Daylong acoustic recordings of grazing and rumination activities in dairy cows.

Monitoring livestock feeding behavior may help assess animal welfare and nutritional status, and to optimize pasture management. The need for continuous and sustained monitoring requires the use of automatic techniques based on the acquisition and analysis of sensor data. This work describes an open dataset of acoustic recordings of the foraging behavior of dairy cows. The dataset includes 708 h of daily records obtained using unobtrusive and non-invasive instrumentation mounted on five lactating multiparous Holstein cows continuously monitored for six non-consecutive days in pasture and barn. Labeled recordings precisely delimiting grazing and rumination bouts are provided for a total of 392 h and for over 6,200 ingestive and rumination jaw movements. Companion information on the audio recording quality and expert-generated labels is also provided to facilitate data interpretation and analysis. This comprehensive dataset is a useful resource for studies aimed at exploring new tools and solutions for precision livestock farming.

Embedded estimator in predictive feedback control.

In this work, a new approach to design predictive feedback control for SISO systems is presented. The proposed formulation relies on the development of a single step predictor based on an autoregressive moving average with external input (ARMAX) model. Although no explicit observer is actually involved in the implementation, this predictor implicitly includes one since the input-output model subsumes an observer. Exploiting this idea the resulting ARMAX model is extended to include extra outputs to improve the quality of the prediction for systems with large time delay and nonmeasurable disturbances. The resulting predictor is used to develop a predictive feedback controller. This new formulation of predictive feedback control includes feedback and feedforward actions. Simulations of two linear systems illustrate the applicability of the control algorithm.

Flexible-structure control: a strategy for releasing input constraints.

In this paper output unreachability under input saturation phenomenon is studied: under a large disturbance or setpoint change, the process output may never reach the set point even when the manipulated variable has driven to saturation. The process output can be brought back to the set point only by activating an auxiliary manipulated variable. A new control structure for designing and implementing a control system capable of solving this problem is proposed by transferring the control from one variable to another and taking into account the different dynamics involved in the system. The control structure, called flexible-structure control due to its ability to adapt the control structure to the operating conditons, is a generalization of the split-range control. It can be summarized as two controllers connected through a piecewise linear function. This function decides, based on the value of one manipulated variable, when and how the control structure changes. Its parameters control the interaction between both manipulated variables and leave the capability for handling the balance between control quality and other goals to the operator.

Predictive feedback control.

In this work a new method for designing predictive controllers for linear single-input/single-output systems is presented. It uses only one prediction of the process output J time intervals ahead to compute the correspondent future error. Then, the predictive feedback controller is defined by introducing a filter which weights the last w predicted errors. In this way, the resulting control action is computed by observing the system future behavior and also by weighting present and past errors. This last feature improves the closed-loop performance to disturbance rejection as shown through simulations of two linear systems and a nonlinear continuous stirred tank reactor.

Model predictive control with amplitude and rate actuator saturation.

In this work we show that the anti-wind-up-bumpless-transfer controller emerges from the structure of model predictive control (MPC) with quadratic objective and input constrains. The key to establish that relationship is the application of optimality conditions to the equivalent optimal control problem. The proposed framework employs a model of physical constraints as part of the controller architecture to ensure that the commands sent to the actuator do not exceed their specific limits and the internal states of the controller are well updated. Numerical examples are presented for illustrating the proposed control design methodology.