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In this paper, model-predictive control is used as a framework for implementing a quasi-time-optimal speed controller for a permanent-magnet synchronous motor. The scheme consists of an inner predictive torque control, which makes use of the full actuation range provided by a two-level voltage source inverter, although with the use of pulsewidth modulation. An outer speed controller, based on classical results for the time-optimal control of the double integrator, constitutes a good example application of the proposed torque controller. The overall scheme achieves both fast transient dynamics (as fast as the physics of the system and the control constraints allow) and acceptable steady-state performance.

In this work, a quasi-time-optimal, nonlinear state-feedback control for the torsional torque of a two-mass system is proposed. The scheme considers constraints in the stator voltage and currents of the driving machine: a permanent-magnet synchronous motor. Its design is based on results of the general framework of optimal control and leverages the assumption of a bang–bang structure for the actuation. In order to render its implementation feasible, the proposed algorithm exploits the geometrical properties displayed by the system state trajectories in the state space, when steered under a time-optimal regime. Spurious chattering is avoided switching to a smoother linear quadratic regulator, once the state reaches the vicinity of the target. The performance of the proposed controller is validated with experimental results, which consider an external proportional-integral controller for the load speed, tuned for relatively high bandwidth.

This paper presents the design of a predictive speed controller for electrical drives. The control scheme does not have a cascaded structure; instead, it uses a single optimization algorithm to generate the control action to be applied at the next sampling instant. The control is based on the optimization of a cost function, which is designed using the insight given by the solution of the minimum-time control problem for a simplified system, namely, the double integrator, which is a reasonable model of the machine dynamic behavior. The experimental results obtained with a permanent-magnet synchronous motor and an induction machine, fed by a two-level three-phase inverter, confirm that this approach reaches a very good dynamic performance without a high computational effort.

This paper presents a predictive strategy for the speed control of a two-mass system driven by a permanent magnet synchronous motor (PMSM). The proposed approach allows to manipulate all the system variables simultaneously, including mechanical and electrical variables in a single control law. The state feedback is achieved with a reduced order extended Kalman filter, which observes the non-measured variables as well as reduces the impact of measurement noise. The performance of the control strategy is shown through simulation and experimental results in a 4 [kW] laboratory prototype.

Multilevel converters can reach medium-voltage operation increasing the efficiency of high-power applications. Among the existing multilevel converter topologies, the modular multilevel converter (MMC) provides the advantages of high modularity, availability, and high power quality. Moreover, the main advantage compared to cascaded multilevel converters is the lack of an input transformer which results in a reduction of cooling requirements, size, and cost. One of the drawbacks of this topology when used as an ac-ac converter is the input and output frequency components in the control loop, resulting in a more complex controller design. In this paper, a single-phase ac-ac MMC predictive control approach is proposed. The controller minimizes the input, output, and circulating current errors and balances the dc voltages. Experimental results show the performance of the proposed predictive control scheme.