Active Inference for Integrated State-Estimation, Control, and Learning

This work presents an approach for control, state-estimation and learning model (hyper)parameters for robotic manipulators. It is based on the active inference framework, prominent in computational neuroscience as a theory of the brain, where behaviour arises from minimizing variational free-energy. The robotic manipulator shows adaptive and robust behaviour compared to state-of-the-art methods. Additionally, we show the exact relationship to classic methods such as PID control. Finally, we show that by learning a temporal parameter and model variances, our approach can deal with unmodelled dynamics, damps oscillations, and is robust against disturbances and poor initial parameters. The approach is validated on the `Franka Emika Panda' 7 DoF manipulator.Comment: 7 pages, 6 figures, accepted for presentation at the International Conference on Robotics and Automation (ICRA) 202

A Unified Framework for the Study of Anti-Windup Designs

We present a unified framework for the study of linear time-invariant (LTI) systems subject to control input nonlinearities. The framework is based on the following two-step design paradigm: "Design the linear controller ignoring control input nonlinearities and then add anti-windup bumpless transfer (AWBT) compensation to minimize the adverse eflects of any control input nonlinearities on closed loop performance". The resulting AWBT compensation is applicable to multivariable controllers of arbitrary structure and order. All known LTI anti-windup and/or bumpless transfer compensation schemes are shown to be special cases of this framework. It is shown how this framework can handle standard issues such as the analysis of stability and performance with or without uncertainties in the plant model. The actual analysis of stability and performance, and robustness issues are problems in their own right and hence not detailed here. The main result is the unification of existing schemes for AWBT compensation under a general framework

Modelling the robustness properties of HVAC plant under feedback control

Most existing building simulation programs fail to capture sufficient of the underlying dynamics of nonlinear HVAC plant and some have restricted room space modelling capabilities for low-time-horizon analyses. In this work, a simplified model of a room space with hot water heating and a chilled ceiling system is developed for the main purpose of analysing control system response. The room model is based on a new approach to lumped capacitance modelling and the heating and chilled ceiling emitters are modelled using third-order descriptions. Control system components are treated in detail and both controllers are ‘tuned’ at a nominal region of plant operation using a gradient-descent-based optimization procedure. Robustness qualities of the controllers are analysed with reference to extremes in plant operating conditions. A key feature of the work is the transparency of the modelling procedure, designed to have appeal to researchers as well as practitioners involved with HVAC control system design problems

Maximum Peak-Gain Margin 2DOF-IMC Tuning for a 2DOF-PID Filter Set Point Controller Under Parametric Uncertainty

The specification of controller setting for a standard controller typically requires a trade-off between set point tracking and disturbance rejection. For this reason two simple strategies can be used to adjust the set point and disturbance responses independently. These strategies are referred to as controllers with two degree of freedom. Unfortunately, the tuning parameters in the case of model uncertainty at two degree of freedom structure controller is difficult to obtain. Juwari et al (2013) has introduced maximum peak-gain margin (Mp-GM) tuning method to obtain setting parameter of two degree of freedom structure controller based on model uncertainty. This tuning method are able to obtain the good controller parameter even under processes uncertainties on standard two degree of freedom (was abbreviated as 2DOF) IMC. This research will be conducted on development maximum peak-gain margin tuning method for a two degree of freedom PID filter set point structure controller. The simulation results show that the maximum peak gain margin tuning method can give a good target set point tracking, disturbance rejection and robustness in system a 2DOF-PID filter set point controller