MPC

A strategy for adaptive control and energetic optimization of aerobic fermentors was implemented, with both air flow and agitation speed as manipulated variables. This strategy is separable in its components: control, optimization, estimation. We optimized parameter’s estimation (from the usual KLa correlation) using sinusoidal excitation of air flow and agitation speed. We have implemented parameter’s estimation trough recursive least squares algorithm with forgetting factor. We carried separate essays on control, optimization and estimation algorithms. We carried our essays using an original computational simulation environment, with noise and delay generating facilities for data sampling and filtering.

Our results show the convergence and robustness of the estimation algorithm used, improved with use of both forgetting factor and KLa dead-band facilities. Control algorithm used in our work compares favorably with PID using the integrated area criteria for deviation between oxygen molarity and critical molarity (set point). Optimization algorithm clearly reduces energetic consumption, respecting critical molarity. Integration of control, optimization and adaptive algorithms was implemented, but future work is needed for stability. Methods were defined and implemented for stability improvement. We have implemented data acquisition and computer manipulation of air flow and agitation speed for actual fermentors.

The study used water level control of drum boiler system Internal Model Control (IMC) with PID controller. Liquid Level System has various configurations to control the water level system such as: IMC and Model Predictive Controller. In this paper IMC has been designed and the result has been compared with, model predictive control (MPC) for all these configurations of water level control strategy and responses get compared. The IMC-PID controller exhibits good way to tackle set-point, due to not proper compensation for disturbance externally, outcome frequently not good for systems having a small time-delay /time-constant. Yes, other applications of system i.e. the disturbance rejecting criteria for system having instability is having more weight age than to track set-point required. That’s why, here an IMC based filter, an alternative approach to design an IMC based PID control which may result in tracking set-point for a system exhibiting instability and performance comparison of IMC controller with other controller to control Water Level.

Impedance network inverters are a good alternative for voltage-source and current-source inverters. The shoot-through solution and the boosting capability of such converters make them an excellent solution for photovoltaic (PV) application. Furthermore, energy storage integration in these inverters does not require any additional components in the converter; indeed, a battery can be directly connected in parallel with one of the capacitors of the Z-or quasi Z-network. However, for an optimal control of these converters, complex control and modulation strategies are required. Model Predictive Control (MPC) provides high control performance at the expense of the computational effort. In this paper, a low computational control method where both MPC and proportional resonant (PR) controller are combined, is proposed. This makes the proposed controller perform two iterations only instead of iterating for all the available switching states. As shown in the obtained results, the proposed controller conserves the high performance of the conventional MPC with 50% less computational burden.

In cascaded multilevel quasi Z-source inverters (CM-qZSI), the intermittent and stochastic fluctuation of the solar power injected to the grid can be smoothened by connecting a battery in parallel with one of the qZ network capacitors. However, since CM-qZSI is a special case of the single phase qZSI, it suffers from some of its demerits, such as double line-frequency ripple. This affects the battery current, the second qZ network's inductor current, and the qZ network's capacitor voltages. This issue can be alleviated either by increasing the size of the passive elements or by developing advanced control schemes, such as MPC. However, MPC is computationally intensive, especially in multilevel converters. In this paper, a low computational control method for PV-fed battery assisted CM-qZSI is proposed, where proportional-resonant (PR) controller is introduced in the control algorithm. The prediction is performed only for the dc side of the converter; hence, the algorithm iterates for the shoot through and zero states only. As shown in the obtained results, by using the proposed method, the double line-frequency ripple can be significantly reduced, while a less computational effort compared to the conventional MPC is needed.

This paper proposes a comparative study of a modeless controller design and a Model Predictive controller strategy (MPC) for a linear process regarding their performance in real time. The system is preferably taken as a level control process with a constant load and both the controllers are developed and implemented in LabVIEW software environment and interfaced to the process using an arduino Mega2560. The defuzzification method chosen for the Fuzzy controller is centre of area. The MPC controller is designed using the approximated first order model from a step response and is verified by finding resistance to the outflow. The controlling of the level is done using a feed pump as actuator. The performance criteria like integral absolute error (IAE), integral square error (ISE), rise time, peak time and percentage overshoot are evaluated for both the control strategies and compared.

Most of the controllers that were proposed to control the pneumatic positioning system did not consider the limitations or constraints of the system in their algorithms. Non-compliance with the prescribed system constraints may damage the pneumatic components and adversely affect its positioning accuracy, especially when the system is controlled in real-time environment. Model predictive controller (MPC) is one of the predictive controllers that is able to consider the constraint of the system in its algorithm. Therefore, constrained MPC (CMPC) was proposed in this study to improve the accuracy of pneumatic positioning system while considering the constraints of the system. The mathematical model of pneumatic system was determined by system identification technique and the control signal to the valves were considered as the constraints of the pneumatic system when developing the controller. In order to verify the accuracy and reliability of CMPC, repetitive experiments on the CMPC strategy was implemented. The existing predictive controller, that was used to control the pneumatic system such as predictive functional control (PFC), was also compared. The experimental results revealed that CMPC effectively improved the position accuracy of the pneumatic system compared to PFC strategy. However, CMPC not capable to provide a fast response as PFC.

A novel wideband microstrip patch antenna with nonuniform transmission line feed is presented using model predictive control. Nonlinear model predictive control (NMPC) is used to achieve a nonuniform transmission line that matches with the microstrip patch antenna. The transmission line is extended using cosine expansion with the impedance differential equation then being used as the dynamic NMPC equation to find the unknown coefficients of that cosine expansion. The transmission line is designed such that the impedance of the input port matches the impedance of the microstrip antenna at the resonance frequency and its adjacent frequencies. The proposed antenna's impedance is 5.15-5.85 GHz. In this bandwidth, the radiation pattern is stable; the cross polarization and back lobe are −30 dB and −20 dB, respectively. The error in the impedance bandwidth is about 4.2%. The simulation and measurement results are considered satisfactory.

The control of liquid is an essential process in process industries. But it is difficult to control a non-linear process. Conical tanks are being used in many industries due to its non-linear shape. So, level control of conical tank presents a challenging task due to its non-linearity and constantly changing cross-section. The aim of this paper is to provide suitable controllers for maintaining the level with flow as input parameter. The different controllers includes Proportional Integral Derivative controller (PID), Model Predictive Controller (MPC) and Internal Model Controller (IMC) which are simulated in Matlab environment.

Impedance network inverters are a good alternative for voltage-source and current-source inverters. The shoot-through solution and the boosting capability of such converters make them an excellent solution for photovoltaic (PV)application. Furthermore, energy storage integration in these inverters does not require any additional components in the converter; indeed, a battery can be directly connected in parallel with one of the capacitors of the Z- or quasi Z-network. However, for an optimal control of these converters, complex control and modulation strategies are required. Model Predictive Control (MPC)provides high control performance at the expense of the computational effort. In this paper, a low computational control method where both MPC and proportional resonant (PR)controller are combined, is proposed. This makes the proposed controller perform two iterations only instead of iterating for all the available switching states. As shown in the obtained results, the proposed con...

This paper proposes a comparative study of a modeless controller design and a Model Predictive controller strategy (MPC) for a linear process regarding their performance in real time. The system is preferably taken as a level control process with a constant load and both the controllers are developed and implemented in LabVIEW software environment and interfaced to the process using an arduino Mega2560. The defuzzification method chosen for the Fuzzy controller is centre of area. The MPC controller is designed using the approximated first order model from a step response and is verified by finding resistance to the outflow. The controlling of the level is done using a feed pump as actuator. The performance criteria like integral absolute error (IAE), integral square error (ISE), rise time, peak time and percentage overshoot are evaluated for both the control strategies and compared.

Modern process control is based on process modeling. Advanced process control (APC), real time optimization (RTO), process monitoring, operator training simulation, abnormal situation management (ASM) and fault detection and isolation (FDI) are all based on some kind of process modeling. Models are a very effective way to embed “knowledge” in process automation, which has increased its “autonomy” level, growing more and more from “reactive” to “proactive” [1], [2].

Les convertisseurs multicellulaires DC-DC sont utilisés dans de nombreuses applications et de nombreux systèmes électriques. Ils présentent un intérêt particulier pour des applications spécifiques liées aux énergies renouvelables et aux Microgrids. Leur principal avantage provient de leur capacité intrinsèque à réduire les ondulations liées au découpage des grandeurs électriques en entrée et en sortie du système de conversion. Cette propriété intéressante au niveau système peut être étendue au fonctionnement interne du convertisseur en adjoignant à ce dernier un élément de filtrage par inductances couplées magnétiquement. Ce composant permet d’étendre les propriétés externes de réduction des ondulations au fonctionnement de chaque cellule du convertisseur. Il permet également d’augmenter la dynamique propre du système de conversion. Ces propriétés permettent de réduire significativement le niveau et le volume de filtrage en entrée et sortie du convertisseur et donc d’augmenter de ma...

In this paper we investigate the design of realizability interpretations for program development in extensions to the constructive and intensional set theory TK [Henson 88]. These realizability interpretations express the idea that a program meets a specification. We explore a ...