Setpoint Modification Research Articles

Hardware-assisted detection of firmware attacks in inverter-based cyberphysical microgrids

The electric grid modernization effort relies on the extensive deployment of microgrid (MG) systems. MGs integrate renewable resources and energy storage systems, allowing to generate economic and zero-carbon footprint electricity, deliver sustainable energy to communities using local energy resources, and enhance grid resilience. MGs as cyberphysical systems include interconnected devices that measure, control, and actuate energy resources and loads. For optimal operation, cyberphysical MGs regulate the onsite energy generation through support functions enabled by smart inverters. Smart inverters, being consumer electronic firmware-based devices, are susceptible to increasing security threats. If inverters are maliciously controlled, they can significantly disrupt MG operation and electricity delivery as well as impact the grid stability. In this paper, we demonstrate the impact of denial-of-service (DoS) as well as controller and setpoint modification attacks on a simulated MG system. Furthermore, we employ custom-built hardware performance counters (HPCs) as design-for-security (DfS) primitives to detect malicious firmware modifications on MG inverters. The proposed HPCs measure periodically the order of various instruction types within the MG inverter’s firmware code. Our experiments illustrate that the firmware modifications are successfully identified by our custom-built HPCs utilizing various machine learning-based classifiers.

A fuzzy-logic-based pressure setpoint modification method for pressurized water reactor pressurizers

For pressurized water reactors, the pressurizer pressure is expected to be maintained constant to limit adverse impacts on the reactor due to pressure variations. To achieve this, a constant pressure setpoint is usually adopted in the pressurizer pressure control system. But it may not guarantee satisfactory pressure control performances especially under severe transient conditions. A feasible solution may be adjusting the pressure setpoint during transient processes and then restoring it to the initial value. For this purpose, the paper proposes a fuzzy-logic-based pressure setpoint modification (FPSM) method for pressurizers. A simulation platform was developed in MATLAB/Simulink implementing a nonequilibrium three-region pressurizer model, the pressure and waterlevel control systems and the FPSM system. Simulation studies of the AP1000 pressurizer during typical load change transients were performed, and responses of the pressurizer implementing the FPSM system are compared with those employing constant pressure setpoint to demonstrate feasibility and effectiveness of the system.

Delivery-Oriented Hierarchical Predictive Control of an Irrigation Canal: Event-Driven Versus Time-Driven Approaches

In this paper, we present the concept of a hierarchical predictive controller used for irrigation canals. The motivation behind this paper is the need in the field of irrigation to deliver water to farmers fast, but with minimal resources involved, as the communication links in the field are not dependable in practice. In response to such a control problem, we propose a hierarchical controller: the lower control layer is formed by decentralized proportional integral (PI) controllers and the higher control layer is constituted by a centralized predictive controller, the purpose of which is to control the inflow to the canal and, importantly, to coordinate the local controllers by modifying their setpoints. Having in mind the restrictions on the available communication infrastructure and the control equipment already present, the scheme is designed to be event driven, i.e., activated when there are either delivery requests or non-delivery-related events of any sort, requiring special care on top of the control provided by the PI controllers. We also study a time-driven formulation with an additional postprocessing step to avoid excessive negligible setpoint modifications. We compare the event-driven formulation and the time-driven formulation theoretically as well as by means of a simulation study for the West-M irrigation canal in Phoenix, Arizona, illustrating the findings of this paper. It is shown that the event-driven controller is able to provide a good balance between the control performance and the required update frequency of the control settings.

Risk-based warning system design methodology for multimode processes

Complex chemical processes usually operate at multiple operating modes, resulting from various factors, such as changes in market demand, set point modifications, and feedstock changes. It is difficult to monitor a multimode process without generating significant number of false alarms. In this paper, a risk-based alarm system design methodology is proposed to monitor multimode processes. The methodology comprises of three main steps: i) analysis of operating data using Gaussian mixture model, ii) identification of independent operating modes (e.g. set points, virtual transient state), and iii) probabilistic model to assess risk and activation of appropriate warning. A continuous stirred tank reactor with model predictive control system is used to demonstrate the effectiveness of the proposed method.

Experimental validation of PID based cascade control system through SCADA–PLC–OPC and internet architectures

The paper presents the experimental validation procedure of a simple cascade control system through number of architectures, such as SCADA, PLC, OPC and internet. The performance and effectiveness of individual architecture is evaluated on the basis of data rate, rise time, peak time and settling time. In this study, PID is implemented on Micrologix-1200 PLC and RSView-32 SCADA has been used with RSLinx communication software. The PLC–SCADA control loop is implemented with the functionalities such as, real time data analysis, set point modifications, automatic report generation and integration of data with MS-Excel and MS-Access. The enhancement in project data analysis is effectively done through the integration of PLC with Labview. The remote monitoring and control of process parameters is done using NET-ENI. The obtained result proved that the conventional SCADA based control system can be enhanced further more with PLC as well as NI-OPC server significantly.

PI-Fuzzy controllers for integral plants to ensure robust stability

New PI-fuzzy controllers comprising Takagi–Sugeno and Mamdani fuzzy systems to control a class of integral plants specific to servo systems are proposed in this paper. Linear PI controllers are designed in the first phase. They are tuned using the Extended Symmetrical Optimum method to ensure the desired overshoot and settling time with respect to step setpoint modifications and three types of load disturbance inputs. This type of PI controller design guarantees robust stability of the closed-loop system in response to parametric variations in a controlled plant. Following this, based on the results from the linear case and the modal equivalence principle, an original development method for PI-fuzzy controllers is proposed. Some experimental results are included to illustrate the effectiveness of the design process.

Supervisory expert control for ball mill grinding circuits

Stable control of particle size in ball mill grinding circuits is of great importance for the recovery of the valuable minerals, and the maximization of mill capacity is another main consideration in concentration plants. A supervisory expert control strategy is proposed to control product particle size and to improve fresh ore feed tonnage in grinding circuits. Expert control in supervisory level is developed to optimize the set–points for controllers in regulatory level. Mill solid concentration variable–ratio control, sump dilution water flowrate single–loop control and sump level loose control are carried out in regulatory level to reach the control targets. While the set–point modification by expert control for dilution water controller demonstrates good dynamic performance, the set–point adjustment for feed rate controller ensures a long-term stableness of particle size even ore hardness has changed. An increase of 10% in feed tonnage was achieved relative to other grinding circuits of similar capacity, running in parallel. More than four year’s operation demonstrates the control strategy’s practicality and reliability.

A methodology for on-line setpoint modification for batch reactor control in the presence of modeling error

Batch and semi-batch reactors are usually highly nonlinear and involve complex reaction mechanisms. Often, the lack of rapid direct or indirect measurements of the properties to be controlled makes the process control task very difficult. It is the usual practice to follow the prespecified setpoint profiles for process variables for which measurements are available, e.g., temperature, in order to obtain desired product properties. Model error can be the cause of poor performance when these setpoint profiles based on a model are implemented on the actual plant. This paper formulates a state estimation model based algorithm for on-line modification of setpoint profiles utilizing infrequent and delayed measurement information of the properties to be controlled, with the goal of obtaining the desired values of the properties in the minimum batch time. The algorithm modifies the setpoint profile for the remainder of the batch after every such measurement by making one step in the right direction instead of attempting to find a completely new optimal profile. This results in robustness with respect to model error and allows improvement even with infrequent product property measurements. The implementation of the setpoint profiles is made via real-time observer based nonlinear quadratic dynamic matrix control, which has been studied extensively in the literature. The modest additional on-line computational requirements of the proposed method offer promise for the practical on-line implementation. The effectiveness of the algorithm is demonstrated with simulations for bulk polymerization of styrene.

Fuzzy-PID hybrid control: Automatic rule generation using genetic algorithms

This paper demonstrates that the genetic algorithms can be used effectively for generating fuzzy rules in fuzzy-PID hybrid control structures. While a number of fuzzy-PID hybrid controllers are considered in the context of tuning of the PID controllers, a general view is provided that they are the special cases of either the set-point modification or the gain modification. Simulation results reveal that genetic algorithms are effective tools to search for optimal or near optimal fuzzy rules. Along with this, they also suggest that there is a real need to develop genetic algorithms which are more tractable for fuzzy rule generation and to study theoretical questions related to the hybrid control structure.