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Sliding Mode Observer based Antilock Braking Patents for Aircraft and Heavy Land Vehicles    

Patented Antilock Brake System (ABS) Employing a Sliding Mode Observer Estimate of Differential Wheel Torque.


This is a patented antilock brake system employing a sliding mode observer based estimate of differential wheel torque with applications to aircraft, rail and heavy land vehicle braking. “Sliding mode observer” is a term from modern estimation and control theory. An SMO is a very robust way for estimating the state variables of a linear or non-linear dynamic system. It can do this with a much less complete mathematical model than its cousin the Kalman Filter, also used in some ABS applications. What “slides” in a SMO is the state estimate's trajectory along a plane in “state space” as it converges to the true state. An SMO based ABS provides more robust control of braking than simple individual wheel speed or comparative wheel speed based braking schemes. The SMO outputs an analytical estimate of the differential wheel torque (runway-braking/tire-drag torque minus the applied wheel brake torque). It implements this in a much simpler manner than using other analytical methods such as a Kalman filters and with fewer measurements, typically only wheel speed.

The patented antilock brake system works with hydraulic, pneumatic or electric brakes. It does not require direct estimation of the wheel slip or advance knowledge of the optimal wheel slip, or runway, rail, or road surface condition. Further it can adapt automatically to changing surface conditions (slippery/dry). The brake controller simply needs to continuously maximize the estimate of differential brake torque from the, appropriately filtered, filtered SMO output.

Primary Application of the Technology

A SMO based ABS is applicable to braking any dynamic system even those having an inexact analytical model. There is no need to add “plant noise” to cover up model uncertainties as with a Kalman Filter. An SMO based ABS will tolerate large uncertainties in the model parameters and or non-linear dynamics. The SMO is especially suited to real-time ABS of transport aircraft and heavy ground vehicles (trucks, locomotives and railcars) and requires only a single state variable as opposed to multiple state variables with a Kalman filter. It may even be extended to optimal braking of rotating but stationary machinery.

The Problem Solved by the Technology

Prevents skidding on runways during landing. Adapts automatically to changing runway conditions. Can be used alone or to augment existing on-board anti-skid algorithms such as ones based on heuristics or even employing Kalman filtering.

How the Technology Solves the Problem

A SMO based ABS forces braking to be such that operation is about the peak mu (friction coefficient) of a mu-slip curve for each braked wheel or group of wheels. There is no need to assume an "optimal wheelslip" and then try and regulate the wheel slip measured to this value. The braking surface condition, and hence the optimal slip corresponding to the peak mu, can vary during the braking such as with an aircraft landing on a partially snow covered runway.

Competitive Advantage

See Preceding. The '041 patent was filed as a Provisional in February 2001. This was some 10 months before a patent with similar claims was filed by Crane Aerospace

Comments on Deal Structure, Potential Terms and Restrictions


Frequently Asked Questions

By sliding mode do we mean the vehicle is already sliding along the runway/rail/road surface before braking starts?
By an SMO based ABS we do not mean that the required wheel speed or other measurements are made while the aircraft or heavy land vehicle is skidding/sliding along the runway or roadway.

Are there any back-up braking modes?
In the rare event of a sudden deep skid such as encountering a patch of ice on an otherwise dry surface conventional wheel speed change based back-up logic is typically overlaid on the SMO algorithm to immediately reduce the available wheel brake torque. This has all been thoroughly simulated in hundreds of MATLAB based simulations as well as in actual Hardware in the Loop tests at at least one company we worked with.

Patent Summary

U.S. Patent Classes & Classifications Covered in this listing:

Class 303: Fluid-Pressure And Analogous Brake Systems

The distribution of fluid to brake motors, i.e., the utilization of fluid-pressure in the operation of brakes.

Subclass 126: Aircraft
Subclass 147: From speed sensors
Subclass 148: From split coefficient of friction (mu)
Subclass 149: Split coefficient of friction (mu)
Subclass 150: Specific mu determination
Subclass 153: Lead signal control for antiskid
Subclass 154: Multiple control signal with multiple threshold
Subclass 167: Brake force or pressure determined from speed sensors
Subclass 188: All wheel apportioning arrangement (e.g., cross coupling)
Subclass 112: Torque sensing