Dynamic Set-point Research Articles

A Control Simulation Tool for Online Demand Calibration

Developing fast calibration algorithms is an important step towards the online simulation of hydraulic water networks. The ob- jective of this paper is to report a new demand calibration approach by using algorithms from control theory. We propose a multivariable PID control where the control parameters are identified by a system identification approach and the system matrix is decoupled. In this control approach the measured flow variables are regarded as dynamic set-points. The controllers use the demand values as manipulated variables in order to control the flow variables to the measured flow. The concept was applied successfully using a small test-network.

Feedforward ouput-feedback control for a class of exothermic tubular reactors

The problem of regulating the effluent concentration in an open-loop unstable exothermic jacketed reactor is addressed. The coolant temperature must be adjusted according to temperature as well as flow measurements. First, the robust nonlinear feedforward-output feedback stabilizing control problem is addressed with advanced control theory, yielding: (i) solvability conditions with sensor location criterion, and (ii) closed-loop robust stability coupled with simple tuning guidelines. Then, the behavior of the advanced controller is recovered with a PI temperature controller equiped with: (i) antiwindup protection, and (ii) feedforward dynamic setpoint compensation driven by measured (feed temperature and volumetric flow rate) disturbances. The approach is applied to a representative case example through numerical simulations.

Improving energy efficiency via smart building energy management systems: A comparison with policy measures

To foster the transition to more sustainable energy systems, policymakers have been approving measures to improve energy efficiency as well as promoting smart grids. In this setting, building managers are encouraged to adapt their energy operations to real-time market and weather conditions. Yet, most fail to do so as they rely on conventional building energy management systems (BEMS) that have static temperature set points for heating and cooling equipment. In this paper, we investigate how effective policy measures are at improving building-level energy efficiency compared to a smart BEMS with dynamic temperature set points. To this end, we present an integrated optimisation model mimicking the smart BEMS that combines decisions on heating and cooling systems operations with decisions on energy sourcing. Using data from an Austrian and a Spanish building, we find that the smart BEMS results in greater reduction in energy consumption than a conventional BEMS with policy measures.

Fuzzy adaptive proportional-integral-derivative controller with dynamic set-point adjustment for maximum power point tracking in solar photovoltaic system

A novel fuzzy adaptive proportional-integral-derivative (PID) control strategy with online set-point tracking is presented for maximum power point tracking (MPPT) in solar photovoltaic (PV) system in this paper. The range of the membership functions of the fuzzy logic for online PID parameter tuner has been optimized using the relay feedback tuning method. The proposed MPPT controller has been designed with online set-point adjustment approach using current, radiation and temperature sensors. Real-time simulations have been carried out on MATLAB™/dSPACE™ ds1104 Research and Development control board platform for solar PV system with synchronous buck converter and resistive load. Performance of the proposed techniques has been compared with main existing MPPT techniques viz. perturb and observe, incremental conductance, fuzzy logic, neural network and adaptive neuro-fuzzy inference system-based methods of MPPT. Performance of various techniques has been compared based on tracking efficiency, steady state and dynamic behaviour. Experimental results showed the superiority of the proposed method for tracking maximum power point under rapidly varying solar radiations.

A dynamic set point for thermal adaptation requires phospholipase C-mediated regulation of TRPM8 in vivo

The ability to sense and respond to thermal stimuli at varied environmental temperatures is essential for survival in seasonal areas. In this study, we show that mice respond similarly to ramping changes in temperature from a wide range of baseline temperatures. Further investigation suggests that this ability to adapt to different ambient environments is based on rapid adjustments made to a dynamic temperature set point. The adjustment of this set point requires transient receptor potential cation channel, subfamily member 8 (TRPM8), but not transient receptor potential cation channel, subfamily A, member 1 (TRPA1), and is regulated by phospholipase C (PLC) activity. Overall, our findings suggest that temperature response thresholds in mice are dynamic, and that this ability to adapt to environmental temperature seems to mirror the in vitro findings that PLC-mediated hydrolysis of phosphoinositol 4,5-bisphosphate modulates TRPM8 activity and thereby regulates the response thresholds to cold stimuli.

The potential of a confined closed greenhouse in terms of sustainable production, crop growth, yield and valuable plant compounds of tomatoes

A confined closed greenhouse (CGH) was applied to save energy and to investigate how tomatoes respond to specific microclimatic conditions. As such, new dynamic set-points for precise climate control were used in the CGH compared to those applied in a conventional greenhouse. Based on the reduced ventilation frequency in the CGH, the results showed that higher levels of mean temperature, CO 2 concentration and relative humidity were achieved. Although the light interception was increased in the CGH, these changing microclimatic conditions resulted in higher rates of photosynthesis and an associated faster crop growth. This means that the mean plant height was increased by 1.5 m, which was the decisive factor to increase the total yield by 21.4% in relation to that produced in the conventional greenhouse. The new microclimatic environment caused by the CGH promoted the accumulation of primary and secondary plant compounds in tomatoes such as soluble solids (by 9%), lycopene (by 22%), s-carotene (by 21%), phenolics (by 8%) and L-ascorbic acid (by 26%) compared to conventional produced tomatoes. Compared to existing greenhouse systems, the results suggested that a CGH can be used to produce tomatoes in a sustainable way, where the water use and the energy use efficiency can be improved by 71% and 43%, respectively.

Networked Multirate Output Feedback Control for Setpoints Compensation and Its Application to Rougher Flotation Process

This paper investigates the setpoints compensation for a class of complex industrial processes. Plants at the device layer are controlled by the local regulation controllers, and a multirate output feedback control approach for setpoints compensation is proposed such that the local plants can reach the dynamically changed setpoints and the given economic objective can also be tracked via certain economic performance index (EPI). First, a sampled-data multivariable output feedback proportional integral (PI) controller is designed to regulate the performance of local plants. Second, the outputs and control inputs of the local plants at the device layer are sampled at operation layer sampling time to form the EPI. Thus, the multirate problem is solved by a lifting method. Third, the static setpoints are generated by real-time optimization and the dynamic setpoints are calculated by the compensator according to the error between the EPI and objective at each operation layer step. Then, a networked case is studied considering unreliable data transmission described by a stochastic packet dropout model. Finally, a rougher flotation process model is employed to demonstrate the effectiveness of the proposed method.

Heat Transfer Based Scale-Down of Chemical Reactions

Mathematical models of dose controlled reactions based on heat flow data(1, 2) are quite common and well developed; however, such predictions for nondose controlled reactions from heat flow data are difficult, requiring extensive study of the kinetics of multiple chemical transformations as well as physical phenomena such as dissolution and diffusion. Presented here is a new scale-down methodology to directly observe, in the laboratory, a variety of dose controlled and nondose controlled large scale thermal effects. This experiment-based scale-down approach has been derived mathematically from first principles, as well as demonstrated experimentally. This approach limits the heat transfer of the laboratory reactor to the scale equivalent of the intended large scale vessel by dynamic jacket set points based on the ratio of the heat transfer coefficients of lab and plant scale reactors. This allows large scale reaction temperature and other temperature-related effects to be mimicked on small scale while maintaining the time/reaction temperature response profile of the large scale vessel in the laboratory. The result is a method for the direct observation, in the laboratory, of the scale-up effects of changing a wide range of process variables for both dose controlled and non-dose controlled systems. Applications for this methodology could include evaluating the effects of proposed large scale process changes on process safety, product purity, or product physical properties as well as evaluating the effects of failure scenarios.

A PI Controller with Dynamic Set-Point Weighting for Nonlinear Processes

The paper deals with the control of nonlinear processes with 2DOF-PI controllers. A new and practical tuning method, based on recent ideas of immersion and invariance, is proposed for the dynamic adjustment of the set-point weight. The main attractive feature of the proposal is the possibility of assigning a reduced-order linear dynamics for the tracking response beyond the nonlinear characteristics of the process and the amplitude of the set-point changes. From a practical point of view the adjustment is performed by a simple sliding mode regime that accepts a straightforward implementation.

Performance improvement of PI controllers through dynamic set-point weighting

Responses of high-order systems under Ziegler–Nichols tuned PI controllers (ZNPIs) are characterized by excessive oscillation with a large overshoot. Although, a fixed set-point weighting based PI controller (FSWPI) may decrease the overshoot considerably, it fails to reduce the oscillation in the set-point response. Moreover, both FSWPI and ZNPI exhibit equally poor load regulation. Keeping in mind an overall improved performance, we propose an online dynamic set-point weighting technique for ZNPIs. The dynamic set-point weighting factor ( β d ) is heuristically derived from the instantaneous process trend. Performance of the proposed dynamic set-point weighting based PI controller (DSWPI) for various second- and third-order processes including a pH process shows a significant improvement during both the set-point and load disturbance responses over other methods. Stability and robustness of the proposed DSWPI are addressed. Effectiveness of the DSWPI is demonstrated through the real-time implementation on a practical DC position control system.

Potential-Function Based Control of a Microgrid in Islanded and Grid-Connected Modes

This paper introduces the potential-function based method for secondary (as well as tertiary) control of a microgrid, in both islanded and grid-connected modes. A potential function is defined for each controllable unit of the microgrid such that the minimum of the potential function corresponds to the control goal. The dynamic set points are updated, using communication within the microgrid. The proposed potential function method is applied for the secondary voltage control of two microgrids with single and multiple feeders. Both islanded and grid-connected modes are investigated. The studies are conducted in the time-domain, using the PSCAD/EMTDC software environment. The study results demonstrate feasibility of the proposed potential function method and viability of the secondary voltage control method for a microgrid.

DYNAMIC SET POINT WEIGHTED PID CONTROLLER

A new set point weighting technique is proposed to improve the set point response and load rejection characteristics of Ziegler―Nichols tuned PID controller (ZNPID). Instead of a fixed or multi-valued set point weighting factor, here dynamic set point weighting is suggested based on the change of error (Δe) of the controlled variable and normalized dead time (θ) of the process under control. Effectiveness of the proposed scheme is tested on high-order linear and nonlinear dead time processes for both set point change and load disturbances. Performance of the proposed PID controller with dynamic set point weighting (DSWPID) is compared with those of a PID controller with variable set point weighting (VSWPID) reported in the leading literature and ZNPID in terms of several performance indices. The result demonstrates a significantly improved overall performance of DSWPID. The proposed scheme can be easily incorporated in an existing control loop.

STEERING OF FOGGING: CONTROL OF HUMIDITY, TEMPERATURE OR TRANSPIRATION?

Fogging systems are increasingly used to cool greenhouses and prevent water stress. More recently, fogging systems are applied also in relatively low radiation environments (such as The Netherlands), for a better control of product quality than whitewashing and to reduce need for natural ventilation ? thus allowing for higher CO2 concentrations to be maintained in the greenhouse. Most commonly the steering of such systems is done by setting an upper limit to the deficit of specific humidity that, whenever exceeded, triggers the fogging system. In both cases, however, one may wonder whether static and pre-fixed set points are the most effective choice. In the experiment presented in this paper, fogging and venting were controlled with the purpose of steering crop transpiration. The desired transpiration rate was the input of an algorithm that calculated on-line the required humidity and air temperature set points in view of the current weather factors. The set points were then the input of a standard P-controller that calculated vent opening and time of operation of the fogging system. In this paper, the resulting climate and actuator control operations are discussed and compared with a similar greenhouse controlled in a traditional fashion. The study concluded that a desired crop transpiration rate (an all-round indicator of crop well-being) could be used to select dynamic set points for the climate control in a greenhouse equipped with a fogging system.

Advanced control and on-line process optimization in multilayer structures

The paper demonstrates the place, role and mutual interaction of advanced control algorithms and on-line set-point optimization in process control structures. First, a multilayer control structure resulting from a functional decomposition is briefly presented. The role and selected realizations of advanced control algorithms, in particular mostly applied now model predictive control (MPC) ones, at direct control and supervisory constraint control layers is discussed. Then possible solutions to on-line set-point optimization, depending of disturbance dynamics, are presented: dynamic set-point optimization including involved structures based on temporal decomposition, and steady-state set-point optimization for cases with disturbance dynamics both much slower than and comparable with the process dynamics. For the last case, important in industrial practice, different structures of interaction and even integration of MPC and steady-state optimization are discussed. The topics are illustrated by briefly presented examples, selected from given references.

ADVANCED CONTROL AND ON-LINE PROCESS OPTIMIZATION IN MULTILAYER STRUCTURES

The aim of the paper is to present the place, role and mutual interaction of advanced control algorithms and on-line set-point optimization in multilayer process control structures. First, such a structure resulting from a functional decomposition is presented. The role and selected realizations of advanced control algorithms, in particular mostly applied now MPC ones, at direct control and constraint control layers is discussed. Then possible solutions to on-line set-point optimization, depending of disturbance dynamics, are presented: dynamic set-point optimization including involved structures based on temporal decomposition, and steady-state set-point optimization for cases with disturbance dynamics both much slower and comparable with the process dynamics. For the last case, important in industrial practice, different structures of interaction and even integration of MPC and steady-state optimization are discussed. The topics are illustrated by briefly presented examples, selected from given references.

Real-time monitoring and automatic density control of large-scale microalgal cultures using near infrared (NIR) optical density sensors

Signals from near infrared (NIR) light transmittance sensors were used for both real-time monitoring of algal biomass density in growing mass cultures (200 l tubular biofences), and also as feedback in a system that controlled the density of the culture by automatic injection of fresh growth medium. When operated in a semi-continuous production mode between predefined density values, diurnal growth patterns were recorded on-line that provided information on the dynamics of the microalgal cultures with respect to environmental conditions. The bioreactor system was also programmed to operate in constant biomass density mode, thereby maintaining the culture at the optimal population density (OPD), and sustaining high biomass production levels. The system has potential for operating a dynamic density set point for microalgal cultures where the optimal population density varies as a function of ambient growing conditions.

SEDATION OF SIMULATED ICU PATIENTS USING REINFORCEMENT LEARNING BASED CONTROL

The Intensive Care Unit (ICU) is a challenging environment to both patient and caregiver. Continued shortages in staffing increase risk to patients. To evaluate the use of intelligent systems in the improvement of patient care, an intelligent agent was developed to regulate ICU patient sedation. A temporal differencing form of reinforcement learning was used to train the agent in the administration of intravenous propofol in simulated ICU patients. The agent utilized a well-studied pharmacokinetic model to calculate the distribution of drug within the patient. Pharmacodynamics were then estimated for the drug effect. A derivative of the electroencephalograms, the bispectral index, served as the system control variable. The agent demonstrated satisfactory control of the simulated patient's consciousness level in static and dynamic setpoint conditions. The agent demonstrated superior stability and responsiveness when compared to a well-tuned PID controller, the control method of choice in closed-loop sedation control literature.

A gentle introduction to the dynamic set-point model of human postural control during perturbed stance

Three models of increasing complexity to capture three observed phenomena of postural control are described. The first-order model mimics the increase in standard deviation of sway with eyes closed, but none of the other phenomena. The damped spring model captures both the increase in standard deviation of sway with eyes closed and the change from phase-lag to phase-lead with increasing frequency of oscillation of a visual surround. The final model, the dynamic set-point model, extends the damped spring model by a degree of freedom that reflects the observed slow drift in baseline. Under the assumption of a strong coupling to positional information, the dynamic set-point model predicts a dependence between natural frequency and position coupling constant of the damped spring model. It is shown that this prediction is borne out in data obtained from haptically perturbed stance but not in data obtained from visually perturbed stance.

Performance of different types of controllers in tracking optimal temperature profiles in batch reactors

Performance of three different types of controllers in tracking the optimal reactor temperature profiles in batch reactor is considered hear. A complex exothermic batch reaction scheme is used for this purpose. The optimal reactor temperature profiles are obtained by solving optimal control problems off-line. Dual mode (DM) control with propotional-integral (PI) and proportional-integral-derivative (PID) and generic model control (GMC) algorithms are used to design the controllers to track the optimal temperature profiles (dynamic set points). Neutral network technique is used as the on-line estimator the amount of heat released by the chemical reaction within th GMC algorithm. The GMC controller coupled with a neural network based heat-release estimator is found to be more effective and robust than the PI and PID controllers in tracking the optimal temperature profiles to obtain the desired products on target.

Why do we eat?

The urge to eat is the main apparent issue underlying obesity. Although vast information regarding the physiology and psychology of eating behavior has been accumulated, a comprehensive concept is still missing. The model presented suggests that feeding behavior is ultimately controlled by the rate of work performed in the muscle or in an as yet unidentified compartment. It suggests a novel approach of a dynamic set-point weight and explains why diets usually fail to resolve the disorder while physical activity is beneficial in losing excess weight. Obesity is presented as a syndrome of high efficiency of energy conversion resulting in a variety of symptoms of which over-weight is only the more apparent. Other symptoms manifested in the predisposition to a variety of illnesses constitute the main health problem and can prevail in the obese subject even without the excess weight. Therefore, resolution of the disorder requires developing approaches which directly affect the efficiency of energy conversion.