In this paper, the focus is on ice clamping of workpieces using feedback-controlled Peltier cells, which represents a novel nonlinear control application. As only the hot-side temperature is accessible for measurements, an Unscented Kalman filter (UKF) estimates the temperatures on both the hot and cold sides of the Peltier element and a lumped disturbance heat flow acting on the cold side. These estimates are employed in linearized discrete-time model predictive control (MPC), which is adapted in each time step based on Taylor linearizations around desired trajectories, also considering the predicted future linearization errors, and tracks a given cold-side temperature profile despite interfering heat inflow from the machining process. Here, the nonlinear system model is exploited to calculate favorable desired values that correspond to low currents, minimizing the overall energy consumption and avoiding another possible operating point with high currents. The achieved tracking precision and estimation accuracy is pointed out in simulation results for a typical ice clamping scenario subject to disturbances.

As the drive force depends in a nonlinear manner on the currents, an accurate tracking control of permanent magnet linear motors is challenging. In this paper, a cascaded control is proposed and combined with a recursive estimator. In the inner loop of the cascaded structure, an inversion-based control design is employed in combination with an eigenvalue assignment. The outer loop involves a backstepping tracking control of the armature position, where a nonlinear error dynamics is assigned. Given nonlinear friction and other disturbances, a lumped disturbance force is estimated by a dual Kalman filter – in addition to the state variables. This combination achieves a high robustness of the overall control structure. The control performance is investigated in detailed simulations, where also measurement noise and external disturbances are included.

This paper proposes an estimator-based tracking control for a thermoelectric cooling system with Peltier cells. It is intended for use in a novel manufacturing system leveraging ice clamping. Starting from physical principles and conservation equations, a 4th-order state space model is developed and exploited within an input-output linearization, where the internal dynamics can be shown to be asymptotically stable. A backstepping-based tracking control is designed to accurately track the desired cold side temperature even in the presence of disturbances. Unknown states and disturbances are observed using an Unscented Kalman Filter, which outperforms previous results with alternative estimators. Conclusive simulation results are discussed and demonstrate the performance of the combined control and estimation structure.

This paper deals with a Peltier cell used in an innovative manufacturing system with a cascaded Kalman filter (KF) structure to estimate states and parameters to be used in a closed loop control law. While disturbances, states, and parameters of the Peltier cell are estimated online using a cascaded Kalman filter structure, a sliding mode control (SMC) strategy is proposed to maintain the cold-side temperature even in the presence of disturbances. One theorem is given that allows the design of a constructive control strategy. Simulation results are shown and with them the effectiveness of the method.