Real time optimization

Abstract. This paper presents a Real Time Optimization (RTO) system to optimize a simulated industrial semi-autogenous mill (SAG) using genetic algorithms (GA). For the design of the RTO we used both a validated first principles steady state model adapted on-line and a ...

This paper presents the status and research results of the "Bonten-Maru" humanoid robot project. The main contributions of this project are on CORBA based control of humanoid robot, real time optimal gait generation, control of humanoid robot in a long distance using teleoperation system, operation of humanoid robot in emergency environments, and various humanoid robot motions. In order to verify

Real time optimization of drilling parameters during drilling operations aims to optimize weight on bit, bit rotation speed for obtaining maximum drilling rate as well as minimizing the drilling cost. The process is formation specific. A Statistical method namely multiple linear regression technique is used for the drilling optimization methodology. An extensive literature survey on drilling optimization was conducted for this research study. A model is developed for this purpose using actual field data collected through modern well monitoring and data recording systems, which will be predicting the rate of drilling penetration as a function of available parameters. The rate of penetration general equation is optimized for effective functions at each data point. In order to optimize the parameters in the field, a computer network is required to be developed. The computer network will keep the piped data directly from the data source, and continuously be collecting the new data to be...

The applications of the crystallization technique in the pharmaceutical industry as a purification and separation process for the isolation and synthesis of pure active pharmaceutical ingredients (API), co-crystals, controlled release pulmonary drug delivery, and separation of chiral isomers are briefly discussed using a few case studies. The effect of process variables and solvent on the polymorphism and morphology of stavudine

ABSTRACT The paper proposes the use of ultracapacitor storage device in order to support the mismatch between the available PV source power and microgrid load requirement. A realistic simulation scheme was implemented to evaluate the hybrid power system behaviour under varying microgrid load requirements. The operating performance were observed in steady state and transient conditions. The action of the ultracapacitor was pointed out, while the PV source operated at the maximum power point. Some discussions about the behaviour of the components and system operating characteristics were reported. The growing trend in both energy market deregulation and environmental preservation is forcing studies and applications of Distributed Generation (DG). DG, connected to local loads and distribution grids, is an extremely interesting issue. It offers the opportunity of constructing smart- and micro-grids, which are emerging as an integral feature of the future power systems. Microgrids are clusters of loads and micro sources operating as a single controllable power system. Microgrids can operate in parallel with the grid, as an autonomous power island, or in transition between grid- connected mode and islanded mode of operation. In the non-autonomous mode, the microgrid produces power while interconnected to the utility system. In the autonomous mode, the microgrid serves its electrical load without drawing power from the distribution utility. When possible, micro generation units are dispatched on the minimization of variable costs for service providing. So, real-time optimization in microgrids is performed through frequent adjustments of generator outputs to

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.

A methodology and model have been developed for the real-time optimal flood operation of river-reservoir systems. This methodology is based upon combining a nonlinear programming model with a flood-routing simulation model within an optimal control framework. The generalized reduced gradient code GRG2 is used to perform the nonlinear optimization and the simulator is the US National Wheather Service DWOPER code. Application of the model is illustrated through a case study of Lake Travis on the Lower ...

A methodology and model have been developed for the real-time optimal flood operation of river-reservoir systems. This methodology is based upon combining a nonlinear programming model with a flood-routing simulation model within an optimal control framework. The generalized reduced gradient code GRG2 is used to perform the nonlinear optimization and the simulator is the U.S. National Wheather Service DWOPER code. Application of the model is illustrated through a case study of Lake Travis on the Lower Colorado River in Texas.

Real time optimization of drilling parameters during drilling operations aims to optimize weight on bit, bit rotation speed for obtaining maximum drilling rate as well as minimizing the drilling cost. The process is formation specific. A Statistical method namely multiple linear regression technique is used for the drilling optimization methodology. An extensive literature survey on drilling optimization was conducted for this research study. A model is developed for this purpose using actual field data collected through modern well monitoring and data recording systems, which will be predicting the rate of drilling penetration as a function of available parameters. The rate of penetration general equation is optimized for effective functions at each data point. In order to optimize the parameters in the field, a computer network is required to be developed. The computer network will keep the piped data directly from the data source, and continuously be collecting the new data to be...

The increasing competition in refinery industries, reducing refinery plant’s costs, minimizing measurement errors and environmental issues lead to growing interest in modeling, simulation and optimization of refineries. Real time optimization (RTO) of the process units is one of the most effective ways for enhancing economic performance and reducing overhead costs of chemical plants. This method has a fully automated system, which intelligently collects and processes main outputs of the plant. Modifications of plant operating conditions have been implemented in order to reduce costs and meet constraints. Many objectives can be reached by implementation of RTO in refinery industries such as: automatically optimizing plant’s performance, automatically performing fault detection, elimination and modification of random errors (Data reconciliation), modification of nonrandom errors (Gross Error Detection), intelligent computation of data which are not measurable, calculating and reportin...

In this paper a practically efficient quality of service algorithm is proposed .Here we have a WARSHALS CONGESTION BASED algorithm for congestion path matrix to be retrieved .The algorithm provides the shortest congestion path matrix due to the congestion that is available in between the different vertex .The algorithm provides an alternate solution to the problem available using constant congestion constants and finding an optimal path matrix based over the congestion occurring over the graph. **

This paper investigates the issue of urban traffic signal control using a real time optimization model for signalized areas proposed in the related literature. The adopted model is modified to take into account the traffic scenarios, the different types of vehicles in the area, as well as pedestrians. The technique is applied to a real case study, consisting of two coordinated intersections located in the urban area of Bari (Italy). On the basis of traffic observations, optimal selection of the phases in the semaphoric cycle is performed under different congestion scenarios. Results show the ability of the strategy to minimize the vehicle queue lengths in the area.

This paper investigates the issue of urban traffic signal control using a real time optimization model for signalized areas proposed in the related literature. The adopted model is modified to take into account the traffic scenarios, the different types of vehicles in the area, as well as pedestrians. The technique is applied to a real case study, consisting of two coordinated intersections located in the urban area of Bari (Italy). On the basis of traffic observations, optimal selection of the phases in the semaphoric cycle is performed under different congestion scenarios. Results show the ability of the strategy to minimize the vehicle queue lengths in the area.

The scheduling of transportation systems has traditionally been done once a day. At beginning of a working day, the planner establishes which tasks will be carried out by each vehicle. Then, traffic jam, breakdown and any unexpected problem will cause delays on our timetable. In this paper, we propose to use real-time vehicle position knowledge to solve this problem. So, the planner is permanently enabled to reallocate tasks as the problem conditions change. As both drayage problem is a NP-Hard problem and a high-speed procedure is required, exact methods are not computationally feasible. So, a genetic algorithm has been implemented to perform the problem described.

An optimal control system was designed and applied to the acetylene hydrogenation section in an industrial process (EP-300) producing ethylene and propylene. A first principles model was developed for the hydrogenation reactor using industrial palladium pellets as catalyst, and a real time optimization algorithm was devised and incorporated to accommodate changing process conditions. The industrial application continues to be harnessed as it reduced the ethylene loss and increased the catalyst life, rendering important gains.

This paper presents a trajectory generation method that optimizes a quadratic cost functional with respect to linear system dynamics and to linear input and state constraints. The method is based on continuous-time flatness-based trajectory generation, and the outputs are parameterized using a polynomial basis. A method to parameterize the constraints is introduced using a result on polynomial nonpositivity. The resulting parameterized problem remains linear-quadratic and can be solved using quadratic programming. The problem can be further simplified to a linear programming problem by linearization around the unconstrained optimum. The method promises to be computationally efficient for constrained systems with a high optimization horizon. As application, a predictive torque controller for a permanent magnet synchronous motor which is based on real-time optimization is presented.