Umberto Montanaro

Synthesis and Experimental Validation of the Novel LQ-NEMCSI Adaptive Strategy on an Electronic Throttle Valve

This paper is concerned with the design of a novel adaptive controller, namely the linear quadratic new extended minimal control synthesis with integral action (LQ-NEMCSI). We present for the first time the analytical proof of asymptotic stability of the controller and experimental evidence of the algorithm effectiveness for controlling an electronic throttle body: an element of any drive-by-wire system in automotive engineering, affected by many nonlinear perturbations.

Minimal Control Synthesis Adaptive Control of Continuous Bimodal Piecewise Affine Systems

This paper reviews the derivation of a model reference adaptive control (MRAC) scheme for bimodal piecewise-affine (PWA) continuous systems [9]. The algorithm is based on an extension of the minimal control synthesis algorithm, originally developed as an MRAC for smooth systems. The resulting adaptive algorithm is a switched feedback controller able to cope with uncertain continuous PWA systems. The effectiveness of the new proposed control strategy is shown by using it to achieve master slave synchronization of two PWA systems as a representative example.

Robust Discrete-Time MRAC With Minimal Controller Synthesis of an Electronic Throttle Body

The electronic throttle body (ETB) is a fundamental actuator for regulating the air mass coming into an internal combustion engine; hence, it is used to control the engine torque in any modern drive-by-wire configuration. To cope with the nonlinear and discontinuous dynamics of this automotive device, in this paper a novel discrete-time model reference adaptive control (MRAC) method is designed and experimentally tested on an ETB installed on a 2-L engine. The control strategy extends the class of the minimal control synthesis (MCS) algorithms for discrete-time systems by adding an explicit discrete-time adaptive integral action and an adaptive robust term. An in-depth experimental investigation shows that the proposed control method is a viable solution as it is robust with respect to nonlinear torques acting on the plant, and it guarantees better performance than those provided by other MRAC strategies especially for small reference signals around the limp-home position where plant nonlinearities strongly affect the ETB dynamics.

Novel switched model reference adaptive control for continuous piecewise affine systems

This paper is concerned with the derivation of a novel model reference adaptive control (MRAC) scheme for piecewise-affine (PWA) continuous systems. A novel version of the minimal control synthesis algorithm, originally developed as a MRAC for smooth systems, is presented. The resulting adaptive algorithm is a switched feedback controller able to cope with uncertain continuous PWA systems. The proof of stability, based on the newly developed passivity theory for hybrid systems, is provided and the effectiveness of the new proposed control strategy is numerically tested.

Novel hybrid MRAC-LQ control schemes: synthesis, analysis and applications

LQ optimal controllers are widely used in many applications as they provide a simple and effective solution to optimal control problems. There are many examples in the literature that show the lack of robustness of such controllers when the process is subject to parameter variations or when some dynamics are neglected. The hybrid algorithms proposed in this work extend the family of model reference minimal control synthesis adaptive controllers and address the issue of enhancing the robustness of LQ regulators. The main idea behind the approach is to seek a simple and alternative route to implement the LQ regulator via the MCS algorithm which is effective also in those practical cases when the LQ action itself fails. The stability of all the proposed control schemes is proved and the performance on a set of representative examples shows the effectiveness of the approach.

Model-Based Control of the Air Fuel Ratio for Gasoline Direct Injection Engines via Advanced Co-Simulation: An Approach to Reduce the Development Cycle of Engine Control Systems

Nowadays, the precise control of the air fuel ratio (AFR) in spark ignition (SI) engines plays a crucial role in meeting the more and more restrictive standard emissions for the passenger cars and the fuel economy required by the automotive market as well. To attain this demanding goal, the development of an advanced AFR control strategy embedding highly predictive models becomes mandatory for the next generation of electronic control unit (ECU). Conversely, the adoption of more complex control strategies affects the development time of the ECU increasing the time-to-market of new engine models. In this paper to solve the AFR control problem for gasoline direct injection (GDI) and to speed up the design of the entire control system, a gain scheduling PI model-based control strategy is proposed. To this aim, AFR dynamics are modeled via a first order time delay system whose parameters vary strongly with the fresh air mass entering the cylinders. Nonlinear relations have been found to describe the behavior of model parameters in function of air mass. Closed loop performances, when this novel controller is nested in the control loop, are compared to those provided by the classical PI Ziegler–Nichols control action with respect to different cost functions. Model validation as well as the effectiveness of the control design are carried out by means of ECU-1D engine co-simulation environment for a wide range of engine working conditions. The combination in one integrated designing environment of control systems and virtual engine, simulated through high predictive commercial one dimensional code, becomes a high predictive tool for automotive control engineers and enables fast prototyping.

Extended Cooperative Adaptive Cruise Control

In this paper the Cooperative Adaptive Cruise Control strategy for vehicles platooning is extended to the case when each vehicle can communicate with a subset of vehicles in the fleet. The control objective is to guarantee that the fleet moves forward with a given spacing policy at the leader velocity. To this aim each vehicle decides its control action using information from all neighboring vehicles through wireless communication. In so doing, a network of dynamical systems is formed, and it is shown that achieving platooning is equivalent to find a control algorithm so that the resulting network is asymptotically stable. A network protocol able to deal with heterogeneous time-varying communication delays is then proposed to solve the problem. A consistent proof of stability of the closed-loop system is provided and numerical results confirm the effectiveness of the approach and its robustness with respect to variations of the leader velocity, as well as to generic topologies of the underlying network emerging from the communication features.

Hybrid Minimal Control Synthesis identification of continuous piecewise linear systems

A novel identification strategy is presented in this paper for piecewise linear (PWL) dynamical systems. The strategy is based on the use of the Minimal Control Synthesis adaptive technique for PWL systems presented in [3]. After stating the general identification problem, the convergence of the novel algorithm is proved analytically in the case where the plant is PWL and the reference model is linear. Simulations are carried out on a representative example and are shown to be in perfect agreement with the theoretical derivations.

A novel cooperative adaptive cruise control approach: Theory and hardware in the loop experimental validation

In this paper we propose and experimentally validate within an ad hoc Hardware In the Loop (HIL) environment a novel approach for the control of a fleet of vehicles. In particular, the Cooperative Adaptive Cruise Control (CACC) for vehicles platooning is extended to the case when, due to the recent advances on vehicular wireless technologies, each vehicle can communicate not only with its follower but also with a subset of vehicles in the fleet. In so doing, a network of dynamical system emerges, and it is shown that the platooning problem is equivalent to find a control algorithm so that the resulting network is asymptotically stable. It is analytically shown that the decentralized control algorithm guarantee exponential stability despite heterogeneous time-varying communication delays which are unavoidable when wireless protocol are used. Finally, experimental results show the effectiveness and the robustness of the control approach also to variations of the leader velocity, as well as to generic topologies of the underlining network emerging from the communication features.

Adaptive Tracking Control of a Common Rail Injection System for Gasoline Engines: A Discrete-Time Integral Minimal Control Synthesis Approach

Over the last decade, gasoline direct injection engines have proven to be a promising solution to reduce both emission and fuel consumption. The achievement of superior performance strongly relies on its fuel injection system based on the common rail (CR) device. In order to tame the CR pressure dynamics without any a priori knowledge of the plant parameters, we design a novel model reference adaptive control strategy that extends the discrete-time minimal control synthesis algorithm. Indeed, an explicit discrete-time adaptive integral action is added to improve closed-loop performance. Experimental results support the analytical proof of stability, and confirm the effectiveness of the novel algorithm to solve both the regulation and the tracking control problem in a wide range of working conditions. The closed-loop performance is quantitatively evaluated via engineering indices.