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Found 18 papers, 2 papers with code
MPC-Inspired Reinforcement Learning for Verifiable Model-Free Control
In this paper, we introduce a new class of parameterized controllers, drawing inspiration from Model Predictive Control (MPC).
Finite Time Performance Analysis of MIMO Systems Identification
This paper is concerned with the finite time identification performance of an n dimensional discrete-time Multiple-Input Multiple-Output (MIMO) Linear Time-Invariant system, with p inputs and m outputs.
Generalized Activation via Multivariate Projection
Activation functions are essential to introduce nonlinearity into neural networks, with the Rectified Linear Unit (ReLU) often favored for its simplicity and effectiveness.
Sensor Selection for Remote State Estimation with QoS Requirement Constraints
By utilizing the solution of the relaxed problem, we propose a heuristic sensor selection algorithm which can provide a good suboptimal solution.
Secure State Estimation with Asynchronous Measurements against Malicious Measurement-data and Time-stamp Manipulation
To deal with such attacks, we propose the design of local estimators based on observability space decomposition, where each local estimator updates the local state and sends it to the fusion center after sampling a measurement.
Almost Surely $\sqrt{T}$ Regret Bound for Adaptive LQR
The Linear-Quadratic Regulation (LQR) problem with unknown system parameters has been widely studied, but it has remained unclear whether $\tilde{ \mathcal{O}}(\sqrt{T})$ regret, which is the best known dependence on time, can be achieved almost surely.
Safe and Efficient Switching Controller Design for Partially Observed Linear-Gaussian Systems
Switching control strategies that unite a potentially high-performance but uncertified controller and a stabilizing albeit conservative controller are shown to be able to balance safety with efficiency, but have been less studied under partial observation of state.
Secure State Estimation against Sparse Attacks on a Time-varying Set of Sensors
At each time step, the local estimates of sensors are fused by solving an optimization problem to obtain a secure estimation, which is then followed by a local detection-and-resetting process of the decentralized observers.
Safe and Efficient Switching Mechanism Design for Uncertified Linear Controller
We show that the switching strategy is both safe and efficient, in the sense that: 1) the linear-quadratic cost of the system is always bounded even if original uncertified controller is destabilizing; 2) in case the uncertified controller is stabilizing, the performance loss caused by switching converges super-exponentially to $0$ for Gaussian noise, while the converging polynomially for general heavy-tailed noise.
Ensuring the Safety of Uncertified Linear State-Feedback Controllers via Switching
Sustained research efforts have been devoted to learning optimal controllers for linear stochastic dynamical systems with unknown parameters, but due to the corruption of noise, learned controllers are usually uncertified in the sense that they may destabilize the system.
Event-Based Control for Synchronization of Stochastic Linear Systems with Application to Distributed Estimation
We propose an event-based control protocol for achieving the synchronization among agents in the mean square sense and theoretically analyze the performance of it by using a stochastic Lyapunov function, where the stability of $c$-martingales is particularly developed to handle the challenges brought by the general model of noises and the event-triggering mechanism.
A Framework for Distributed Estimation with Reduced Communication via Event-Based Strategies
This paper considers the problem of distributed estimation in a sensor network, where multiple sensors are deployed to infer the state of a linear time-invariant (LTI) Gaussian system.
Efficient Secure State Estimation against Sparse Integrity Attack for System with Non-derogatory Dynamics
We consider the problem of estimating the state of a time-invariant linear Gaussian system in the presence of integrity attacks.
Low Complexity Secure State Estimation Design for Linear System with Non-derogatory Dynamics
We consider the problem of estimating the state of a linear Gaussian system in the presence of integrity attacks.
Security Protection in Cooperative Control of Multi-agent Systems
An upper bound of false alarm rate in the absence of malicious attackers and the necessary and sufficient condition for there is no undetectable input by the attack detector in the system are given.
Safe Linear-Quadratic Dual Control with Almost Sure Performance Guarantee
This paper considers the linear-quadratic dual control problem where the system parameters need to be identified and the control objective needs to be optimized in the meantime.
A Distributed Implementation of Steady-State Kalman Filter
This paper studies the distributed state estimation in sensor network, where $m$ sensors are deployed to infer the $n$-dimensional state of a linear time-invariant (LTI) Gaussian system.
Resilient Multi-Dimensional Consensus in Adversarial Environment
To this end, this paper first considers a general class of consensus algorithms, where each benign agent computes an "auxiliary point" based on the received values and moves its state toward this point.
