•A new damper, which can achieve different damping modes, is applied to vehicle suspension.•The hybrid dynamics of the air suspension with the new damper are modeled using MLD systems.•The optimal ...control of the switching sequences of the damping modes is achieved by MPC method.
This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPUK, ZRSKP
Mathematical modeling of the crowd behavior is inevitable for evaluating the safety and comfort of social systems. In this study, we focus on a dynamical flow model of the crowd behavior, which ...reflects the subjective behavior of the pedestrians in the crowd, and construct a pedestrian flow model of the route-selection introducing the effect of subjective satisfaction. The features of the proposed model are investigated based on the simulation of pedestrian flows with route selection.
This paper proposes a cruise control for a two-wheeled mobile vehicle on a two-dimensional plane. The cruise control is executed using model predictive control (MPC), such that input and state ...constraints can be addressed explicitly. For real-time execution of MPC, we model the dynamics of the vehicle as a mixed logical dynamical system rather than an underlying nonlinear model. The cruise control is then reduced to a mixed integer quadratic programming problem, for which efficient solvers using the convexities are available. Simulations and experiments demonstrate the effectiveness of the proposed cruise control through a computation time comparison with the nonlinear MPC method.
This paper considers a velocity control problem for merging and splitting maneuvers of vehicle platoons. In this paper, an external device sends velocity commands to some vehicles in the platoon, and ...the others adjust their velocities autonomously. The former is pinning control, and the latter is consensus control in multi-agent control. We propose a switched pinning control algorithm. Our algorithm consists of three sub-methods. The first is an optimal switching method of pinning agents based on an MLD (Mixed Logical Dynamical) system model and MPC (Model Predictive Control). The second is a representation method for dynamical platoon formation with merging and splitting maneuver. The platoon formation follows the positional relation between vehicles or the formation demand from the external device. The third is a switching reduction method by setting a cost function that penalizes the switching of the pinning agents in the steady-state. Our proposed algorithm enables us to improve the consensus speed. Moreover, our algorithm can regroup the platoons to the arbitrary platoons and control the velocities of the multiple vehicle platoons to each target value.
A wireless sensor and actuator network (WSAN) is a class of networked control systems. In WSANs, sensors and actuators are located in a distributed way, and communicate to controllers through a ...wireless communication network such as a multi-hop network. In this paper, we propose a model predictive control (MPC) method for co-design of control and routing of WSANs. MPC is an optimal control strategy based on numerical optimization. The control input is calculated by solving the finite-time optimal control problem at each discrete time. In the proposed method, a WSAN is modeled by a switched linear system. In the finite-time optimal control problem, a control input and a mode corresponding to a communication path are optimized simultaneously. The proposed method is demonstrated by a numerical example.
Control of multi-agent systems is one of the central problems in control theory. In this paper, we study the optimal monitoring (surveillance) problem over a graph. This problem is to find ...trajectories of multiple agents that travel each node as evenly as possible, and can be applied to several applications such as city safety management and disaster rescue. In our previous work, the finite-time optimal monitoring problem was formulated, and was reduced to a mixed integer linear programming (MILP) problem. Based on the policy of model predictive control, an optimal trajectory is generated by solving the MILP problem at each discrete time. However, the computation time for solving the MILP problem is frequently long. In this paper, to reduce the computation time, we introduce the policy of time sequence-based modeling. In the proposed method, the adjacency relation of a given graph is time varying depending on the current locations of agents. Since the unnecessary arcs are eliminated, the computation time is improved. The effectiveness of the proposed method is demonstrated by numerical examples.
Many controllers are implemented on digital platforms as periodic control tasks. But, in embedded systems, an amount of resources are limited and the reduction of resource utilization of the control ...task is an important issue. Recently, much attention has been paid to a self-triggered controller, which updates control inputs aperiodically. A control task by which the self-triggered controller is implemented skips the release of jobs if the degradation of control performances by the skipping can be allowed. Each job computes not only the updated control inputs but also the next update instant and the control task is in the sleep state until the instant. Thus the resource utilization is reduced. In this paper, we consider self-triggered predictive control (stPC) of mixed logical dynamical (MLD) systems. We introduce a binary variable which determines whether the control inputs are updated or not. Then, we formulate an stPC problem of mixed logical dynamical systems, where activation costs are time-dependent to represent the preference of activations of the control task. Both the control inputs and the next update instant are computed by solving a mixed integer programming problem. The proposed stPC can reduce the number of updates with guaranteeing stability of the controlled system.
PDF
