Search Results for author:
Found 27 papers, 1 papers with code
On constructive extractability of measurable selectors of set-valued maps
Finally, a viable control law can be seen, in general, as a selector.
Deep Neural Network based Optimal Control of Greenhouses
Then, the references are tracked using the trained Deep Neural Network (DNN) to reduce the computational burden.
Comparison of Unscented Kalman Filter Design for Agricultural Anaerobic Digestion Model
Dynamic operation of biological processes, such as anaerobic digestion (AD), requires reliable process monitoring to guarantee stable operating conditions at all times.
Experimental verification of an online traction parameter identification method
In this work, we validate such a method in field experiments with a mobile robot.
Observability and Identifiability Analyses of Process Models for Agricultural Anaerobic Digestion Plants
Dynamic operation of anaerobic digestion plants requires advanced process monitoring and control.
A map-based model predictive control approach for train operation
The developed method is simulated along a track with fast-changing traction conditions for different scenarios, like changing weather conditions and unexpected delays.
Modeling and optimal control of growth, energy, and resource dynamics of Hermetia illucens in mass production environment
Despite abundant literature on factors that affect larvae growth and the optimal static parameters identified in laboratory setup, for an industrial production process it is necessary to identify the trajectories such that the growth as well as the production process is optimal.
Process Optimization of Black Soldier Fly Egg Production via Model Based Control
Therefore, control must be applied in a careful way, which requires knowledge of the egg production cycle.
Predictive Control with Learning-Based Terminal Costs Using Approximate Value Iteration
Learning-based methods may be used to construct the terminal cost by relating it to, for instance, an infinite-horizon optimal control problem in which the optimal cost is a Lyapunov function.
Critical Clearing Time Estimates of Power Grid Faults via a Set-Based Method
This paper is concerned with estimating critical clearing times in the transient stability problem of power grids without extensive time-domain simulations.
A stabilizing reinforcement learning approach for sampled systems with partially unknown models
The method is tested in adaptive traction control and cruise control where it proved to significantly reduce the cost.
High-gain observer for the nitrification process including sensor dynamics
Point measurements of adjacent sensors in coarse sensor networks can be used to infer upon the state of nitrate concentrations in the sensor surroundings.
Synthesis of Lyapunov Functions using Formal Verification
Recent employments of SMT solvers within the Lyapunov function synthesis provided effective tools for automated construction of Lyapunov functions alongside with sound computer-assisted certificates.
Formal verification of a controller implementation in fixed-point arithmetic
This work aims to provide a computer-certified inductive definition for the control functions that are implemented on such processors accompanied with the fixed-point data type in a proof assistant.
Approximate infinite-horizon predictive control
Using a parametric terminal cost trained via approximate dynamic programming, a stabilizing predictive controller is proposed whose performance can directly be related to cost approximation errors.
Performance bounds of adaptive MPC with bounded parameter uncertainties
Because the system model is used to calculate the control law, the closed-loop behavior of the system and thus its performance, measured by the sum of the stage costs, are related to the model used.
Tracking of stabilizing, optimal control in fixed-time based on time-varying objective function
The controller of an input-affine system is determined through minimizing a time-varying objective function, where stabilization is ensured via a Lyapunov function decay condition as constraint.
Optimal control of centrifugal spreader
The presented work is concerned with the development of a predictive control scheme for optimized fertilizer application using modeling of the tractor moving on the field and the spread pattern in form of a crescent behind the tractor.
Extraction of a computer-certified ODE solver
To this end, an initial value problem has to be usually solved via numerical algorithms which rely on a certain software realization.
On MPC without terminal conditions for dynamic non-holonomic robots
We consider an input-constrained differential-drive robot with actuator dynamics.
On inf-convolution-based robust practical stabilization under computational uncertainty
It is a fairly general stabilization technique based on a generic non-smooth control Lyapunov function (CLF) and robust to actuator uncertainty, measurement noise, etc.
Transient Stability Analysis of Power Grids with Admissible and Maximal Robust Positively Invariant Sets
In this paper a set-based approach is presented to assess the transient stability of power systems.
Optimization and Control Systems and Control Systems and Control 93A15, 93-08, 93D99
On the Turnpike to Design of Deep Neural Nets: Explicit Depth Bounds
It is well-known that the training of Deep Neural Networks (DNN) can be formalized in the language of optimal control.
PoCET: a Polynomial Chaos Expansion Toolbox for Matlab
We introduce PoCET: a free and open-scource Polynomial Chaos Expansion Toolbox for Matlab, featuring the automatic generation of polynomial chaos expansion (PCE) for linear and nonlinear dynamic systems with time-invariant stochastic parameters or initial conditions, as well as several simulation tools.
Systems and Control Systems and Control
A method of online traction parameter identification and mapping
A case study is provided with the actual and estimated ground condition maps.
Recursive feasibility of continuous-time model predictive control without stabilising constraints
We consider sampled-data Model Predictive Control (MPC) of nonlinear continuous-time control systems.
Optimization and Control Dynamical Systems 93C15 (primary), 93C10, 34H05, 49N10 (secondary)
Half-Gain Tuning for Active Disturbance Rejection Control
A new tuning rule is introduced for linear active disturbance rejection control (ADRC), which results in similar closed-loop dynamics as the commonly employed bandwidth parameterization design, but with lower feedback gains.
