Fabio Previdi

Data-driven control design for neuroprotheses: a virtual reference feedback tuning (VRFT) approach

This paper deals with design of feedback controllers for knee joint movement of paraplegics using functional electrical stimulation (FES) of the paralyzed quadriceps muscle group. The controller design approach, virtual reference feedback tuning (VRFT), is directly based on open loop measured data and fits the controller in such a way that the closed-loop meets a model reference objective. The use of this strategy, avoiding the modeling step, significantly reduces the time required for controller design and considerably simplifies the rehabilitation protocols. Linear and nonlinear controllers have been designed and experimentally tested, preliminarily on a healthy subject and finally on a paraplegic patient. Linear controller is effective when applied on small range of knee joint angle. The design of a nonlinear controller allows better performances. It is also shown that the control design is effective in tracking assigned knee angle trajectories and rejecting disturbances.

Identification of non-linear parametrically varying models using separable least squares

In this paper a novel identification algorithm for a class of non-linear, possibly parameter varying models is proposed. The algorithm is based on separable least squares ideas. These models are given in the form of a linear fractional transformation (LFT) where the ‘forward’ part is represented by a conventional linear regression and the ‘feedback’ part is given by a non-linear map which can take into account scheduling variables available for measurement. The non-linear part of the model can be parameterized according to various paradigms, like, e.g. neural network (NN) or general nonlinear autoregressive exogenous (NARX) models. The estimation algorithm exploits the separability of the criterion used to estimate the parameters. When using a NN, it is possible the explicit computation of the Frechet derivative needed to implement a separable least square algorithm.

Control system design on a power-split CVT for high-power agricultural tractors

The problem considered in this paper is the design and tuning of the control system of a power-split continuously variable transmission (CVT) used in high-power tractors. Power-split CVTs are characterized by the combination of a traditional mechanical transmission and by a continuously-variable transmission. This guarantees, at the same time, smooth variations of the transmission-ratio and high efficiency of the overall transmission system. The control architecture of an hydrostatic power-split CVT is constituted by three main parts: 1) servo-controller on the current of the valve which drives the hydraulic transmission; 2) a servo-controller on the hydraulic transmission-ratio; and 3) a synchronizer which coordinates the hydraulic and the mechanical parts of the CVT. In this work, these three controllers are fully developed, including: design, implementation, and evaluation on an experimental system.

Identification of black-box nonlinear models for lower limb movement control using functional electrical stimulation

In this work, the problem of identification of nonlinear models for the functional electrical stimulation (FES) process is considered. In particular, experiments of stimulation of the quadriceps muscle group and the subsequent movement (or torque release) of the knee-joint will be examined. Both isometric and isotonic experimental conditions are described and NARX models will be identified from data, considering polynomial and neural network structures. For both model families, the issues of parameter estimation, structural identification and model validation will be discussed and effective solutions are proposed.

Design of a feedback control system for real-time control of flow in a single-screw extruder

The topic of this paper is the design and experimental testing of a prototype feedback control system for the regulation of the volumetric flow in a polymer single-screw extruder. Flow regulation is achieved by means of joint regulation of the temperature and the pressure at the die. The overall controller architecture is constituted by three control sub-tasks: the inner-loop control of the local temperatures along the barrel; the outer-loop control of the temperature at the extruder output; the control of the pressure at the extruder output. In this work, the whole design procedure (modeling, controller design, and testing) is presented. Extensive tests have shown that the system reacts rapidly to changes in the operating conditions and effectively rejects disturbances due to unexpected changes in the quality of the material. The achieved regulation provides very small steady state errors both for pressure and temperature. Moreover, it is shown that this control system is a cost-effective alternative to mechanical volumetric pumps.

Model-free actuator fault detection using a spectral estimation approach: the case of the DAMADICS benchmark problem

This paper presents the application to the DAMADICS benchmark fault detection problem of a model-free fault detection technique based on the use of a specific spectral analysis tool, namely, the Squared Coherency Functions (SCFs). The detection of a fault is achieved by on-line monitoring the estimate of the squared coherency function, which is sensitive to the occurrence of significative changes in the plant dynamics. The alarm threshold are based on the estimates of the confidence intervals of the SCF. Results on both simulation and real data of the DAMADICS benchmark (which is developed to approximate the industrial process in a sugar factory located in Lublin, Poland) are outlined.

Identification of the rainfall-runoff relationship in urban drainage networks

The calibration of conceptual models for the design of urban drainage networks is an important and well-known problem in hydraulic engineering. In this paper the problem is analysed and the use of black-box identification methods is proposed and applied to experimental data. Both linear (ARX and state space) and nonlinear (polynomial and neural NARX) models are considered and their performance in the simulation and prediction of the network flow from rainfall measurements is evaluated.

Performance analysis of semi-active suspensions with control of variable damping and stiffness

The problem considered in this paper is the study and the control strategy design of semi-active suspensions, featuring the regulation of both damping and stiffness. The first contribution of this paper is the introduction and the analysis of two architectures based on the use of only controllable dampers, which make possible the emulation of an ideal suspension with controllable-damping-and-stiffness. This work presents an evaluation of the performances and drawbacks achieved by such suspension architectures, also in a nonlinear setting (explicitly taking into account the stroke limits of the suspension). This paper then proposes a new comfort-oriented variable-damping-and-stiffness control algorithm, named stroke–speed–threshold–stiffness–control, which overcomes the critical trade-off between the choice of the stiffness coefficient and the end-stop hitting. The use of a variable-damping-and-stiffness suspension, together with this algorithm, provides a significant improvement of the comfort performances, if compared with traditional passive suspensions and with more classical variable-damping semi-active suspensions.

Slip-deceleration control in anti-lock braking systems

Abstract In road vehicles, wheel locking can be prevented by means of closed-loop Anti-lock Braking Systems (ABS). Two output measured variables are usually considered for regulation: wheel- deceleration and wheel longitudinal slip. The traditional controlled variable used in ABS is the wheel deceleration, since it can be easily measured with a simple wheel encoder; however, it can be dynamically critical if the road-surface rapidly changes. On the other hand, the regulation of the longitudinal slip is much robust from the dynamical point of view, but the slip measurement is critical, since it requires the estimation of the longitudinal vehicle speed. In this work a control strategy is proposed, where the regulated variable is a combination of wheel deceleration and longitudinal slip.

Modeling, identification, and analysis of limit-cycling pitch and heave dynamics in an ROV

The topic of this paper is the modeling, parameter identification, and analysis of the heave and pitch dynamics in a remote operated vehicle (ROV). The work presented here is motivated by an unusual dynamic behavior experienced on the Gaymarine Pluto-Gigas ROV: if the depth is regulated using a proportional controller, the ROV exhibits permanent oscillations at high forward speed. The purpose of this paper is to gain insight into ROV dynamics, so as to explain the reason for the oscillations. To this end, a dynamic gray-box model is developed and its uncertain parameters are identified from real data. The analysis of such a model shows that the nonlinear dynamics of the ROV contains a limit cycle. This discovery explains the observed oscillatory behavior. An interesting aspect of this limit-cycling behavior is that it is not due (as usual) to saturation effects of the actuators, but is intrinsic in the ROV dynamics.