arXiv subjects

Michael Cantoni

Publications and source records attributed to Michael Cantoni.

At least 19 recordsLinked to original sources

arXiv2026

Convergence Analysis of Noisy Distributed Gradient Descent for Non-convex Optimization -- Saddle Point Escape

This paper studies noisy distributed gradient descent (\textbf{NDGD}) for smooth non-convex finite-sum optimization over networks. Random perturbations enable saddle-point escape while preserving distributed implementation and consensus. Under suitable regularity conditions, \textbf{NDGD} converges with high probability to a neighborhood of a common local minimizer. Its convergence complexity is comparable to centralized first-order saddle-point escape methods, reducing exponential dependence on problem dimension to polynomial dependence. Numerical experiments demonstrate improved saddle-point escape over standard \textbf{DGD}.

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arXiv2026

Partitioned robustness analysis of networks with uncertain links

Network robustness to link perturbations is studied from an input-output perspective. The main result is a set of integral quadratic constraints (IQCs) that imply robust stability of the uncertain network dynamics. The model dependency of each IQC is localized according to an overlapping edge-partition for the network graph. The choice of partition over the admissible set affords flexibility in balancing conservativeness of the distributed certificate against its verification complexity. This is illustrated by a numerical example for a network with sampled-data links.

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arXiv2026

Energy-Gain Control of Time-Varying Systems: Receding Horizon Approximation

Standard formulations of prescribed worst-case disturbance energy-gain control policies for linear time-varying systems depend on all forward model data. In discrete time, this dependence arises through a backward Riccati recursion. This article is about the infinite-horizon $\ell_2$ gain performance of state feedback policies with only finite receding-horizon preview of the model parameters. The proposed synthesis of controllers subject to such a constraint leverages the strict contraction of lifted Riccati operators under uniform controllability and observability. The main approximation result is a sufficient number of preview steps for the incurred performance loss to remain below any set tolerance, relative to the baseline gain bound of the associated infinite-preview controller. Aspects of the result are explored in a numerical example.

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arXiv2025

Decentralized water-level balancing for irrigation channels in storage critical operations

A feedback control system is proposed for balancing the deviations of water levels from set-points along open channels subject to uncertain supply-demand mismatch that exceeds individual pool capacity. Decentralized controllers adjust the gate flows between pools to regulate potentially weighted differences between neighbouring water-level errors to zero in steady state. A sequential SISO loop-shaping procedure is developed for the design of each local flow controller based on distributed parameter transfer function models of the channel dynamics. Recursive feasibility of the procedure for relevant performance specifications, and stability of the resulting MIMO closed-loop, are verified by supporting analysis. Both numerical simulations and field trial results are presented.

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arXiv2024

Structured stability analysis of networked systems with uncertain links

An input-output approach to stability analysis is explored for networked systems with uncertain link dynamics. The main result consists of a collection of integral quadratic constraints, which together imply robust stability of the uncertain networked system, under the assumption that stability is achieved with ideal links. The conditions are decentralized inasmuch as each involves only agent and uncertainty model parameters that are local to a corresponding link. This makes the main result, which imposes no restriction on network structure, suitable for the study of large-scale systems.

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arXiv2024

Stereographic Projection of Probabilistic Frequency-Domain Uncertainty

This paper investigates the stereographic projection of points along the Nyquist plots of single input single output (SISO) linear time invariant (LTI) systems subject to probabilistic uncertainty. At each frequency, there corresponds a complex-valued random variable with given probability distribution in the complex plane. The chordal distance between the stereographic projections of this complex value and the corresponding value for a nominal model, as per the well-known Nu-Gap metric of Vinnicombe, is also a random quantity. The main result provides the cumulative density function (CDF) of the chordal distance at a given frequency. Such a stochastic distance framework opens up a fresh and a fertile research direction on probabilistic robust control theory.

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arXiv2024

Neighbourhood conditions for network stability with link uncertainty

The main result relates to structured robust stability analysis of an input-output model for networks with link uncertainty. It constitutes a collection of integral quadratic constraints, which together imply robust stability of the uncertain networked dynamics. Each condition is decentralized in the sense that it depends on model data pertaining to the neighbourhood of a specific agent. By contrast, pre-existing conditions for the network model are link-wise decentralized, with each involving conservatively more localized problem data. A numerical example is presented to illustrate the advantage of the new broader neighbourhood conditions.

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arXiv2023

On Riccati contraction in time-varying linear-quadratic control

Contraction properties of the Riccati operator are studied within the context of non-stationary linear-quadratic optimal control. A lifting approach is used to obtain a bound on the rate of strict contraction, with respect to the Riemannian metric, across a sufficient number of iterations. This number of iterations is related to an assumed uniform controllability and observability property of the dynamics and stage-cost in the original formulation of the problem.

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arXiv2023

On receding-horizon approximation in time-varying optimal control

The closed-loop stability and infinite-horizon performance of receding-horizon approximations are studied for non-stationary linear-quadratic regulator (LQR) problems. The approach is based on a lifted reformulation of the optimal control problem, under assumed uniform controllability and observability, leading to a strict contraction property of the corresponding Riccati operator. Leveraging this contraction property, a stabilizing linear time-varying state-feedback approximation of the infinite-horizon optimal control policy is constructed to meet a performance-loss specification. Its synthesis involves only finite preview of the time-varying problem data at each time step, over a sufficiently long prediction horizon.

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arXiv2023

Second-order Properties of Noisy Distributed Gradient Descent

We study a fixed step-size noisy distributed gradient descent algorithm for solving optimization problems in which the objective is a finite sum of smooth but possibly non-convex functions. Random perturbations are introduced to the gradient descent directions at each step to actively evade saddle points. Under certain regularity conditions, and with a suitable step-size, it is established that each agent converges to a neighborhood of a local minimizer and the size of the neighborhood depends on the step-size and the confidence parameter. A numerical example is presented to illustrate the effectiveness of the random perturbations in terms of escaping saddle points in fewer iterations than without the perturbations.

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arXiv2023

Explicit Time-Optimal Speed Profiles for Planar Paths with Monotone Curvature

Minimum-time speed profiles are constructed for planar paths with smooth strictly-monotonic signed curvature, subject to constraints on velocity, normal acceleration and tangential acceleration. The construction is explicit and exact, and global optimality is rigorously established from first principles under mild regularity conditions on the path. Free, fixed, and inequality-constrained boundary speeds are all accommodated. Numerical implementation is straightforward.

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arXiv2022

MITL Verification Under Timing Uncertainty

A Metric Interval Temporal Logic (MITL) verification algorithm is presented. It verifies continuous-time signals without relying on high frequency sampling. Instead, it is assumed that collections of over- and under-approximating intervals are available for the times at which the individual atomic propositions hold true for a given signal. These are combined inductively to generate corresponding over- and under-approximations for the specified MITL formula. The gap between the over- and under-approximations reflects timing uncertainty with respect to the signal being verified, thereby providing a quantitative measure of the conservativeness of the algorithm. The verification is exact when the over-approximations for the atomic propositions coincide with the under-approximations. Numerical examples are provided to illustrate.

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arXiv2022

Event-triggered boundary control of 2x2 semilinear hyperbolic systems

We present an event-triggered boundary control scheme for hyperbolic systems. The trigger condition is based on predictions of the state on determinate sets, where the control input is only updated if the predictions deviate from the reference by a given margin. Closed-loop stability and absence of Zeno behaviour is established analytically. For the special case of linear systems, the trigger condition can be expressed in closed-form as an $L_2$-scalar product of kernels with the distributed state. The presented controller can also be combined with existing observers to solve the event-triggered output-feedback control problem. A numerical simulation demonstrates the effectiveness of the proposed approach.

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arXiv2022

Sampling Polynomial Trajectories for LTL Verification

This paper concerns the verification of continuous-time polynomial spline trajectories against linear temporal logic specifications (LTL without 'next'). Each atomic proposition is assumed to represent a state space region described by a multivariate polynomial inequality. The proposed approach samples a trajectory strategically, to capture every one of its region transitions. This yields a discrete word called a trace, which is amenable to established formal methods for path checking. The original continuous-time trajectory is shown to satisfy the specification if and only if its trace does. General topological conditions on the sample points are derived that ensure a trace is recorded for arbitrary continuous paths, given arbitrary region descriptions. Using techniques from computer algebra, a trace generation algorithm is developed to satisfy these conditions when the path and region boundaries are defined by polynomials. The proposed PolyTrace algorithm has polynomial complexity in the number of atomic propositions, and is guaranteed to produce a trace of any polynomial path. Its performance is demonstrated via numerical examples and a case study from robotics.

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arXiv2021

Predictive feedback boundary control of semilinear and quasilinear 2x2 hyperbolic PDE-ODE systems

We present a control design for semilinear and quasilinear 2x2 hyperbolic partial differential equations with the control input at one boundary and a nonlinear ordinary differential equation coupled to the other. The controller can be designed to asymptotically stabilize the system at an equilibrium or relative to a reference signal. Two related but different controllers for semilinear and general quasilinear systems are presented and the additional challenges in quasilinear systems are discussed. Moreover, we present an observer that estimates the distributed PDE state and the unmeasured ODE state from measurements at the actuated boundary only, which can be used to also solve the output feedback control problem.

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arXiv2021

Boundary Feedback Control of 2x2 Quasilinear Hyperbolic Systems: Predictive Synthesis and Robustness Analysis

We present a predictive feedback control method for a class of quasilinear hyperbolic systems with one boundary control input. Assuming exact model knowledge, convergence to the origin, or tracking at the uncontrolled boundary, are achieved in finite time. A robustness certificate is provided, showing that at least under more restrictive assumptions on the system coefficients, the control method has inherent robustness properties with respect to small errors in the model, measurements and control input. Rigorous, although conservative conditions on the time derivative of the initial condition and on the design parameter controlling the convergence speed are given to ensure global existence of the solution for initial conditions with arbitrary infinity-norm.

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arXiv2020

Rigid-profile input scheduling under constrained dynamics with a water network application

The motivation for this work stems from the problem of scheduling requests for flow at supply points along an automated network of open-water channels. The off-take flows are rigid-profile inputs to the system dynamics. In particular, the channel operator can only shift orders in time to satisfy constraints on the automatic response to changes in the load. This leads to a non-convex semi-infinite programming problem, with sum-separable cost that encodes the collective sensitivity of end users to scheduling delays. The constraints encode the linear time-invariant continuous-time dynamics and limits on the state across a \al{continuous} scheduling horizon. Discretization is used to arrive at a more manageable approximation of the semi-infinite program. A method for parsimoniously refining the discretization is applied to ensure continuous-time feasibility for solutions of the approximate problem. It is then shown how to improve cost without loss of feasibility. Supporting analysis is provided, along with simulation results for a realistic irrigation channel setup to illustrate the approach.

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arXiv2020

Structured preconditioning of conjugate gradients for path-graph network optimal control problems

A structured preconditioned conjugate gradient (PCG) solver is developed for the Newton steps in second-order methods for a class of constrained network optimal control problems. Of specific interest are problems with discrete-time dynamics arising from the path-graph interconnection of $N$ heterogeneous sub-systems. The computational complexity of each PGC step is shown to be $O(NT)$, where $T$ is the length of the time horizon. The proposed preconditioning involves a fixed number of block Jacobi iterations per PCG step. A decreasing analytic bound on the effective conditioning is given in terms of this number. The computations are decomposable across the spatial and temporal dimensions of the optimal control problem, into sub-problems of size independent of $N$ and $T$. Numerical results are provided for a mass-spring-damper chain.

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