Su Ki Ooi

Control of Large-Scale Irrigation Networks

Irrigation networks of open-water channels are used throughout the world to support agricultural activity. By and large, these networks are managed in open loop. To achieve closed-loop water distribution management, it is necessary to augment these civil engineering systems with an appropriate information infrastructure-sensors, actuators, information processing, and communication resources. Recent pilot projects in Australia demonstrate the significant potential of closed-loop management, which can yield a significant improvement in the quality of service, while achieving improved water distribution efficiency. This paper focuses on the modelling and closed-loop control of open-water channels from the perspective of large-scale irrigation network management. Several feedback information structures are discussed and the key design tradeoffs identified

Systems engineering for irrigation systems: Successes and challenges

In Australia, gravity fed irrigation systems are critical infrastructure essential to agricultural production and export. By supplementing these large scale civil engineering systems with an appropriate information infrastructure, sensors, actuators and a communication network it is feasible to use systems engineering ideas to improve the exploitation of the irrigation system. This paper reports how classical ideas from system identification and control can be used to automate irrigation systems to deliver a near on-demand water supply with vastly improved overall distribution efficiency.

Closed loop identification of an irrigation channel

We consider the closed loop identification of an irrigation channel. A first order nonlinear model of the water level is used, and previous work by Weyer (2000) has shown that this model gives a good description of the dynamics. Earlier, such models were obtained using open loop system identification which caused disruptions to the normal operations of the irrigation channel. These disruptions can be reduced by using closed loop identification. The gates in the irrigation channel are controlled using feedback from water levels, and the excitations are provided by set point changes. Only relatively small set point changes and short experiment times are needed in order to obtain a reliable model. The obtained models are validated against data sets with large variations in flow, and there is very good agreement between the simulated model output and the observed water levels. Hence, models of irrigation channels can be obtained using closed loop identification which causes only minor disruptions to the normal operation of the channel.

Irrigation networks: a systems engineering approach

Irrigation systems are critical infrastructure for the worlds food supply. Irrigation efficiency plays an important role in the sustainable utilisation of the worlds fresh water reserves. It is argued that systems engineering principles can assist to realize the goal of maximising the water efficiency of an irrigation network whilst maintaining quality of service. In approaching this resource management problem interesting open research questions in the field of systems engineering are illustrated.

Modelling of Rivers for Control Design

Agriculture is the world wide biggest consumer of water. However, a large portion of the water is wasted due to inefficient distribution from lakes and reservoirs via rivers to farms. More efficient water distribution can be achieved with the help of improved control and decision support systems, but in order to design such systems, river models are required. Traditionally, the Saint Venant equations which are partial differential equations, have been used for modelling rivers. They are however difficult to use for control design and thus, simpler alternative models are sought. In this paper, system identification techniques are used to obtain models which are useful for control design. We show through experimental validation and actual control design that simple time-delay and integrator-delay models are sufficient for control design.

System Identification and Control of the Broken River

In this paper, control system designs are proposed for the Broken River in Victoria, Australia. The aim of the control system is to improve water resource management and operation for the benefit of irrigators and the environment. Both centralized and decentralized control schemes are considered. The decentralized scheme consists of a number of PI and I controllers, while the centralized scheme is a model predictive controller. The controllers are designed based on simple models obtained using system identification methods. In a realistic simulation scenario, the control systems compared very favorably with current manual operation offering increased operational flexibility with a significant potential for substantial water savings, improved level of service to irrigators, and improved environmental benefits.

Model Predictive Control for Real-Time Irrigation Scheduling

Abstract Irrigation underpins agricultural productivity. The purpose of irrigation is to match water supply to crop water demand. The effectiveness of irrigation depends on the quality of the timing and duration of watering events, also called irrigation scheduling. Most farmers use heuristic rules to determine irrigation events. This often leads to over-watering which results in lower crop yields and wasted water. By acquiring good estimates of a plants water demand and local weather, it is possible to use optimization theory to compute an irrigation schedule that matches supply and demand thereby improving crop yields. Previous work has focused on scheduling irrigation over long time frames such as seasonal water allocations. Real-time irrigation scheduling, e.g. hourly or daily, has received little attention. Farmers rely on heuristic approaches implemented using simple spreadsheet tools to help them in this task. This approach cannot deal effectively with operational constraints and thereby results in poor performance. In this paper we develop a Model Predictive Control framework for real-time irrigation scheduling. The proposed formulation can take into account common operational constraints, including limitations on water availability as well as practical limits on the maximum or minimum amount of water that should be applied. We use measured climate data coupled with a simulation model to evaluate the proposed algorithm.

Non-asymptotic quality assessment of generalised FIR models with periodic inputs

In any real-life identification problem, only a finite number of data points is available. On the other hand, almost all results in stochastic identification pertain to asymptotic properties, that is they tell us what happens when the number of data points tends to infinity. In this paper we consider the problem of assessing the quality of the estimates identified from a finite number of data points. We focus on least squares identification of generalised FIR models and develop a method to produce a bound on the uncertainty in the parameter estimate. The method is data driven and based on tests involving permuted data sets. Moreover, it does not require that the true system is in the model class.

Modelling of river for control design

Farming consumes a large amount of water and a large portion of that water is wasted through inefficient distribution from rivers to farms. More efficient water distribution can be achieved with better control and decision support systems. In order to design such systems, river models are required. Traditionally, the Saint Venant equations which are partial differential equations, have been used for modelling rivers. They are however more difficult to use for control design and thus, simpler alternative models are sought. In this paper, system identification techniques are used to obtain models which are simple and useful for control design. We show through experimental validation that very simple time delay models are sufficient for control design. Controllers designed using the simple time delay models showed good performance in a simulation example.

A Systems Engineering Approach to Viticulture On-Farm Irrigation

Abstract Water resources management presents an important research topic, because our planet is facing a serious water crisis. About 70% of all fresh water usage goes towards agriculture. Moreover, low water application efficiency are well reported in the literature. Improving on-farm irrigation efficiency can make a substantial contribution to a more sustainable utilization of the worlds fresh water resources. It is argued that systems engineering principles can assist to realize the goal of improving water efficiency or produce quality in on-farm irrigation whilst maintaining productivity and quality of service. In approaching this resource management problem, wireless sensor network technologies and automation ideas are combined to improve economic productivity in dairy, horticulture and viticulture industries in such a way as to support continued growth in these major food industries in the face of a competitive water market. This paper reports the early progress of the project on smart irrigation system for viticulture and initial attempt in modeling the viticulture soil-water dynamics is briefly discussed. The results obtained are encouraging indicating that water automation is a promising technology.