Three-Loop Flight Control System Design
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Classic feedback control laws for unstable aircraft flight systems require extensive flight testing and gain adjustments, limiting performance and robustness, and are not effective in stabilizing and navigating aircraft simultaneously.
Innovation Solution
A three-control-loop flight control system design incorporating an inner loop with an improved linear quadratic regulator (LQR) method, an outer loop with classic feedback summary gain design, and a steady-state trim search method to enhance stability, handling qualities, and reduce development time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If classic feedback control laws are used to stabilize the aircraft system, then system stability is improved, but flight test time and gain adjustment time increase significantly
Solution Approach 1:
The control system is divided into three independent loops: inner loop for stabilization using LQR, outer loop for guidance using classic feedback, and trim loop for steady-state optimization. This segmentation allows each loop to be tuned independently, reducing the overall complexity and time required for system adjustment and flight testing.
Solution Approach 2:
The LQR controller is designed offline to pre-optimize the stabilization gains for the inner loop. This preliminary design phase eliminates the need for extensive real-time flight testing to tune stabilization parameters, as the optimal gains are computed beforehand based on system models and performance criteria.
2Ease of operation
If classic feedback control laws are used to guide the aircraft in all maneuvers, then navigation capability is improved, but the system requires fine tuning of all gains which increases development time
Solution Approach 1:
The control system separates stabilization functions (inner loop with LQR) from guidance functions (outer loop with classic feedback). This segmentation allows the outer loop to focus solely on navigation and maneuvering without the complexity of simultaneous stabilization tuning, as the inner loop already handles stability independently.
Solution Approach 2:
The LQR-based inner loop acts as an intermediary that handles the complex stabilization tasks, allowing the classic feedback outer loop to operate with simpler gain structures focused on guidance. This intermediary layer reduces the complexity of gain tuning for the overall system.
3Productivity
If individual optimal search algorithm is manually computed and added into the system, then performance improvement is achieved, but engineering hours and development time increase
Solution Approach 1:
The LQR controller automatically computes optimal control actions based on pre-defined cost functions and system models, eliminating the need for manual optimal search algorithms. The system self-optimizes its control outputs in real-time based on state feedback, reducing engineering hours while maintaining high performance.
Solution Approach 2:
The LQR approach transforms the control problem into a parameter optimization problem during offline design, where optimal gain matrices are computed once based on system parameters and performance weights. This eliminates the need for continuous manual parameter adjustment during development and operation.
4Stability of the object's composition
If many error corrections and gain-scheduling techniques are introduced to stabilize the system, then system stability is improved, but control law development time increases
Solution Approach 1:
The control system is segmented into three loops with distinct objectives: LQR for stabilization, classic feedback for guidance, and trim for steady-state optimization. This segmentation eliminates the need for complex gain-scheduling techniques across the entire system, as each loop operates independently with its own simplified control strategy.
Solution Approach 2:
The stabilization function is extracted from the overall control system and handled independently by the LQR inner loop. This extraction removes the need for complex error corrections and gain-scheduling in the outer guidance loop, simplifying the control law development while maintaining system stability.
Data Source
AI summary
A flight control system is configured for controlling the flight of an aircraft utilizing a three control loop design to robustly increase system performance. An inner loop comprises an improved linear quadratic regulator (LQR) search method, and an outer loop comprises a classic feedback summary gain design. A third loop comprises a steady state trim search method.