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Control by interconnection (CbI) is a dynamic output-feedback approach used to control port-Hamiltonian (PH) systems. Here, both the plant and the controller are modelled in PH form, in terms of their own Hamiltonians. However, obtaining an appropriate controller Hamiltonian is generally difficult. In this paper, we address this issue by using reinforcement learning (RL). Additionally due to the semi-supervised...
In many practical applications, it is not feasible to measure a large number of variables. Therefore, strategies are required to enhance fault diagnosis, given the available monitoring signals. In this paper, we consider fault diagnosis in networks using a limited number of monitoring signals. We propose to use spatial dependencies between the monitoring data of the subsystems to discriminate between...
This paper introduces an approximate analytical solution to the otherwise non-integrable double-stance dynamics of the bipedal spring-loaded inverted pendulum (SLIP). Despite the apparent structural simplicity of the SLIP, the exact analytical solution to its stance dynamics cannot be found. Approximate maps have been proposed for the monoped SLIP runner (encompassing a single-stance phase). Still,...
The autonomous capabilities of light-weight Flapping Wing Micro Air Vehicles (FWMAVs) have much to gain from onboard state estimation and attitude control. In this article, we present the first FWMAV with robust onboard state estimation and attitude control. The tailed FWMAV DelFly II was used, with the main goal to achieve active stabilization in the (passively unstable) hover condition. The attitude...
Three nonlinear predictive control algorithms were applied in simulation to a MIMO waste-water treatment process. Two algorithms are based on instantaneous linearization of the nonlinear prediction model and one is based on a branch-and-bound search technique. The prediction model employed is a fuzzy model of the Takagi-Sugeno type. The performance of the controllers is compared in terms of setpoint...
An overview of nonlinear predictive control based on neural and fuzzy models is given. The similarities and differences of these two modeling approaches are discussed, as well as their advantages and drawbacks. Several optimization approaches within the predictive controller based on these nonlinear model structures are reviewed, including iterative methods, operating-point and feedback linearization,...
A model predictive approach to the control of a GDI engine is presented. Fuzzy Takagi-Sugeno type models are used to predict the future engine behaviour. The optimization algorithm is based on instantaneous linearization of the nonlinear prediction model at the current operating point. Special mode switching strategies are designed to minimize the torque bumps during combustion mode changes. The performance...
For naturally distributed systems, such as multiagent systems, the construction and tuning of a centralized observer may be computationally expensive or even intractable. An important class of distributed systems can be represented as cascaded subsystems. For this class of systems, observers may be designed separately for the subsystems. If the subsystems are linear, the Kalman filter provides an...
In this paper, an adaptive friction compensation scheme is proposed. The friction force is computed as a time-varying friction coefficient multiplied by the sign of the velocity and an online update law is designed to estimate this coefficient based on the actual position and velocity errors. Furthermore, a modified signum function definition is proposed to better capture the behavior of friction...
Legged robots are intrinsically nonlinear hybrid dynamic systems due to the intermittent contact of the feet with the ground. For optimal performance, in the sense of maximizing speed or energy consumption, different motion control affects the stance from the swing leg during a stride. Designing such controllers, however, can be a daunting task when there is a lack of knowledge about the exact operating...
Maintaining postural balance is a fundamental requirement for humanoid robots faced with unknown terrain or external perturbations. In this paper we present an observer-based balancing control strategy that is robust to persistent perturbations on the ground slope which is based on the estimation of the disturbance without the need for an inertial measurement unit. We use the workspace control method...
In this research, time optimal control is considered for the hit motion of a badminton robot during a serve operation. For this task the racket always starts at rest in a given position and has to move to a target state, defined by a target position and a non-zero target velocity. The goal is to complete this motion in as little time as possible, yet without violating bounds on the actuator. To find...
In this paper we address the identification of linear distributed-parameter systems with missing data. This setting is relevant in, for instance, sensor networks, where data are frequently lost due to transmission errors. We consider an identification problem where the only information available about the system are the input-output measurements from a set of sensors placed at known fixed locations...
Recently, adaptive fuzzy observers have been introduced that are capable of estimating uncertainties along with the states of a nonlinear system represented by an uncertain Takagi-Sugeno (TS) model. In this paper, we use such an adaptive observer to estimate the uncertainties in the state matrices of a two-degrees-of-freedom robot arm model. The TS model of the robot arm is constructed using the sector...
In this paper, an optimal scheduler for a printer is presented. The scheduling is based on the max-plus modeling framework. It allows to model scheduling of multiple sheets as discrete events in a system described by max-plus linear statespace equations. The optimal scheduler uses the feeding and handling time of each sheet as the design variables. It is shown that the proposed method successfully...
Various applications in scheduling, such as train timetables and multi-legged locomotion, can be modeled using systems of max-plus linear equations. In this framework, the eigenvalue of the system matrix represents the total cycle time, whereas the eigenvector dictates the steady-state behavior. For a class of concurrent two-state cyclic systems, with direct application to legged locomotion, we present...
Switching gaits in many-legged robots can present challenges due to the combinatorial nature of the gait space. In this paper we present an intrinsically safe gait switching generator that minimizes the velocity variance of all the legs in stance, allowing for smooth acceleration in legged robots. The gait switching generator is modeled as a max-plus linear discrete event system which is translated...
Switching gaits in many-legged robots can present challenges due to the combinatorial nature of the gait space. In this paper we present an intrinsically safe gait switching generator that minimizes the velocity variance of all the legs in stance, allowing for smooth acceleration in legged robots. The gait switching generator is modeled as a max-plus linear discrete event system which is translated...
In this paper we compare four methods for decentralized Kalman filtering for distributed-parameter systems, which after spatial and temporal discretization, result in large-scale linear discrete-time systems. These methods are: parallel information filter, distributed information filter, distributed Kalman filter with consensus filter, and distributed Kalman filter with weighted averaging. These filters...
This paper reviews different observer design methods for linear dynamic distributed-parameter systems. In such systems, the states, inputs, and outputs depend on some spatial variable. This dependence, along with additional aspects such as the boundary conditions, increase the complexity of the state estimation problem and of the design methods. The paper in particular surveys observers for first-order...
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