Aircraft Actuator Allocation Under Failure and Input Saturation
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Solution Overview
Problem
Multiactuator aerial vehicles face challenges in controlling actuator systems when actuator malfunctions or failures occur, leading to incomplete fulfillment of desired control tasks due to under-actuation or over-determination.
Innovation Solution
A method for controlling actuator systems using an allocation equation with inverse matrix computation and state feedback control, prioritizing control inputs based on actuator capacity and system state to ensure stable operation even when actuators reach their limits, employing a prioritization algorithm to adjust control inputs and maintain system stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all actuators are controlled to achieve desired control tasks, then control performance is improved, but system reliability deteriorates when actuator failures occur
Solution Approach 1:
The control allocation system dynamically adapts its structure based on actuator status. When actuators fail, the system transitions from controlling all actuators to controlling only functional actuators, with the controller configuration changing in real-time to maintain stability while accommodating the reduced actuator set
Solution Approach 2:
The system changes control parameters (control allocation matrix, system matrices) based on actuator failure conditions. By detecting actuator status and adjusting the control allocation parameters accordingly, the system maintains optimal control performance across different operational states without requiring complete redesign for each failure scenario
2Manufacturing precision
If control inputs are distributed equally across all actuators, then ease of operation is improved, but manufacturing precision deteriorates when actuators reach their limits
Solution Approach 1:
The control allocation assigns different control priorities to different actuators based on their functional importance and current status. Critical actuators receive higher priority control inputs while non-critical actuators receive reduced inputs, ensuring that control tasks are fulfilled with precision by prioritizing essential actuator contributions over equal distribution
3Stability of the object's composition
If the system operates with under-actuation due to actuator failures, then adaptability is improved, but stability deteriorates
Solution Approach 1:
The control allocation system is designed in advance to handle actuator failures by pre-configuring fallback control strategies. When actuators fail, the system activates pre-planned control redistribution patterns that maintain stability by smoothly transitioning to controlled operation with fewer actuators, preventing instability rather than reacting to it
Data Source
AI summary
A method of operating an under-actuated actuator system including a plurality of actuators (3), preferably for operating a multiactuator aerial vehicle (1), wherein the actuators (3) are individual propulsion units of the multiactuator aerial vehicle (1), each actuator having a maximum physical capacity umax, the method including: controlling the actuators (3) by with an actual control input u∈k computed from an allocation equation u=D−1up, wherein D−1 is an inverse allocation matrix and up∈m is a pseudo control input defined by a system dynamics equation m(x){umlaut over (x)}+c(x,{dot over (x)})+g(x)+G(x)up=fext, wherein x∈n is an n-dimensional configuration vector of the system, m(x)∈n×n is a state dependent generalized moment of inertia, c(x,{dot over (x)})∈n are state dependent Coriolis force, g(x)∈n are gravitational forces and fext∈n are external forces and torques, and G(x)∈n×m is a control input matrix which contains the information of under-actuation. The system is under-actuated if Rank (G(x))<n or both under-actuated and overly determined in case of k>m>n and Rank (G(x)D)<n, with k,m,n∈; using state feedback control to recurrently compute a desired pseudo control input up from the system dynamics equation. If at least one component of the desired pseudo control input up is greater than a corresponding maximum pseudo control input upmax that can be generated based on the actuator maximum physical capacity umax and based on positions (or characteristics and configurations) of the actuators within the system, prioritizing at least one of the components of up over the other components of up; and a) by using a prioritizing algorithm, solving the allocation equation for the at least one prioritized component of up before solving the allocation equation for the remaining components of up; or b) during state feedback control, adjusting a limiting value of the at least one prioritized component of up by an amount, while keeping respective limiting values of the remaining components of up essentially constant.