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We study the temporal robustness of temporal logic specifications and show how to design temporally robust control laws for time-critical control systems. This topic is of particular interest in connected systems and interleaving processes such as multi-robot and human-robot systems where uncertainty in the behavior of individual agents and humans can induce timing uncertainty. Despite the importance of time-critical systems, temporal robustness of temporal logic specifications has not been studied, especially from a control design point of view. We define synchronous and asynchronous temporal robustness and show that these notions quantify the robustness with respect to synchronous and asynchronous time shifts in the predicates of the temporal logic specification. It is further shown that the synchronous temporal robustness upper bounds the asynchronous temporal robustness. We then study the control design problem in which we aim to design a control law that maximizes the temporal robustness of a dynamical system. Our solution consists of a Mixed Integer Linear Programming (MILP) encoding that can be used to obtain a sequence of optimal control inputs. While asynchronous temporal robustness is arguably more nuanced than synchronous temporal robustness, we show that control design using synchronous temporal robustness is computationally more efficient. This tradeoff can be exploited by the designer depending on the particular application at hand. We conclude the article with a variety of case studies. [ABSTRACT FROM AUTHOR]

This paper describes the implementation of the model predictive direct torque control (MPDTC) algorithm for the control of three-phase induction motor drives comprising a three-level dc-link inverter. The MPDTC scheme is designed to keep the motor torque and stator flux and the inverter's neutral point potential within given hysteresis bounds while reducing the average switching frequency of the inverter, in comparison with the standard direct torque control (DTC) method. The algorithm is embedded in the control software environment of ABB's ACS6000 medium-voltage drive, and experimental results are provided which verify the advantageous features of MPDTC in terms of average inverter switching frequency reduction. More specifically, compared to standard DTC, the proposed MPDTC scheme achieves an average (over the whole operating range) reduction of the inverter switching frequency of 16.5%, but for specific operating conditions the reduction is as much as 37.4%. Index Terms--AC motor drives, direct torque control, model predictive control, power electronics.

This paper focuses on direct torque control (DTC) for three-phase ac electric drives. A novel model predictive control scheme is proposed that keeps the motor torque, the stator flux, and (if present) the inverter's neutral point potential within given hysteresis bounds while minimizing the switching frequency of the inverter. Based on an internal model of the drive, the controller predicts several future switch transitions, extrapolates the output trajectories, and chooses the sequence of inverter switch positions (voltage vectors) that minimizes the switching frequency. The advantages of the proposed controller are twofold. First, as underlined by the experimental results in the second part of this paper, it yields a superior performance with respect to the industrial state of the art. Specifically, the switching frequency is reduced by up to 50% while the torque and flux are kept more accurately within their bounds. Moreover, the fast dynamic torque response is inherited from standard DTC. Second, the scheme is applicable to a large class of (three-phase) ac electric machines driven by inverters. Index Terms--AC motor drives, direct torque control (DTC), model predictive control (MPC), power electronics.

This paper presents a sensorless explicit model predictive control scheme for the dc--dc boost converter. No direct inductor current measurement is needed as the coil current is derived either via a static approximation or, for improved accuracy, through an extended Kalman filter. The estimate is used in the chosen optimal control problem formulation which yields the optimal input by intrinsically accounting for duty cycle and current constraints. The optimization problem is explicitly presolved offline so that the online effort is reduced to a simple search in the resulting lookup table. No online optimization is required, greatly facilitating physical implementation and allowing for experimental validation on an integrated dc--dc converter through a fixed-point DSP. Index Terms--Boost converter, dc--dc extended Kalman filter (EKF), explicit model predictive control, model predictive control (MPC), switched-mode power supply (SMPS).

This paper deals with the control of pulsewidth modulation inverters connected to the grid through resonant LCL filters. It proposes two alternative (piecewise affine) models that account for the switched behavior of the converter. Based on these improved models, an explicit model-predictive control scheme is derived in order to provide a fast response, making it very suitable for applications, such as active filtering, where a large bandwidth is required. A state observer and a grid voltage estimator are used in order to reduce the number of required sensors and to eliminate noise. The control scheme relies only on filtered current measurements and on the dc voltage. Index Terms--Active damping, explicit model-predictive control (EMPC), Kalman filter, LCL filter, pulsewidth-modulation (PWM) inverter.

In this paper, we propose a novel approach to the modeling and controller design of the synchronous step-down dc-dc converter. We introduce a hybrid converter model that is valid for the whole operating regime and captures the different modes of operation. Based on this model, we formulate and solve a constrained optimal control problem. This allows a systematic controller design that achieves the regulation of the output voltage to its reference despite input voltage and output load variations while satisfying the constraints on the duty cycle and the inductor current. The resulting state-feedback control law is of piecewise affine form, which can be easily stored and implemented in a lookup table. A Kalman filter is added to account for unmeasured load variations and to achieve zero steady-state output voltage error. Experimental results demonstrate the potential advantages of the proposed control methodology. Index Terms--DC-DC converter, power electronics, model predictive control (MPC), optimal control, hybrid system, piecewise-affine (PWA) system.

This note continues on the results proposed in two previous papers for computing vector 1- or [infinity]-norm based Lyapunov functions for linear discrete-time systems by presenting a finitely terminating algorithm for the construction of Lyapunov functions of that class. The algorithm utilizes the solution of a finite sequence of feasibility linear programs (LPs) with very few constraints or, equivalently, very simple algebraic tests in contrast to solving the original problem where a bilinear matrix equation with rank and norm constraint needs to be solved. Index Terms--1-norm, [infinity]-norm, discrete-time system, linear system, Lyapunov function, Lyapunov stability, model predictive control (MPC) stability, vector norm.

We consider the constrained finite and infinite time optimal control problem for the class of discrete-time linear hybrid systems. When a linear performance index is used the finite and infinite time optimal solution is a piecewise affine state feedback control law. In this paper, we present algorithms that compute the optimal solution to both problems in a computationally efficient manner and with guaranteed convergence and error bounds. Both algorithms combine a dynamic programming exploration strategy with multiparametric linear programming and basic polyhedral manipulation. Index Terms--Constrained systems, discrete-time, dynamic programming, finite time, hybrid systems, infinite time, mnitiparametric linear program, optimal control, piecewise affine systems.