skip to main content

Title: Proportional Integral Derivative Control in Spark Plasma Sintering Simulations
The prediction of microstructure evolution and densification behavior during the spark plasma sintering (SPS) process largely depends on accurate temperature regulation. A loop feedback control algorithm called proportional integral derivative (PID) control is a practical simulation tool, but its coefficients are often determined by an inefficient “trial and error” method. This paper is devoted to proposing a numerical method based on the principles of variable coefficients to construct an optimal linear PID controller in SPS electro-thermal simulations. Different types of temperature profiles were applied to evaluate the feasibility of the proposed method. Simulation results showed that, for temperature profiles conventionally used in SPS cycles, the PID output keeps pace with the desired profile. Characterized by an imperfect time delay and overshoot/undershoot, the constructed PID controller needs further advancement to provide a more satisfactory temperature regulation for non-continuous temperature profiles. The first step towards a numerical rule for the optimal PID controller design was undertaken in this work. It is expected to provide a valuable reference for the advanced electro-thermal modeling of SPS.
Authors:
; ; ;
Award ID(s):
1900876
Publication Date:
NSF-PAR ID:
10222136
Journal Name:
Materials
Volume:
14
Issue:
7
Page Range or eLocation-ID:
1779
ISSN:
1996-1944
Sponsoring Org:
National Science Foundation
More Like this
  1. In this paper, we propose a modeling and design technique for a proportional-integral-derivative (PID) controller in the presence of aperiodic intermittent sensor measurements. Using classical control design methods, PID controllers can be designed when measurements are available periodically, at discrete time instances, or continuously. Unfortunately, such design do not apply when measurements are available intermittently. Using the hybrid inclusions framework, we model the continuous-time plant to control, the mechanism triggering intermittent measurements, and a hybrid PID control law defining a hybrid closed-loop system. We provide sufficient conditions for uniform global asymptotic stability using Lyapunov set stability methods. These sufficient conditionsmore »are used for the design of the gains of the hybrid PID controller. Also, we propose relaxed sufficient conditions to provide a computationally tractable design method leveraging a polytopic embedding approach. The results are illustrated via numerical examples.« less
  2. In modern high-performance aircraft, the Fuel Thermal Management System (FTMS) plays a critical role in the overall thermal energy management of the aircraft. Actuator and state constraints in the FTMS limit the thermal endurance and capabilities of the aircraft. Thus, an effective control strategy must plan and execute optimized transient fuel mass and temperature trajectories subject to these constraints over the entire course of operation. For the control of linear systems, hierarchical Model Predictive Control (MPC) has shown to be an effective approach to coordinating both short- and long-term system operation with reduced computational complexity. However, for controlling nonlinear systems,more »common approaches to system linearization may no longer be effective due to the long prediction horizons of upper-level controllers. This paper explores the limitations of using linear models for hierarchical MPC of the nonlinear FTMS found in aircraft. Numerical simulation results show that linearized models work well for lower-level controllers with short prediction horizons but lead to significant reductions in aircraft thermal endurance when used for upper-level controllers with long prediction horizons. Therefore, a mixed-linearity hierarchical MPC formulation is presented with a nonlinear upper-level controller and a linear lower-level controller to achieve both high performance and high computational efficiency.« less
  3. A high frequency solid-state transformer (SST) proposed by FREEDM centre is an interesting alternative to conventional distribution transformer in microgrids as it supports additional functionalities such as active-reactive power flow control, fault current limitation and voltage regulation. This paper proposes a dynamic phasor based robust control of SST through the modular control of each stage. The control problem is formulated in frequency domain by representing the system states with time varying Fourier coefficients or dynamic phasors (DP). This formulation transforms the oscillating waveforms of ac circuits to constant or slowly varying variables, hence allow the use of PI controller tomore »track the sinusoidal references. For rectifier and inverter stages of SST, dq transformation is applied on DP which facilitates the design of PI controller to smoothen out the ripples in the output voltage waveform. The controller gains are tuned to reject input and load disturbances and attenuate measurement noise using loop shaping and pole assignment technique. The robustness of the controller is assured analytically against parametric uncertainties using small gain theorem. Simulation results are provided to support the proposed control scheme. Hardwarein- Loop (HIL) simulation is carried out on critical stages using Opal-RT and dSPACE simulators to confirm the effectiveness of the proposed scheme.« less
  4. Reinforcement learning (RL) has recently shown promise in solving difficult numerical problems and has discovered non-intuitive solutions to existing problems. This study investigates the ability of a general RL agent to find an optimal control strategy for spacecraft attitude control problems. Two main types of Attitude Control Systems (ACS) are presented. First, the general ACS problem with full actuation is considered, but with saturation constraints on the applied torques, representing thruster-based ACSs. Second, an attitude control problem with reaction wheel based ACS is considered, which has more constraints on control authority. The agent is trained using the Proximal Policy Optimizationmore »(PPO) RL method to obtain an attitude control policy. To ensure robustness, the inertia of the satellite is unknown to the control agent and is randomized for each simulation. To achieve efficient learning, the agent is trained using curriculum learning. We compare the RL based controller to a QRF (quaternion rate feedback) attitude controller, a well-established state feedback control strategy. We investigate the nominal performance and robustness with respect to uncertainty in system dynamics. Our RL based attitude control agent adapts to any spacecraft mass without needing to re-train. In the range of 0.1 to 100,000 kg, our agent achieves 2% better performance to a QRF controller tuned for the same mass range, and similar performance to the QRF controller tuned specifically for a given mass. The performance of the trained RL agent for the reaction wheel based ACS achieved 10 higher better reward then that of a tuned QRF controller« less
  5. Abstract

    Textile-based compression devices are widely used in fields such as healthcare, astronautics, cosmetics, defense, and more. While traditional compression garments are only able to apply passive pressure on the body, there have been some efforts to integrate smart materials such as shape memory alloys (SMAs) to make compression garments active and controllable. However, despite the advances in this field, accurate control of applied pressure on the body due remains a challenge due to vast population-scale anthropometric variability and intra-subjects variability in tissue softness, even if the actuators themselves are fully characterized. In this study, we begin to address thesemore »challenges by developing a novel size-adjustable SMA-based smart tourniquet capable of producing a controllable pressure for circumferential applications. The developed prototype was tested on an inflatable pressure cuff wrapped around a rigid cylinder. The thermal activation of SMA coils was achieved through Joule heating, and a microcontroller and a programmable power supply are used to provide the input signal. To control the compression force, a closed-loop PID controller was implemented, and the performance of the system was evaluated in 5 different testing conditions for variable and cyclic compression levels. The experiments showed that the controlled system could follow the desired control pressure reference with a steady-state of 1 mmHg. The compression tourniquet is able to produce more than 33 mmHg with an average actuation rate of 0.19 mmHg/s. This is the first demonstration of accurate closed-loop control of an SMA-incorporated compression technology to the best of our knowledge. This paper enables new, dynamic systems with controllable activation and low-effort donning and doffing, with applications ranging from healthcare solutions to advanced spacesuit design.

    « less