The field of control theory is moving towards the development of more sophisticated and robust control methods, with a focus on handling complex systems, uncertainties, and nonlinear dynamics. Recent research has explored the use of novel techniques such as compressed singular value decomposition, Bayesian optimization, and tensor-based polynomial Hamiltonian systems to improve the performance and stability of control systems. Additionally, there is a growing interest in the development of multi-objective and robust control methods, including the use of Integral Quadratic Constraints (IQCs) and H∞ control. These advances have the potential to impact a wide range of applications, from stabilizing inverted pendulums and suppressing vibrations in turbine blades to optimizing the performance of internal combustion engines and controlling complex systems such as triple inverted pendulums and slug flow crystallizers. Noteworthy papers include 'Stabilizing Linear Systems under Partial Observability: Sample Complexity and Fundamental Limits', which proposes a novel technique for stabilizing partially observable linear systems, and 'Optimal Parameter Adaptation for Safety-Critical Control via Safe Barrier Bayesian Optimization', which presents a framework for optimizing the performance of safety-critical control systems using Bayesian optimization.
Advances in Control Theory and Applications
Sources
Stabilizing Linear Systems under Partial Observability: Sample Complexity and Fundamental Limits
System Identification Under Bounded Noise: Optimal Rates Beyond Least Squares
Finite-Time Bounds for Two-Time-Scale Stochastic Approximation with Arbitrary Norm Contractions and Markovian Noise
Constraint Horizon in Model Predictive Control
Inertial-Based LQG Control: A New Look at Inverted Pendulum Stabilization
QSID-MPC: Model Predictive Control with System Identification from Quantized Data
Optimal Parameter Adaptation for Safety-Critical Control via Safe Barrier Bayesian Optimization
Iterative Learning Predictive Control for Constrained Uncertain Systems
A multiobjective approach to robust predictive control barrier functions for discrete-time systems
A Spectrum-based Filter Design for Periodic Control of Systems with Time Delay
Model Predictive Control for Tracking Bounded References With Arbitrary Dynamics
Automated and Risk-Aware Engine Control Calibration Using Constrained Bayesian Optimization
Local Stability and Stabilization of Quadratic-Bilinear Systems using Petersen's Lemma
Output-Feedback Boundary Control of Thermally and Flow-Induced Vibrations in Slender Timoshenko Beams
Explicit error bounds and guaranteed convergence of the Koopman-Hill projection stability method for linear time-periodic dynamics
On Tensor-based Polynomial Hamiltonian Systems
Multi-objective robust controller synthesis with integral quadratic constraints in discrete-time
Design and Analysis of a Robust Control System for Triple Inverted Pendulum Stabilization
Multi-stage model predictive control for slug flow crystallizers using uncertainty-aware surrogate models