Antonella Ferrara

• Professor
• Professor (Full) at University of Pavia

Large-scale interconnected networks, composed of multiple low-dimensional subsystems, serve as a crucial framework for modeling a wide range of real-world applications. Despite offering computational scalability, the inherent interdependence among subsystems poses significant challenges to the effective control of such networks. This complexity is...

In this paper, a priority-based switching model predictive control (SMPC) method is proposed for space robots to execute sequential operation tasks efficiently. For a predefined series of subtasks, we develop a state-dependent SMPC approach that simultaneously determines control inputs and switching times. By incorporating switching within the pred...

This paper addresses the challenge of regulating the output voltage in single-end primary inductor converters (SEPICs) and introduces a practical solution based on the generation of second-order suboptimal sliding modes (2-SOSM). In contrast to the common assumption of a lossless SEPIC, in this paper, a lossy SEPIC is explored. A concise mathematic...

This letter proposes a discrete-time integral sliding mode (DT-ISM) control strategy for linear time-invariant systems subject to matched and unmatched disturbances. The DT-ISM strategy is defined based on a discrete-time model of the system obtained from its continuous-time counterpart, providing numerical procedures to determine the sets in which...

This paper considers electric and automated buses required to follow a given line and respect a given timetable in an inter-city road. The main goal of this work is to design a control scheme in order to optimally decide, in real time, the speed profile of the bus along the line, as well as the dwell and charging times at stops. This must be done b...

In this paper, we propose three control strategies, based on different levels of cooperation (centralized, decentralized and quasi-decentralized), to improve density dependent traffic performance indexes, such as fuel consumption, by acting on a small number of Connected and Automated Vehicles (CAVs) operating as moving bottlenecks on the surroundi...

This paper presents a control method for trajectory tracking of a robotic manipulator, subject to practical constraints and uncertainties. The proposed method is established upon an adaptive backstepping procedure incorporating a tangent-type barrier Lyapunov function and it preserves some important metrics of trajectory tracking such as fast and u...

The papers presents a new concept for controlling voltage and frequency in islanded microgrids composed by a Battery Energy Storage System (BESS) and PhotoVoltaic (PV) Units. The proposed approach is totally decentralized as each source is equipped with a purely local controller and no communication infrastructure is needed. Moreover, a centralized...

This letter introduces a new methodology for the design and tuning of sliding mode controllers with fixed-time stability property for a class of second-order uncertain nonlinear systems. Exploiting the Gauss error function, a novel sliding variable is designed, giving rise to a new control law, whose the main strengths are its ease of implementatio...

This article presents a fault diagnosis control scheme for intrinsically redundant robot manipulators based on the combination of a deep reinforcement learning (DRL) approach and a battery of sliding mode observers. The DRL plays the role of detecting and isolating possible sensor faults, thus generating an alarm and pin‐pointing the source. This i...

Model predictive control (MPC) has been widely used for traffic management, such as for minimizing the total time spent or the total emissions of vehicles. When long-term green urban mobility is considered including e.g. a constraint on the total yearly emissions, the optimization horizon of the MPC problem is significantly larger than the control...

This paper proposes an integral sliding mode (ISM) based unknown input observer (UIO) which is able to perform fault diagnosis (FD) in condition of lack of knowledge of the plant model. In particular, a two-layer neural network (NN) is employed to estimate online the drift term of the system dynamics needed to compute the so-called integral sliding...

In this paper, a control solution to reduce congestion in highway traffic systems is presented. The aim is to produce a control strategy characterized by low computational cost, so that real-time implementation can be attained. The adopted model to describe traffic dynamics is the METANET model. A particular spatio-temporal derivative relationship,...

Climate change, air pollution and energy costs impose new energy paradigms in order to meet the goals of a sustainable energy transition. Islanded Microgrids (MGs) are a very good structures to integrate Renewable Energy Sources (RES), as Photovoltaic (PV) units. PV plants are often connected in parallel with Storage (ST) units in order to exploit...

This paper proposes an enhanced version of the integral sliding mode (ISM) control, where a deep neural network (DNN) is first trained as a deep reinforcement learning (DRL) agent. Then, such a DNN is fine-tuned relying on a Lyapunov-based weight adaptation law, with the aim of compensating the lack of knowledge of the full dynamics in the case of...

This letter deals with the design of a novel adaptive bounded integral control (BIC) with enhanced anti-windup properties for systems with saturated actuators. Specifically, the BIC is re-designed improving its capability of desaturation after reaching the input bounds. Moreover, by adapting its characteristic curve, the proposed BIC is capable of...

In many application domains, navigation of unmanned aerial vehicles (UAVs) requires a planar flight to move along a desired path or to track a moving object under uncertain conditions. In this paper, we propose a robust control approach for quadrotor UAVs performing a nonholonomic-like navigation with a predefined velocity based guidance law. Speci...

In this letter a novel deep neural network based integral sliding mode (DNN-ISM) control is proposed for controlling perturbed systems with fully unknown dynamics. In particular, two DNNs with an arbitrary number of hidden layers are exploited to estimate the unknown drift term and the control effectiveness matrix of the system, which are instrumen...

The problem of stabilizing a class of nonholonomic systems in chained form affected by both matched and unmatched uncertainties is addressed in this paper. The proposed design methodology is based on a discontinuous transformation of the perturbed nonholonomic system to which an adaptive multiple-surface sliding mode technique is applied. The gener...

This study presents a near-optimal learning-based approach for sliding-mode control of uncertain nonsquare nonlinear systems subject to output constraints. To achieve a compromise between safety and optimality, a reinforcement learning algorithm is proposed to compute the near-optimal values of the sliding manifold coefficients. In the reinforcemen...

This paper considers the design of a minimum-time second-order sliding mode control (SOSMC) method for a class of full-state and input-constrained nonlinear systems. In this study, to enable the handling of the state and input constraints, a barrier-function-based state transformation method is employed to convert the original control problem to an...

The word teleoperation (which, in general, means “working at a distance”) is typically used in robotics when a human operator commands a remote agent. A teleoperated robot is often employed to substitute human beings in conditions where the latter cannot operate. A possible reason is the need to be in contact with dangerous substances, and indeed...

To achieve optimal robot behavior in dynamic scenarios we need to consider complex dynamics in a predictive manner. In the vehicle dynamics community, it is well know that to achieve time-optimal driving on low surface, the vehicle should utilize drifting. Hence many authors have devised rules to split circuits and employ drifting on some segments....

We present a general multi-scale approach for modeling the interaction of controlled autonomous vehicles (AVs) with the surrounding traffic flow. The model consists of a scalar conservation law for the bulk traffic, coupled with ordinary differential equations describing the possibly interacting AV trajectories. The coupling is realized through flu...

This paper analyzes how the presence of service stations on highways affects traffic congestion. We focus on the problem of optimally designing a service station to achieve beneficial effects in terms of total traffic congestion and peak traffic reduction. Microsimulators cannot be used for this task due to their computational inefficiency. We prop...

As the UK, together with numerous countries in the world, moves towards a new phase of the COVID-19 pandemic, there is a need to be able to predict trends in sufficient time to limit the pressure faced by the National Health Service (NHS) and maintain low hospitalisation levels. In this study, we explore the use of an epidemiological compartmental...

This letter presents a novel optimal control approach for systems represented by a multi-model, i.e., a finite set of models, each one corresponding to a different operating point. The proposed control scheme is based on the combined use of model predictive control (MPC) and first order integral sliding mode control. The sliding mode control compon...

Sustainable energy transition, air pollution reduction and climate change mitigation are the most challenging themes in nowadays energy sector. Microgrids (MGs) are one of the most effective ways to integrate Renewable Energy Sources (RES), and among them PhotoVoltaic (PV)-Storage (ST) configuration is relevantly promising. Focusing the attention o...

In this letter, a novel scheme is proposed to identify in finite time the value of an unknown output parameter for a class of nonlinear dynamical systems. Inspired by the Super-Twisting Sliding Mode Algorithm (STA), the identification problem is solved in an innovative way, consisting of two steps. An STA observer is firstly designed to track in fi...

In this paper, we propose a novel model that describes how the traffic evolution on a highway stretch is affected by the presence of a service station. The presented model enhances the classical CTM dynamics by adding the dynamics associated with the service stations, where the vehicles may stop before merging back into the mainstream. We name it C...

This letter deals with the design of a novel neural network based integral sliding mode (NN-ISM) control for nonlinear systems with uncertain drift term and control effectiveness matrix. Specifically, this letter extends the classical integral sliding mode control law to the case of unknown nominal model. The latter is indeed reconstructed by two d...

This letter considers electric and autonomous buses which have to follow a given route, including fixed stops, in extra-urban roads with a given timetable. A charging infrastructure is present in each stop, allowing to charge the bus batteries. An optimal control scheme is proposed in this letter in order to regulate the optimal speed of buses alon...

In this paper a novel hierarchical multi-level control scheme is proposed for freeway traffic systems. Relying on a coupled PDE-ODE nominal model, capturing the interaction between the macroscopic traffic flow and a platoon of connected and automated electric vehicles (CAVs) which acts as a moving bottleneck, a high-level model predictive controlle...

In this article a novel algorithm for the on-line control of formations of heterogeneous vehicles is proposed for highway traffic scenarios. A two-step iterative strategy relying on both a discrete and a continuous space representation, using Dynamic Programming and reference tracking via Model Predictive Control, is formulated. It allows the creat...

This paper extends previous results on constrained optimization control problems of uncertain robot systems based on sliding modes generation. An equivalent linear parameter varying (LPV) state-space representation of the nonlinear robot model is considered to design a stabilizing state-feedback control law by solving linear matrix inequalities (LM...

Freeway traffic control is a broad research area, not only interesting for its applicative perspective, but also highly motivating for theoretical investigations. This research topic has been developed in the last decades by different research groups worldwide and still offers open problems and issues to tackle which may be a source of inspiration...

This work presents the experimental assessment of a hybrid control scheme based on Deep Reinforcement Learning (DRL) for obstacle avoidance in robot manipulators. More precisely, relying on an equivalent Linear Parameter Varying (LPV) state-space representation of the system, two operative modes, one based on both joint positions and velocities, on...

This work proposes a novel control methodology to achieve gait symmetry in trans-femoral amputated patients with prostheses. The proposed approach allows to overcome the limits of classical model-based control strategies by introducing a Deep Reinforcement Learning (DRL) method trained ad hoc for generating the velocity control signals fed into the...

In this brief, a novel sliding mode (SM) observer-based scheme is proposed to achieve frequency regulation and economic dispatch (ED) in power grids composed of interconnection of generators and load buses. The ED problem is addressed in two steps. Assuming only the voltage phase angles are measured, in the first step a network of heterogeneous SM...

In this paper a novel distributed adaptive dual-layer super-twisting sliding mode observer-based scheme is designed to isolate, reconstruct and mitigate the effects of disturbances and a class of communication attacks affecting both generator nodes and load nodes in power networks. Voltage phase angles are measured at each node by means of Phasor M...

Event-triggered controllers are well known for guaranteeing the desired stability for a sampled-data system with minimum resource utilization. Over the past decade, the study has revealed that the overall performance improvement for a sampled-data system can be achieved by replacing the time-based sampling with an event-triggered one. The design of...

A discrete-time adaptive control approach for uncertain linear multivariable networked systems is proposed. It is capable of dealing with unknown time-delays introduced by a communication network between plant and controller. Based on the idea of model reference adaptive control, two adaptive laws are presented to reduce the conservativeness that i...

In this paper a hierarchical two-level control scheme is proposed in order to solve a ramp metering problem in freeway traffic systems. The proposal combines a Model Predictive Control (MPC) based supervisor with decentralized low-level Sliding Mode Controllers (SMCs). The considered freeway METANET model describes the traffic system, which is natu...

The objective of this note is to introduce a novel data-driven iterative linear quadratic control method for solving a class of nonlinear optimal tracking problems. Specifically, an algorithm is proposed to approximate the Q-factors arising from linear quadratic stochastic optimal tracking problems. This algorithm is then coupled with iterative lin...

In this chapter, an overview of the possibility of applying Sliding Mode Control to Consensus Control problems is proposed. The theoretical concepts at the basis of Consensus Control are first introduced to form a common basis useful to understand the results currently available in the literature, which are here adapted when needed to achieve a uni...

In this paper, a discrete-time sliding mode control law is proposed for nonlinear (possibly multi-input) systems, in the presence of mixed input-state constraints and additive bounded disturbances. The control law is defined by formulating a nonlinear predictive control problem aimed at generating a control input that imitates an unconstrained disc...

Two hierarchical control schemes for regulating traffic in freeway networks via ramp metering are developed in this article. Both schemes are characterized by a multiclass nature and aim to jointly improve the total time spent by the vehicles and their pollutant emissions in the freeway network. Moreover, these schemes have been designed to be "imp...

The paper deals with the design of a Suboptimal Second-Order Sliding Mode (SSOSM) control algorithm for local ramp metering of freeway systems. Indeed, sliding mode control is well-known for its robustness in front of uncertain terms and it perfectly fits to solve the control problem in case of traffic systems. Moreover, the proposed control law is...

In this paper a coupled PDE-ODE model describing the interaction between the bulk traffic flow and a platoon of connected vehicles is adopted to develop a control action aiming at reducing the fuel consumption of the overall traffic flow. The platoon is modeled as a capacity restriction acting on the surrounding traffic. The trajectory of the initi...

This letter proposes a hybrid control methodology to achieve full body collision avoidance in anthropomorphic robot manipulators. The proposal improves classical motion planning algorithms by introducing a Deep Reinforcement Learning (DRL) approach trained ad hoc for performing obstacle avoidance, while achieving a reaching task in the operative...

Charge unbalancing in series-connected cells can lead to lower storage capacity and shorter battery life. Model-based optimization strategies have proven to be very effective in addressing this problem. In this article, we propose a general nonlinear model predictive control (NMPC) scheme for obtaining a balancing-aware optimal charging. The presen...

Sliding mode control is a widely used approach in different application domains, due to its versatility and ease of implementation. As is well-known, one of its most serious drawbacks is the presence of chattering. To alleviate this problem, higher-order sliding mode approaches have been proposed, which also allow dealing with high relative degree...

In this paper a novel second order sliding mode control strategy is proposed for relative-degree-2 nonlinear uncertain SISO systems. To design the strategy, it is studied the phase portrait of the second order system in normal form associated with the formulated sliding mode control problem. A sliding surface switching between arcs of parabolas is...

Driving on the limits of vehicle dynamics requires predictive planning of future vehicle states. In this work, a search-based motion planning is used to generate suitable reference trajectories of dynamic vehicle states with the goal to achieve the minimum lap time on slippery roads. The search-based approach enables to explicitly consider a nonlin...

This chapter is devoted to the problem of Fault Diagnosis (FD) for industrial robotic manipulators within the framework of sliding mode control theory. According to this control concept, a set of unknown input higher order sliding mode observers are designed to detect, isolate and identify multiple actuators faults and corruptions. More specificall...

In this chapter, the robust control of input and state-constrained nonlinear systems is discussed from the perspective of sliding-mode control. The proposals currently available in the literature are summarized and some of them are briefly discussed, in particular cases providing also commented examples.

This chapter presents a review of sliding-mode estimation techniques recently proposed by the authors in the area of power systems. The power grid is interpreted as a large-scale system, composed of an interconnection of generator nodes and load nodes. The analysis starts at the local level by considering a single generator node for which two dynam...

This paper discusses the possibility of generating second-order sliding modes for the distributed control of vehicles in a platoon in the presence of both matched and unmatched uncertainty. In particular, a policy leading to the consideration of both spacing and velocity tracking requirements is considered for third-order vehicle dynamics, proving...

This paper presents an in-depth analysis of the application of different techniques for vehicle state and tyre force estimation using the same experimental data and vehicle models, except for the tyre models. Four schemes are demonstrated: (i) an Extended Kalman Filter (EKF) scheme using a linear tyre model with stochastically adapted cornering sti...

This paper deals with the design and the experimental-based assessment of a scheme to identify the relative degree of a system in order to correctly design the controller. The system is assumed to have an unknown dynamics, and the output is measured in a discrete-time fashion. Provided that a prescribed input signal is applied, it is proven that a...

We consider a model describing the presence of a platoon of vehicles moving in the traffic flow. The model consists of a coupled PDE-ODE system describing the interaction between the platoon and the surrounding traffic flow. The scalar conservation law takes into account the main traffic evolution, while the ODEs describe the trajectories of the in...

he environmental impact of transportation systems is considered a crucial point when new solutions must be adopted to enhance life quality in urban areas. All countries are seriously supporting and adopting green transportation systems according to increasingly stringent environmental quality targets. In this context, this paper introduces an innov...