Time optimal MPC for mechatronic applications

Abstract

Model predictive control (MPC) is an on-line control technique originally developed for slow processes which makes an assessment between input effort and output error while respecting constraints on inputs and outputs. Due to improved computing power and algorithms, MPC is nowadays also applied to mechatronic systems. For these systems, achieving minimal settling time is the main concern, while the input cost is usually of less importance. Hence, this paper presents a new type of MPC; time optimal MPC (TOMPC) which minimizes the settling time of the system. Theoretical considerations show that TOMPC is stabilizing. Simulations show the merits of this technique and indicate that it is applicable in real-time.

Pushing motion control systems to their limits using convex optimization techniques

“…To do so, the objective function is augmented with log-barrier terms associated with constraints (20) multiplied with the so-called log-barrier parameter κ, and constraints (20) are omitted. Also constraints (19) are omitted since for a time-optimal solutionṡ(t) should always be ≥ 0. Hence an unconstrained optimization problem is obtained.…”

“…Optimal control of mechatronic systems is one of the key application areas of OPTEC, with a focus on dynamic and embedded optimization software (e.g. qpOASES [8], ACADO [http://acadotoolkit.org/]) and applications [18], [19], and analysis and control of linear infinite-dimensional parameter varying systems [13], [6].…”

Analysis of the MPC Using in the Control of a Mechatronic System with Flexible Elements

“…The proposal to eliminate the negative effects of the combination of the filter using and the existence of the elastic coupling parameter error is the use of predictive control method called Model predictive control (MPC). [7,8,9,10] Next part -control system with MPC controller was added (Fig. 7) to original control system with PID controller (Fig.…”

Near time-optimal model predictive control using an L1-norm based cost functional

“…Traditionally MPC problems are based on quadratic forms in order to cast the optimization problem as a quadratic program (QP) for which efficient solvers are available [2], [3]. QPs can be used for near time-optimal control but it is necessary to approximate and/or transform the original time-optimal control problem [4], [5].…”