Distributed Extremum Seeking Control for a Variable Refrigerant Flow System

The variable refrigerant flow (VRF) technology has facilitated the development of multi-split ductless air conditioning systems, in which multiple indoor units (IDU) are used to regulate the refrigerant flow to achieve individualized zoning control. Model based control for VRF system demands for more modeling efforts in part due to diverse configuration, as well as changes in load and ambient conditions. As a model-free control strategy, Extremum Seeking Control (ESC) has been investigated for VRF systems. Dong et al. (2015) applied the standard centralized ESC scheme to a VRF system that consists of one outdoor unit (ODU) and four IDU’s. Simulation results have indicated the effectiveness of such strategy. As the number of IDU’s increases, the complexity of centralized controllers will increase accordingly. Therefore distributed ESC becomes a natural consideration for VRF systems with large number of IDU’s. In this paper, the Shashahani gradient based distributed ESC scheme proposed by Poveda and Quijano (2013, 2015), is applied to the four-zone VRF system simulated by Dong et al. (2015). In particular, this scheme is enhanced by appending a band-pass filter array at the output to achieve a better “isolation†among individual input channels. A single-input ESC is applied to the ODU, while the distributed ESC is applied to the four IDU’s with each acting as an agent. For each agent, the respective power consumption is used as feedback. The objective is to minimize the total power consumption of all agents. For the ODU ESC, the compressor suction pressure (PCS) set-point is employed as the manipulative input. For the IDU DESC, the evaporator superheat (SH) set-point is used as the manipulative input for each IDU agent. The distributed ESC scheme assumes full information communication among all IDU’s. Simulation study is performed to evaluate the proposed strategy with the Modelica based dynamic simulation model developed by Dong et al. (2015). The ESC is designed under the ambient condition of 35oC and 40 %RH, respectively. The initial temperature of all four IDUs zone is 29oC, and the zone temperature set-point is 26oC. The heat loads for IDU1 through IDU4 are 3000W, 2600W, 2400W and 2000W, respectively. It takes the average total power about 10000 seconds to converge to about 3200W in steady state, with PCS around 13bar, and the SH values of IDU1 through IDU4 at 4.5oC, 4.5oC, 6oC, and 5.5oC, respectively. The total power consumption was decreased from 4500 W to 3200 W, i.e. by 29%. In comparison with the centralized ESC Dong et al. (2015), the steady state error of total power is less than 50w. Work is under way to improve transient and steady-state performance, as well as simulation of other operation modes.  Â

A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Extremum Seeking Based Fault-Tolerant Cooperative Control for Multiagent Systems

We propose a novel fault-tolerant cooperative control strategy for multiagent systems. A set of unknown input observers for each agent are constructed for fault detection. Then a real-time adaptive extremum seeking algorithm is utilized for adaptive approximation of fault parameter. We prove that the consensus can be still reached by regulating the interconnection weights and changing the connection topology of the fault agent. A numerical simulation example is given to illustrate the feasibility and effectiveness of the proposed method

CONTROL AND ESTIMATION ALGORITHMS FOR MULTIPLE-AGENT SYSTEMS

Tese arquivada ao abrigo da Portaria nº 227/2017 de 25 de julhoIn this thesis we study crucial problems within complex, large scale, networked control systems and mobile sensor networks. The ¯rst one is the problem of decomposition of a large-scale system into several interconnected subsystems, based on the imposed information structure constraints. After associating an intelligent agent with each subsystem, we face with a problem of formulating their local estimation and control laws and designing inter-agent communication strategies which ensure stability, desired performance, scalability and robustness of the overall system. Another problem addressed in this thesis, which is critical in mobile sensor networks paradigm, is the problem of searching positions for mobile nodes in order to achieve optimal overall sensing capabilities. Novel, overlapping decentralized state and parameter estimation schemes based on the consensus strategy have been proposed, in both continuous-time and discrete-time. The algorithms are proposed in the form of a multi-agent network based on a combination of local estimators and a dynamic consensus strategy, assuming possible intermittent observations and communication faults. Under general conditions concerning the agent resources and the network topology, conditions are derived for the stability and convergence of the algorithms. For the state estimation schemes, a strategy based on minimization of the steady-state mean-square estimation error is proposed for selection of the consensus gains; these gains can also be adjusted by local adaptation schemes. It is also demonstrated that there exists a connection between the network complexity and e±ciency of denoising, i.e., of suppression of the measurement noise in°uence. Several numerical examples serve to illustrate characteristic properties of the proposed algorithm and to demonstrate its applicability to real problems. Furthermore, several structures and algorithms for multi-agent control based on a dynamic consensus strategy have been proposed. Two novel classes of structured, overlapping decentralized control algorithms are presented. For the ¯rst class, an agreement between the agents is implemented at the level of control inputs, while the second class is based on the agreement at the state estimation level. The proposed control algorithms have been illustrated by several examples. Also, the second class of the proposed consensus based control scheme has been applied to decentralized overlapping tracking control of planar formations of UAVs. A comparison is given with the proposed novel design methodology based on the expansion/contraction paradigm and the inclusion principle. Motivated by the applications to the optimal mobile sensor positioning within mobile sensor networks, the perturbation-based extremum seeking algorithm has been modifed and extended. It has been assumed that the integrator gain and the perturbation amplitude are time varying (decreasing in time with a proper rate) and that the output is corrupted with measurement noise. The proposed basic, one dimensional, algorithm has been extended to two dimensional, hybrid schemes and directly applied to the planar optimal mobile sensor positioning, where the vehicles can be modeled as velocity actuated point masses, force actuated point masses, or nonholonomic unicycles. The convergence of all the proposed algorithms, with probability one and in the mean square sense, has been proved. Also, the problem of target assignment in multi-agent systems using multi-variable extremum seeking algorithm has been addressed. An algorithm which e®ectively solves the problem has been proposed, based on the local extremum seeking of the specially designed global utility functions which capture the dependance among di®erent, possibly con°icting objectives of the agents. It has been demonstrated how the utility function parameters and agents' initial conditions impact the trajectories and destinations of the agents. All the proposed extremum seeking based algorithms have been illustrated with several simulations