Improved generalized predictive controllers for decentralized control

In general, decentralized control refers to the multivariable control of a nxn square process using n SISO (Single-Input Single-Output) control loops designed for the diagonal elements. Under consideration is an equivalent transfer function method for decentralized controller design proposed by Cai et.al. known as the (Relative Normalized Gain Array) RNGA-based decentralized PID design method. The design procedure involves loop pairing using the RNGA, RGA (Relative Gain Array) and NI (Niederlinski Index) analysis, deriving the RNGA-based equivalent transfer functions (ETFs) of the n diagonal elements and using them to design PID controllers for the n loops. The objective of this work was to use the RNGA-based ETFs to design GPCs (Generalized Predictive Controllers) in place of the standard PID in order to exploit some of the inherent features of the GPC such as constraints handling. The GPC or Generalized Predictive Controller is one member of the family of long range predictive controllers (or Model Predictive Controllers) which was proposed in 1979 by Clarke et.al. to handle unstable, non minimum phase processes. It differs from other varieties of Model Predictive Controllers (MPC) in that it uses the CARIMA (Controlled Auto-Regressive Integrated Moving Average) model of the process to derive its output predictions. Simulation studies proved that the SISO unconstrained GPC was unsuitable for direct application to a decentralized structure. Modifications were needed on two fronts: the parameter tuning and disturbance model of the GPC (for Robustness). Research in the tuning direction led to the development of two novel tuning methods: The first is the N*tuning method which is applicable to the conventional GPC for the control of stable and unstable FOPTD (First Order Plus Time Delay) processes. The second is the 2GPC method which is an extension of the general Parallel Control structure (PCS) to predictive control. The 2GPC algorithm is offered as a variant of the conventional GPC. It consists of two GPCs working in tandem; one governs the set-point tracking response and the other controls the disturbance rejection response. However, the 2GPC is formulated as a single optimization problem integrating system constraints. The extent to which the 2GPC algorithm can perform Transparent Online Parameter Tuning (TOPT) is explained. (Transparent Online Parameter Tuning (TOPT) is the facility of the controller to allow the user to independently manipulate online the three most important loop performance attributes - Set-point Tracking Performance, Disturbance Rejection Performance and Robustness - with the use of three seperate parameters). It is shown through derivations that the extent to which the 2GPC method can perform TOPT is maintained even under mismatch conditions. Most importantly, it is also proved that the 2GPC control loop, by utilization of its TOPT feature, can have greater Robustness than a conventional GPC loop. On the disturbance model front, the structure of the GPC was first analysed. The structure of the conventional unconstrained SISO GPC can be split into a primary loop with setpoint filter and an optimal predictor. The filter transfer function of this optimal predictor is inversely proportional to the loop robustness and is also the only transfer funciton in the GPC loop that is a function of the process delay. For higher delays, the filter is such that the Robustness deteriorates. But it is the optimal predictor's filter that is responsible for one of the GPC's most attractive features - guaranteed internal stability even in the case of open loop unstable processes. At the loss of this feature, in order to improve disturbance rejection/robustness, there are variants of the GPC that utilize modified filters, such as the SPGPC (Smith Predictor based GPC). A new GPC is proposed in this work called the CDGPC (or GPC with Constant Disturbance Model). This effectively makes it equivalent to the popular DMC (or Dynamic Matrix Controller) with the exception that the former uses the transfer function model for predictions and can thus work for intergrator systems as well. It is proved that the CDGPC has greater robustness than the conventional GPC and the SPGPC. The CDGPC together with N*tuning method generate the required level of robustness and precision in tuning that enables it to be applied to decentralized control. The CDGPC with N*tuning is designed for the RNGA-based ETFs of the diagonal elements of the MIMO system. Closed loop responses of 2x2 MIMO systems were studied in simulation and were compared to the performance of RNGA-based PID controllers.DOCTOR OF PHILOSOPHY (EEE

Laser scan matching for mobile robot localization

This masters project deals with mobile robot localization - making the robot aware of its position with respect to its environment or the global frame. Odome - try from the robot does give us this position information directly, but it is always erroneous, with the errors also adding up over time. There are several ways to correct the errors in the odometry awl thereby achieve robust localization. One of those techniques is Laser Scan Matching and it is the focus of this project. The Laser Scan Matching algorithm processes two laser scans taken from a mobile robot’s Laser Range Finder sensor to obtain information about the translation and rotation executed by the robot, in the time between the two scans. Further, the algorithm has several distinct steps that are executed in sequence, in order to obtain these translation and orientation estimates. This major portion of this project involved the studying, implementing and testing of the Laser Scan Matching algorithm in matlab, using laser scans front both simulations and from actual laser scanners. By scan-matching consecutive scans from a mobile robot’s laser seamier, we can obtain estimates for the translations and rotations made by the robot all through its run, and thereby estimate its path. This has also been explored in this project. The estimation of the robot path using the laser scan matching algorithm is localization and is what gave this report the title “Laser Scan Matching for Mobile Robot Localization”.Master of Science (Computer Control and Automation

A hybrid dynamic modeling of active chilled beam terminal unit

This paper proposes a hybrid dynamic model of active chilled beam (ACB) terminal unit. The model encapsulates mechanical and thermal aspects of the confined air jet and the cooling coil contained in the terminal unit and could be divided into two sub-models respectively. The models for the primary air, secondary air and mixing of them are together taken as the confined air jet sub-model. Another sub-model is the heat transfer description of the cooling coil. The model is kept simple and practical, avoiding sophisticated jet flow theories as well as heat transfer theories. Thus, in deriving the model using first principles and estimating it experimentally, a reasonable compromise is made between capturing exact underlying physics and suitability for engineering applications. Supported by experimental results from a pilot plant, unknown model parameters are identified by either a linear or nonlinear least-squares method. It is shown that static and dynamic performances of the model are satisfied, which reflect the effectiveness of this hybrid modeling technique as well. The model developed in this work is expected to have wide control and optimization applications.ASTAR (Agency for Sci., Tech. and Research, S’pore)Accepted versio

Smart lighting system using ANN-IMC for personalized lighting control and daylight harvesting

Lighting contributes a significant portion to the overall energy consumption in an office building. It is thus important to reduce the energy consumption of lighting systems especially for Net Zero Energy Buildings (NZEB). Maximizing daylight harvesting can significantly increase the energy savings. With increase in demand for satisfying occupant preferences in visual comfort, the need for personalized lighting in the office space is also rising. In this paper, a novel lighting control system for Net Zero Energy Buildings (NZEB) is proposed which models the lighting system using Artificial Neural Network (ANN) and utilizes this model with the Internal Model Control (IMC) principle for controller design. Modeling the lighting system using ANN reduces the challenge of modeling a large and complex system with inherent process variability without the need to analyze extensive data-sets. The proposed ANN-IMC controller uses feedback from sensors on the task table to maintain desired illuminance, is easy to tune with just one parameter and is robust to process variability. The proposed control design is applicable to square systems where the number of lights and number of sensors are equal. However, the proposed architecture can also be extended for controlling other lighting accessories such as roller blinds. The performance of the proposed lighting control system to harvest the daylight effectively is demonstrated using both simulation results and an experimental setup in test-bed environment. The versatility of the proposed system will allow an operator to deploy personalized lighting in an office space.NRF (Natl Research Foundation, S’pore)Accepted versio

Energy savings and thermal comfort in a zero energy office building with fans in Singapore

Elevated air movement produced by fans can offset air-conditioning energy requirements by allowing temperature setpoints to be raised without compromising thermal comfort. These advantages are even greater in hot and humid climates that inherently have large and sustained indoor cooling requirements. Few studies have assessed the in-situ benefits of fans in actual buildings. We installed ceiling and desk fans into a Zero Energy office building (675 m2) in Singapore. Across an 11-week period, 35 occupants alternated between two conditions (no fan vs. fan): 24 °C setpoint with fans off, and 26.5 °C setpoint with fans on. When the temperature setpoint was raised and elevated air movement was provided, a 32% energy reduction was obtained. The energy savings accrued without any negative impacts occurring on thermal satisfaction. Overcooling caused by thermal preference to slightly warmer and warmer conditions was substantially reduced from 33 to 9%. No changes in perceived air-staleness or self-reported alertness and ability to concentrate occurred either, indicating parity across the no fan and fan conditions. Although occupants primarily relied on ceiling fans at the 26.5 °C setpoint, they were by default on at the beginning of each day, giving less incentive to use the desk fans. Our study took place in a high-performance Zero Energy building, whereby thermal dissatisfaction was already low (7%). Therefore, notable changes did not occur, but significant improvements to thermal comfort could still occur in buildings that are unable to maintain high levels of thermal satisfaction