Applications of A.I. in control systems
This Paper Presents a case study of an aircraft central system that can tolerate control surface failures using Semantic control theory. In this application, the semantic control system uses system identification and the control mixer concept to exploit the analytical or control redundancy among the control surfaces and thus accommodate the failures. System identification Is performed using artificial intelligence techniques. With this approach unpredictable faults can also be accomodated, which is normally not realized using the conventional techniques.
Surface failure detection and evaluation of control law for reconfiguration of flight control system
The problem of detecting actuator surface failures and evaluating the control law for reconfiguration of flight control systems is considered. The method used for detecting failures is based on tracking error criteria which are developed by considering linear combinations of measured residual tracking errors. The tracking errors are generated using a model of the aircraft multivariable dynamics. Measurement disturbances1 noise are also included and avoidance of false alarms is discussed. The detection and control law, which consists of a control mixer and a compensating signal, evaluation method is demonstrated using a six degree of freedom A-7D Digitac II aircraft model at 0.6 Mach and 15,000 ft. altitude. The simulation results indicate that failure detection can be fast and successful, and false alarms can be avoided by properly modifying the tracking error criteria. The method developed is independent of the feedback control input and therefore the controller of the system can be updated at different failure situations with absolutely no effect on the detection decision making. Aircraft damage in battles or hardware failure may destroy the stability properties of the flight control system and lead to the loss of an aircraft. Even though the control laws can be designed with a certain degree of robustness with respect to uncertainties which may include modeling errors due to failures, such errors have to be small enough for stability and acceptable performance. When a primary surface becomes inoperative due to combat damage or mechanical failure, the control laws may no longer effectively exploit the resulting control power and therefore may lead to instability. One way to improve safety-of-flight reliability is to add redundant hardware. The extra hardware, however, not only adds additional cost but also increases maintenance activity. A more efficient way to deal with reliability in case of surface failures is to use the redundant control effectors, which are present (for performance reasons) in most newer aircraft, to distribute the forces and moments of the failed surfaces to the remaining healthy control surfaces. Thus the objective of such reconfigaration is to take advantage of the existing redundancy and produce the forces and moments acting on the aircraft without requiring the addition of redundant hardware. This approach will increase the survivability of the flight control system and at the same time reduce support requirements. The purpose of this paper is to develop a system impairment detection (SID) scheme which will detect and *~epar tment of Electrical Engineering, University of Southern California. t* Lockheed Aeronautical System Company, Member AIAA. classify the type of surface failures and a control reconfiguration (CR) scheme to distribute the control power to the healthy control surfaces. The SID scheme consists of a detection error model (DEM) and a failure classification model (FCM). The DEM is developed by using an observer type model for the aircraft dynamics to generate error signals and a similarity transformation is used so that each transformed error signal is affected by only one control surface. By monitoring each error signal we can detect individual surface failures and proceed by inputing this information to the FCM which will decide about the type of failure, i.e., whether the surface is partially missing, stuck or floating. The CR scheme is based on the control mixer approach [1,2,3] and the use of a compensating input signal to accommodate the surface failures. The compensating signal is needed when the impaired surface leads to a non-zero input to the aircraft. The error criteria are modified in the presence of noise in order to avoid false alarms. The higher the noise level, the longer the detection time of the failure. Our methodology is applied to a six degree of freedom A-7D Digitac II aircraft model at a cruise configuration of 0.6 Mach, angle of attack at 4.2O and flying at 15 K feet [4]. The simulation results presented in section 4 demonstrate the effectiveness of the proposed approach. In all cases surface failures were accommodated successfully. In this paper we assume that the parameters of the aircraft model are fixed and known. The more realistic situation where the parameters are time-varying and unknown [5,6] is presently under investigation. 2. Failure Detection Scheme The block diagram of the failure detection scheme and control reconfiguration scheme is shown below: SID scheme CR scheme I Compensating Signal d 1 1
Parboiled rice effluent: A wastewater niche for microalgae and cyanobacteria with growth coupled to comprehensive remediation and phosphorus biofertilization
Abstract The potential of microalgae and cyanobacteria for bioremediation of wastewater by nutrient uptake combined with simultaneous biomass production is a well recognized perception of today's world. The present study illustrates the treatment of a highly polluted wastewater generated during parboiling of paddy in rice mill industries, widely operational in developing countries where rice is the staple food crop, with the help of microalgal and cyanobacterial isolates capable of growing at high rates in parboiled rice mill effluent (RME). This endeavor leads to comprehensive bioremediation of the said effluent and subsequent use of the harvested biomass as slow release phosphorus biofertilizers and the treated effluent for crop irrigation. The RME-acclimatized algal consortium demonstrated highest growth in terms of fresh weight and greatest remediation efficiency at the end of 36 days' treatment of RME, with 93.9% phosphorus and 100% ammonia-nitrogen removal, 98.7%, 91.6% and 93.5% reduction in biological oxygen demand, chemical oxygen demand and total dissolved solid, respectively, and an increment of 186 ± 0.3 mg L − 1 dissolved oxygen, bringing down the pollutants level well below the discharge limits suggested by Central Pollution Control Board, India. Additionally, microalgae in the consortium aggregated in clumps spontaneously in presence of the filaments of Phormidium sp. facilitating easy harvest. The RME-acclimatized algal consortium demonstrated highest accumulation of polyphosphate (poly-P) (0.76 ± 0.01% of dry weight) as well as highest release of phosphorus in non-sterile soil emphasizing the essential role of soil phosphorus solubilizing organisms to leach soluble phosphorus from the insoluble poly-P present in the biomass. The rice seedlings watered with treated RME also showed improved growth effect on shoot height and leaf width. The study results establish the suitability of RME as an excellent growth media for microalgae and cyanobacteria.