw angle of the TRMS. The novelty of the present work lies in the implementation of the robust FOI-PD controller, which has not yet been explored by the researchers for the TRMS kit to the best of authors’ knowledge. The nonlinear interior point optimization technique (fmincon function available in MATLAB optimization toolbox) has been utilized to identify the suitable controller parameter values by minimizing the cost functions within a predefined interval of controller parameters. The transient performance of the FOI-PD controller is studied and compared with those of the IOPID and IOI-PD controller. The observation reveals that the FOI-PD controller outperforms both the IOPID and IOI-PD controller in terms of overshoot and settling time. It has been further observed that the control signal gets improved as the structure moves from the PID to I-PD and integer order to the fractional order. The robustness analysis has also been incorporated to show the effectiveness of the FOI-PD controller.

Closed loop speed control of chopper fed DC motor for industrial drive application

In this paper a comparative transient and robustness analysis of closed loop speed control employing different linear controllers for the same dc motor using 4 quadrant chopper is investigated. The controller configurations can be broadly classified under (i) Integer order PID controller (ii) linear state space observer and (iii) fractional order PID controller. All of them exhibit superior performances, the first one is the conventional controller used in industries but the later two are modern controllers that have rich potential for industry use and have large advantage over the conventional controllers. The closed loop control of chopper fed DC motor is shown with the 1st quadrant operation of chopper circuit.