Optimal Tracking Control of Multi-Zone Indoor Environmental Spaces

1995 ◽  
Vol 117 (3) ◽  
pp. 292-303 ◽  
Author(s):  
M. Zaheer-uddin ◽  
R. V. Patel
Keyword(s):  
Optimal Control ◽  
Tracking Control ◽  
Control Law ◽  
Closed Loop System ◽  
Order Model ◽  
Fast Subsystem ◽  
Reduced Order ◽  
Optimal Tracking ◽  
Optimal Tracking Control ◽  
Slow Subsystem

Optimal control of indoor environmental spaces is explored. A physical model of the system consisting of a heating system, a distribution system and an environmental zone is considered and a seventh order bilinear system model is developed. From the physical characteristics and open-loop response of the system, it is shown that the overall system consists of a fast subsystem and a slow subsystem. By including the effects of the slow subsystem in the fast subsystem, a reduced order model is developed. An optimal control law is designed based on the reduced order model and it is implemented on the full order nonlinear system. Both local and global linearization techniques are used to design optimal control laws. Results showing the disturbance rejection characteristics of the resulting closed-loop system are presented. The use of optimal tracking control to implement large changes in setpoints, in a prescribed manner, is also examined. A general model to describe environmental zones is proposed and its application to multi-zone spaces is illustrated. A multiple-input optimal tracking control law with output error integrators is designed. The resulting closed-loop system response to step-like disturbances is shown to be good.

scholarly journals Online Optimal Control of Robotic Systems with Single Critic NN-Based Reinforcement Learning

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Xiaoyi Long ◽  
Zheng He ◽  
Zhongyuan Wang
Keyword(s):  
Optimal Control ◽  
Reinforcement Learning ◽  
Tracking Control ◽  
Learning Algorithm ◽  
Tracking Error ◽  
Adaptive Dynamic Programming ◽  
Robotic Systems ◽  
Control Synthesis ◽  
Optimal Tracking ◽  
Optimal Tracking Control

This paper suggests an online solution for the optimal tracking control of robotic systems based on a single critic neural network (NN)-based reinforcement learning (RL) method. To this end, we rewrite the robotic system model as a state-space form, which will facilitate the realization of optimal tracking control synthesis. To maintain the tracking response, a steady-state control is designed, and then an adaptive optimal tracking control is used to ensure that the tracking error can achieve convergence in an optimal sense. To solve the obtained optimal control via the framework of adaptive dynamic programming (ADP), the command trajectory to be tracked and the modified tracking Hamilton-Jacobi-Bellman (HJB) are all formulated. An online RL algorithm is the developed to address the HJB equation using a critic NN with online learning algorithm. Simulation results are given to verify the effectiveness of the proposed method.

Model Simplification and Stability Robustness With Elastic Flight Vehicles

1995 ◽  
Vol 117 (3) ◽  
pp. 336-342
Author(s):  
Brett Newman ◽  
David K. Schmidt
Keyword(s):  
Closed Loop ◽  
Order Reduction ◽  
Higher Order ◽  
Reduced Order Model ◽  
Control Law ◽  
Model Simplification ◽  
Closed Loop System ◽  
Order Model ◽  
Reduced Order ◽  
Stability Robustness

Quantitative criteria are presented for model simplification, or order reduction, such that the reduced order model may be used to synthesize and evaluate a control law, and the stability and stability robustness obtained using the reduced order model will be preserved when controlling the higher order system. The error introduced due to model simplification is treated as modeling uncertainty, and some of the results from multivariable robustness theory are brought to bear on the model simplification problem. Also, the importance of the control law itself, in meeting the modeling criteria, is underscored. A weighted balanced order reduction technique is shown to lead to results that meet the necessary criteria. The procedure is applied to an aeroelastic vehicle model, and the results are used for control law development. Critical robustness properties designed into the lower order closed-loop system are shown to be present in the higher order closed-loop system.

Optimal Tracking Control for Discrete-time Systems with Time-delay Based on the Preview Control Method

2019 ◽  
Vol 7 (5) ◽  
pp. 452-461
Author(s):  
Haishan Xu ◽  
Fucheng Liao
Keyword(s):  
Optimal Control ◽  
Time Delay ◽  
Discrete Time ◽  
Tracking Control ◽  
Control Method ◽  
Reference Signal ◽  
Control Law ◽  
Preview Control ◽  
Optimal Tracking ◽  
Delayed System

Abstract In this paper, the optimal tracking control problem for discrete-time with state and input delays is studied based on the preview control method. First, a transformation is introduced. Thus, the system is transformed into a non-delayed system and the tracking problem of the time-delay system is transformed into the regulation problem of a non-delayed system via processing of the reference signal. Then, by applying the preview control theory, an augmented system for the non-delayed system is derived, and a controller with preview function is designed, assuming that the reference signal is previewable. Finally, the optimal control law of the augmented error system and the optimal control law of the original system are obtained by letting the preview length of the reference signal go to zero.

Dynamic Walk of a Quadruped Locomotion Robot Using Robust Optimal Tracking Control

1995 ◽  
Author(s):  
Hiroaki Uchida ◽  
Kenzo Nonami
Keyword(s):  
Optimal Control ◽  
High Frequency ◽  
Tracking Control ◽  
Control Method ◽  
Reaction Force ◽  
The Body ◽  
High Frequency Vibration ◽  
Quadruped Locomotion ◽  
Optimal Tracking ◽  
Optimal Tracking Control

Abstract We propose a new control system design strategy that is called “frequency-shaped optimal tracking control method” in this paper. We make sure that the proposed method is very useful by creating the quasi-dynamic walk of a quadruped locomotion robot. During control of the locomotion robot, high feedback (FB) gains should be selected to work against the force and the moment from the body and the reaction force from the ground. However, if high FB gains are used, high frequency vibration comes out because of the backlash of the gear. Frequency-shaped optimal control is the control method to improve the robustness against the disturbance like high frequency vibration. Frequency-shaped optimal tracking control extends the frequency-shaped optimal control to the servo system like the trajectory following control of the robot. First, we’ll show the design scheme of the frequency-shaped optimal tracking control. Next, we’ll show how decentralized control is realized in order to apply frequency-shaped optimal tracking control. Finally, we’ll compare the frequency-shaped optimal tracking control with the optimal tracking control from the points of view of the simulations and the experiments.

scholarly journals Robust Optimal Tracking Control of a Full-Bridge DC-AC Converter

2021 ◽  
Vol 11 (3) ◽  
pp. 1211
Author(s):  
En-Chih Chang ◽  
Chun-An Cheng ◽  
Rong-Ching Wu
Keyword(s):  
Steady State ◽  
Digital Signal Processor ◽  
Tracking Control ◽  
Harmonic Distortion ◽  
Digital Signal ◽  
Fast Convergence ◽  
Solution Quality ◽  
Hybrid Strategy ◽  
Optimal Tracking ◽  
Optimal Tracking Control

This paper develops a full-bridge DC-AC converter, which uses a robust optimal tracking control strategy to procure a high-quality sine output waveshape even in the presence of unpredictable intermissions. The proposed strategy brings out the advantages of non-singular fast convergent terminal attractor (NFCTA) and chaos particle swarm optimization (CPSO). Compared with a typical TA, the NFCTA affords fast convergence within a limited time to the steady-state situation, and keeps away from the possibility of singularity through its sliding surface design. It is worth noting that once the NFCTA-controlled DC-AC converter encounters drastic changes in internal parameters or the influence of external non-linear loads, the trembling with low-control precision will occur and the aggravation of transient and steady-state performance yields. Although the traditional PSO algorithm has the characteristics of simple implementation and fast convergence, the search process lacks diversity and converges prematurely. So, it is impossible to deviate from the local extreme value, resulting in poor solution quality or search stagnation. Thereby, an improved version of traditional PSO called CPSO is used to discover global optimal NFCTA parameters, which can preclude precocious convergence to local solutions, mitigating the tremor as well as enhancing DC-AC converter performance. By using the proposed stable closed-loop full-bridge DC-AC converter with a hybrid strategy integrating NFCTA and CPSO, low total harmonic distortion (THD) output-voltage and fast dynamic load response are generated under nonlinear rectifier-type load situations and during sudden load changes, respectively. Simulation results are done by the Matlab/Simulink environment, and experimental results of a digital signal processor (DSP) controlled full-bridge DC-AC converter prototype confirm the usefulness of the proposed strategy.

Sign in / Sign up

Export Citation Format

Share Document