Model predictive control of magnetically actuated mass spring dampers for automotive applications

Mechatronic systems such as those arising in automotive applications are characterized by significant non-linearities, tight performance specifications as well as by state and input constraints which need to be enforced during system operation. This paper takes a view that model predictive control (MPC) and hybrid models can be an attractive and systematic methodology to handle these challenging control problems, even when the underlying process is not hybrid. In addition, the piecewise affine (PWA) explicit form of MPC solutions avoids on-line optimization and can make this approach computationally viable even in situations with rather constrained computational resources. To illustrate the MPC design procedure and the underlying issues, we focus on a specific non-linear process example of a mass spring damper system actuated by an electromagnet. Such a system is one of the most common elements of mechatronic systems in automotive systems, with fuel injectors representing a concrete example. We first consider a linear MPC design for the mechanical part of the system. The approach accounts for all the constraints in the system but one, which is subsequently enforced via a state-dependent saturation element. Second, a hybrid MPC approach for the mechanical subsystem is analysed that can handle all the constraints by design and achieves better performance, at the price of a higher complexity of the controller. Finally, a hybrid MPC design that also takes into account the electrical dynamics of the system is considered.     

A unified approach for inverse and direct dynamics of constrained multibody systems based on linear projection operator: applications to control and simulation

This paper presents a unified approach for inverse and direct dynamics of constrained multibody systems that can serve as a basis for analysis, simulation, and control. The main advantage of the dynamics formulation is that it does not require the constraint equations to be linearly independent. Thus, a simulation may proceed even in the presence of redundant constraints or singular configurations, and a controller does not need to change its structure whenever the mechanical system changes its topology or number of degrees of freedom. A motion-control scheme is proposed based on a projected inverse-dynamics scheme which proves to be stable and minimizes the weighted Euclidean norm of the actuation force. The projection-based control scheme is further developed for constrained systems, e.g., parallel manipulators, which have some joints with no actuators (passive joints). This is complemented by the development of constraint force control. A condition on the inertia matrix resulting in a decoupled mechanical system is analytically derived that simplifies the implementation of the force control. Finally, numerical and experimental results obtained from dynamic simulation and control of constrained mechanical systems, based on the proposed inverse and direct dynamics formulations, are documented.     

Nonlinear model-based control of pneumatic artificial muscle servo systems

This paper proposes a control methodology of the pneumatic artificial muscle (PAM) actuated servo systems. The four major processes in such systems, including the flow dynamics, pressure dynamics, force dynamics, and load dynamics, are studied to develop a full nonlinear model that encompasses all the major nonlinearities. The developed single-input-single-output model takes the valve command as the input and calculates the third-order derivative of the load position as the output. Since this model is expressed in the control canonical form, nonlinear control approaches can be easily applied. Based on this model, a sliding model controller is developed to obtain robust control in the existence of model uncertainties and disturbances. The controller is implemented on an experimental system, and the effectiveness of the proposed approach demonstrated by step response and sinusoidal tracking at different frequencies.     

Simultaneous stabilization and trajectory tracking of underactuated mechanical systems with included actuators dynamics

The paper deals with a novel control algorithm for simultaneous stabilization and trajectory tracking of underactuated nonlinear mechanical systems (UNMS) with included actuators dynamics. Simultaneous stabilization and trajectory tracking refer to arbitrary chosen actuated and unactuated degrees of freedom (DOF) of the system. The proposed control approach can be applied both to the second-order nonholonomic systems and the systems with input coupling, while a general model of actuators dynamics includes electrical, pneumatic, and hydraulic drives. Control law is based on linear combination of two control signals, where the first signal is designed to separately control only actuated DOF, and second to separately control only unactuated DOF. Simulation example of rotational inverted pendulum driven by electrical DC motor is presented, showing the effectiveness of the proposed approach.     

Contouring Control for Multi‐Axis Motion Systems With Holonomic Constraints: Theory and Application to a Parallel System

In this paper, the contouring control problem for the constrained multi‐axis motion system is studied. The method of equivalent errors, previously proposed for unconstrained motion systems, is generalized to the system with holonomic constraints. It is shown that the method can be applied to the constrained system provided that the constraints satisfy a proper condition. Because of the constraints, the states in the control law are not completely independent. The unavailable states can be estimated using linear approximation from the constraint equations. As an illustrative example, the proposed method is applied to a parallel motion system with complicated dynamics. A contouring controller is designed using the method of equivalent errors incorporated with integral sliding mode control. Simulation results for contouring circular, elliptic, and square paths verify the effectiveness of the proposed method.     

A robust constrained model predictive control scheme for norm‐bounded uncertain systems with partial state measurements

A robust model predictive control scheme for a class of constrained norm‐bounded uncertain discrete‐time linear systems is developed under the hypothesis that only partial state measurements are available for feedback. The proposed strategy involves a two‐phase procedure. Initialization phase is devoted to determining an admissible, though not optimal, linear memoryless controller capable to formally address the input rate constraint; then, during on‐line phase, predictive capabilities complement the designed controller by means of N steps free control actions in a receding horizon fashion. These additive control actions are obtained by solving semidefinite programming problems subject to linear matrix inequalities constraints. As computational burden grows linearly with the control horizon length, an example is developed to show the effectiveness of the proposed approach for realistic control problems: the design of a flight control law for a flexible unmanned over‐actuated aircraft, where the states of the flexibility dynamics are not measurable, is discussed, and a numerical implementation of the controller within a nonlinear simulation environment testifies the validity of the proposed approach and the possibility to implement the algorithm on an onboard computer.     

Task-level approaches for the control of constrained multibody systems

This paper presents a task-level control methodology for the general class of holonomically constrained multibody systems. As a point of departure, the general formulation of constrained dynamical systems is reviewed with respect to multiplier and minimization approaches. Subsequently, the operational space framework is considered and the underlying symmetry between constrained dynamics and operational space control is discussed. Motivated by this symmetry, approaches for constrained task-level control are presented which cast the general formulation of constrained multibody systems into a task space setting using the operational space framework. This provides a means of exploiting task-level control structures, native to operational space control, within the context of constrained systems. This allows us to naturally synthesize dynamic compensation for a multibody system, that properly accounts for the system constraints while performing a control task. A set of examples illustrate this control implementation. Additionally, the inclusion of flexible bodies in this approach is addressed.     

具有全状态约束和未建模动态的严格反馈系统有限时间自适应动态面控制

针对一类具有全状态约束、未建模动态和动态扰动的严格反馈非线性系统,通过构造非线性滤波器,并利用Young’s不等式,提出一种新的有限时间自适应动态面控制方法.引入非线性映射处理全状态约束,将有约束系统变成无约束系统,利用径向基函数逼近未知光滑函数,利用辅助系统产生的动态信号处理未建模动态.对于变换后的系统,利用改进的动态面控制和有限时间方法设计的控制器结构简单,移去现有有限时间控制中出现的“奇异性”问题,可加快系统的收敛速度.理论分析表明,闭环系统中的所有信号在有限时间内有界,全状态不违背约束条件.数值算例的仿真结果表明,所提出的自适应动态面控制方案是有效的.     

A DAE Approach to Flexible Multibody Dynamics

The present work deals with the dynamics of multibody systems consisting ofrigid bodies and beams. Nonlinear finite element methods are used to devise a frame-indifferent spacediscretization of the underlying geometrically exact beam theory. Both rigid bodies and semi-discrete beams are viewed as finite-dimensional dynamical systems with holonomic constraints. The equations of motion pertaining to the constrained mechanical systems under considerationtake the form of Differential Algebraic Equations (DAEs).The DAEs are discretized directly by applying a Galerkin-based method.It is shown that the proposed DAE approach provides a unified framework for the integration of flexible multibody dynamics.     

Linear dynamics of flexible multibody systems

We consider mechanical systems where the dynamics are partially constrained to prescribed trajectories. An example for such a system is a building crane with a load and the requirement that the load moves on a certain path.Enforcing this condition directly in form of a servo constraint leads to differential-algebraic equations (DAEs) of arbitrarily high index. Typically, the model equations are of index 5, which already poses high regularity conditions. If we relax the servo constraints and consider the system from an optimal control point of view, the strong regularity conditions vanish, and the solution can be obtained by standard techniques.By means of the well-known \(n\)-car example and an overhead crane, the theoretical and expected numerical difficulties of the direct DAE and the alternative modeling approach are illustrated. We show how the formulation of the problem in an optimal control context works and address the solvability of the optimal control system. We discuss that the problematic DAE behavior is still inherent in the optimal control system and show how its evidences depend on the regularization parameters of the optimization.     

A rotationless formulation of multibody dynamics: Modeling of screw joints and incorporation of control constraints

In the present work, a new energy-momentum conserving time-stepping scheme for multibody systems comprising screw joints is developed. In particular, it is shown that the underlying rotationless formulation of multibody dynamics along with a specific coordinate augmentation technique makes possible the energy-momentum discretization of the screw pair. In addition to that, control (or servo) constraints are treated within the rotationless framework of multibody dynamics. The control constraints are used to partially prescribe the motion of a multibody system. In particular, control constraints, in conjunction with the coordinate augmentation technique, make possible to solve inverse dynamics problems by applying the present simulation approach.     

Stabilization of electromechanical systems via interconnection and damping assignment

In this article, we propose a general controller structure for asymptotic position regulation of electromechanical systems derived using the Interconnection and Damping Assignment Passivity‐Based Control methodology recently proposed in the literature. The controller is applicable to arbitrary fully actuated electromechanical systems with linear magnetic materials consisting of inductances, permanent magnets, and one mechanical co‐ordinate. We assume linear magnetic materials and fully actuated electrical dynamics; however, no restrictions are imposed on the particular form of the parameters that define the system dynamics, i.e. the inductance matrix, the magnetic coupling or the potential energy function. This allows us to treat—in a unified framework and without any additional simplifying assumptions—very diverse applications, including magnetic suspensions, and stepper and permanent magnet synchronous motors. Instrumental for our developments is the inclusion of ‘virtual’ couplings between the electrical and the mechanical subsystem, which is naturally suggested in this control methodology. Copyright © 2003 John Wiley & Sons, Ltd.     

Power-constrained intermittent control

In this article, input power, as opposed to the usual input amplitude, constraints are introduced in the context of intermittent control. They are shown to result in a combination of quadratic optimisation and quadratic constraints. The main motivation for considering input power constraints is its similarity with semi-active control. Such methods are commonly used to provide damping in mechanical systems and structures. It is shown that semi-active control can be re-expressed and generalised as control with power constraints and can thus be implemented as power-constrained intermittent control. The method is illustrated using simulations of resonant mechanical systems and the constrained nature of the power flow is represented using power-phase-plane plots. We believe the approach we present will be useful for the control design of both semi-active and low-power vibration suppression systems.     

Index reduction by minimal extension for the inverse dynamics simulation of cranes

The present work deals with the inverse dynamics simulation of underactuated mechanical systems relying on servo constraints. The servo-constraint problem of discrete mechanical systems is governed by differential–algebraic equations (DAEs) with high index. We propose a new index reduction approach, which makes possible the stable numerical integration of the DAEs. The new method is developed in the framework of a specific crane formulation and facilitates a reduction from index five to index three and even to index one. Particular attention is placed on the special case in which the reduced index-1 formulation is purely algebraic. In this case the system at hand can be classified as differentially flat system. Both redundant coordinates and minimal coordinates can be employed within the newly developed approach. The success of the proposed method is demonstrated with two representative numerical examples.     

Generalized discrete-time PI control of output PDFs using square root B-spline expansion

A new control approach is proposed for the probability density function (PDF) control of non-Gaussian stochastic systems using PI controllers. Using the square root output PDF model and the weight dynamics, the PDF tracking is transformed to a constrained dynamical tracking control problem for weight dynamics, where LMI techniques are used to design a generalized PI controller such that stability, state constraints and tracking performances can be guaranteed simultaneously.     

Inter-sample output predictor based sampled-data ADRC supporting high precision control of VCM servo systems

Ultra high precision servo control systems usually require fast sampling rate to achieve desired digital control performance, where output sampling restrictions (such as sensor bandwidth) pose major challenges for such applications. In this paper, we propose a novel sampled-data multi-rate active disturbance rejection control (ADRC) architecture under sampling rate restrictions, where a digital extended state observer (ESO) with inter-sample output prediction structure is employed to construct inter-sample dynamics between two consecutive sampling instants, such that high frequency disturbances can be better rejected. The convergence of the estimation and the stability of the closed-loop system are analyzed based on Lyapunov function method and separation principle. The proposed control architecture is implemented on a voice coil motor (VCM) actuated micro–nano servo gantry, demonstrating significant performance improvement over existing single-rate or multi-rate ADRC methods.     

带状态约束的事件触发积分强化学习控制

为克服全状态对称约束以及控制策略频繁更新的局限,同时使得无限时间的代价函数最优,针对一类具有部分动力学未知的仿射非线性连续系统,提出一种带状态约束的事件触发积分强化学习的控制器设计方法。该方法是一种基于数据的在线策略迭代方法。引入系统转换将带有全状态约束的系统转化为不含约束的系统。基于事件触发机制以及积分强化学习算法,通过交替执行系统转换、策略评估、策略改进,最终系统在满足全状态约束的情况下,代价函数以及控制策略将分别收敛于最优值,并能降低控制策略的更新频率。此外,通过构建李亚普诺夫函数对系统以及评论神经网络权重误差的稳定性进行严格的分析。单连杆机械臂的仿真实验也进一步说明算法的可行性。     

Online constrained optimization based adaptive robust control of a class of MIMO nonlinear systems with matched uncertainties and input/state constraints

A performance oriented two-loop control approach is proposed for a class of multiple-input–multiple-output (MIMO) systems with input saturation, state constraints, matched parametric uncertainties and input disturbances. In the inner loop, a constrained adaptive robust control (ARC) law is synthesized to achieve the required robust tracking performances with respect to on-line replanned trajectory in the presence of input saturation and various types of matched uncertainties. In the outer loop, a replanned trajectory is generated by solving a constrained optimization algorithm online to minimize the converging time of the overall system response to the desired trajectory while not violating various constraints. Interaction of the two loops is explicitly characterized by a set of inequalities that the design variables of each loop have to satisfy. It is theoretically shown that the resulting closed-loop system can track feasible desired trajectories with a guaranteed converging time and steady-state tracking accuracy without violating the state constraints. Since the system in study is most appropriate to describe the dynamics of the robotic systems, the control of a two-axis planar robotic manipulator is used as an application example. Comparative simulation results demonstrate the advantage of the proposed approach over the traditional approaches in practical applications.     

A Nonsmooth Nonlinear Programming Based Predictive Control for Mechanical Servo Systems with Backlash‐like Hysteresis

In this paper, a multi‐step‐ahead predictive control approach for dynamic systems with preceded backlash‐like hysteresis based on nonsmooth nonlinear programming is proposed. In this approach, a nonsmooth multi‐step‐ahead predictive model is developed for long‐range prediction of the controlled dynamic systems with preceded backlash‐like hysteresis. Then, the predictive control strategy is treated as a problem of on‐line nonsmooth nonlinear programming. Subsequently, the stability of the nonsmooth predictive control system is analyzed and the corresponding stability condition is derived. Afterward, a numerical example and a simulation based on a mechanical servo system are presented, respectively.     

Constraint‐admissible sets for systems with soft constraints and their application in model predictive control

Constraint‐admissible sets have been widely used in the study of control systems with hard constraints. This paper proposes a generalization of the maximal constraint‐admissible set for constrained linear discrete‐time systems to the case where soft or probabilistic constraints are present. Defined in the most obvious way, the maximal probabilistic constraint‐admissible set is not invariant. An inner approximation of it is proposed which is invariant and has other nice properties. The application of this approximate set in a model predictive control framework with probabilistic constraints is discussed, including the feasibility and stability of the resulting closed‐loop system. The effectiveness of the proposed approach is illustrated via numerical examples. Copyright © 2011 John Wiley & Sons, Ltd.