D. Paesa

Bio: D. Paesa is an academic researcher from University of Zaragoza. The author has contributed to research in topics: Adaptive control & Reset (computing). The author has an hindex of 7, co-authored 14 publications receiving 191 citations.

Adaptive Simmering Control for Domestic Induction Cookers

Abstract: The goal of this paper is twofold. First, we aim at investigating the potentials of reset observers (ReOs) applied to process control. Second, we aim to overcome the existing performance limitations of the temperature control in domestic cookers. To this end, we present an adaptive simmering control for induction cookers, whose parameters are updated online, depending on the estimates provided by a multiple-model ReO (MMReO). This new observer results in extending the idea of multiple models to the state observer framework. The MMReO consists of a reinitialized ReO and of multiple fixed identification models. The resultant control scheme satisfies the user requirements such as quick heating up, accurate temperature control, and fast disturbance rejection, outperforming previous results. Moreover, the proposed control scheme reduces energy consumption, and consequently, it can increase the efficiency of the whole cooking process. Additionally, a fixed robust quantitative feedback theory (QFT)-based controller is designed, and it is also used for comparison purposes. Several verification tests are carried out in real induction hobs to emphasize the effectiveness of our proposal compared with the QFT-based controller.

Reset Adaptive Observer for a Class of Nonlinear Systems

Abstract: This technical note proposes a novel kind of state estimator called reset adaptive observer (ReO). A ReO is an adaptive observer consisting of an integrator and a reset law that resets the output of the integrator depending on a predefined condition. The main contribution of this technical note is that the reset element theory is applied for the first time to the nonlinear adaptive observer framework. The introduction of the reset element in the adaptive law can decrease the overshooting and settling time of the estimation process without sacrificing the rising time. The stability and convergence LMI-based analysis of the proposed ReO is addressed and, additionally, an easily computable method to determine the L2 gain of the ReO dealing with noise-corrupted systems is presented.

Inductive Sensor for Temperature Measurement in Induction Heating Applications

Abstract: A new inductive sensor for temperature measurement in domestic induction hobs and results of its applications are presented. It consists of a coil and a resonant electronic circuit which measures the impedance variation of ferromagnetic pots when their temperature changes. This sensor has promising applicability in induction hobs because it has instantaneous response, it is cheap, and contactless. The performance of the sensor is tested in the cooking range from 20°C to 220° C with pots of different materials, revealing a measurement error lower than 6°C. This error is much lower than that obtained from measurements with current sensing systems installed in induction hobs, namely a thermistor measuring the temperature of the glass in the cooking zone. The proposed sensor will allow fire prevention in cooking processes with a cost comparable to that of conventional measurement systems.

Adaptive Observers Applied to Pan Temperature Control of Induction Hobs

Abstract: In this paper, a pan temperature control of induction hobs is described. The aim is that the user may select the cooking temperature instead of the power for the cooker. Pan temperature has to be estimated from a thermal sensor placed under the ceramic glass. Heat transmission from the induction coil to the pan and from the pan to the thermal sensor is modeled using a state-space model. As induction heating is highly dependent on thermal and magnetic pan properties, two different adaptive schemes are proposed and compared. Both guarantee a proper closed loop behavior. The contribution of this paper is related with temperature adaptive observer for different pans. The resultant system is simple, user friendly, robust, and safe, and is used for automatic cooking.

Coverage control for mobile sensing networks

Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Induction Heating Technology and Its Applications: Past Developments, Current Technology, and Future Challenges

Abstract: Induction heating (IH) technology is nowadays the heating technology of choice in many industrial, domestic, and medical applications due to its advantages regarding efficiency, fast heating, safety, cleanness, and accurate control. Advances in key technologies, i.e., power electronics, control techniques, and magnetic component design, have allowed the development of highly reliable and cost-effective systems, making this technology readily available and ubiquitous. This paper reviews IH technology summarizing the main milestones in its development and analyzing the current state of art of IH systems in industrial, domestic, and medical applications, paying special attention to the key enabling technologies involved. Finally, an overview of future research trends and challenges is given, highlighting the promising future of IH technology.

State and Unknown Input Observers for Nonlinear Systems With Bounded Exogenous Inputs

Abstract: A systematic design methodology for state observers for a large class of nonlinear systems with bounded exogenous inputs (disturbance inputs and sensor noise) is proposed. The nonlinearities under consideration are characterized by an incremental quadratic constraint parameterized by a set of multiplier matrices. Linear matrix inequalities are developed to construct observer gains, which ensure that a performance output based on the state estimation error satisfies a prescribed degree of accuracy. Furthermore, conditions guaranteeing estimation of the unknown inputs to arbitrary degrees of accuracy are provided. The proposed scheme is illustrated with a numerical example, which does not satisfy the so-called “matching conditions.”

Analytical Model of the Half-Bridge Series Resonant Inverter for Improved Power Conversion Efficiency and Performance

Abstract: Resonant power conversion is a key enabling technology of dc–dc conversion, inverters and contactless energy transfer systems. This paper presents an analytical model of the series resonant half-bridge topology aimed at improving the design, control, and efficiency of resonant power converters. The main contribution is a closed-form expression of the main converter waveforms as well as output power and efficiency. This model enables a fast design-space exploration, as well as the implementation of advanced control techniques using adaptive control or real-time emulation, significantly improving the converter operation. The analytical expressions presented have been applied and verified through a half-bridge series resonant inverter applied to induction heating applications, proving the accuracy and effectiveness of the proposed model.

FPGA-Based Test-Bench for Resonant Inverter Load Characterization

Abstract: Resonant converters often require accurate load characterization in order to ensure appropriate and safe control. Besides, for systems with a highly variable load, as the induction heating systems, a real-time load estimation is mandatory. This paper presents the development of an FPGA-based test-bench aimed to extract the electrical equivalent of the induction heating loads. The proposed test-bench comprises a resonant power converter, sigma-delta ADCs, and an embedded system implemented in an FPGA. The characterization algorithm is based on the discrete-time Fourier series computed directly from the ΔΣ ADC bit-streams, and the FPGA implementation has been partitioned into hardware and software platforms to optimize the performance and resources utilization. Analytical and simulation results are verified through experimental measurements with the proposed test-bench. As a result, the proposed platform can be used as a load identification tool either for stand-alone or PC-hosted operation.